© 2017 Marc Tobias Heinrichstarget site pharmacokinetics of moxifloxacin, linezolid and...

TARGET SITE PHARMACOKINETICS OF MOXIFLOXACIN, LINEZOLID AND PYRAZINAMIDE IN PATIENTS WITH MULTIDRUG-RESISTANT TUBERCULOSIS,

AND DOSE OPTIMIZATION BASED ON PHARMACOKINETIC-PHARMACODYNAMIC MODELING AND SIMULATION

By

MARC TOBIAS HEINRICHS

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2017

© 2017 Marc Tobias Heinrichs

To my family

4

ACKNOWLEDGMENTS

I would like to express my deepest appreciation to my mentor, Dr. Hartmut

Derendorf, for accepting me into his outstanding laboratory and for placing his trust and

confidence in my abilities. His philosophy and visions for pharmaceutical drug

development have had a great impact on my personal and professional development

over the years.

My sincere gratitude to my co-advisor, Dr. Charles A. Peloquin, for his strong

support and guidance throughout my Ph.D. studies, and for always being available

despite his busy schedule.

I would also like to thank my other committee members Dr. Kenneth H. Rand and

Dr. Sihong Song for their support and valuable feedback and advice.

I would like to thank our collaborators from Emory University, Dr. Henry M.

Blumberg, and in particular, Dr. Russell R. Kempker for his mentorship and

unconditional support, and for the great team player he is.

I would like to thank Dr. Sergo Vashakidze, Dr. Irina Sabulua, Dr. Shota

Gogishvili, Dr. Nino Bablishvili and Dr. Ketino Nikolaishvili from the National Center of

Tuberculosis and Lung Diseases, Tbilisi, Georgia, for their support and excellent work

on the clinical trials.

I am deeply grateful to Dr. George Drusano, Dr. Arnold Louie, David Brown and

the staff of the Institute of Therapeutic Innovation, Lake Nona, for teaching me how to

build and run the hollow fiber infection model system, and for their support during the

conduct of dynamic time-kill experiments. Sincere thanks to Dr. Drusano for his

mentorship and for broadening my horizons every day we worked together.

5

I would like to thank Dr. Juergen Bulitta and Dr. Stephan Schmidt for all their

support and expert insights on mathematical modeling and simulation principles and

applications.

My thanks also go to the professional chemists from the Infectious Disease

Pharmacokinetics Laboratory, Dr. Kyung-Mee Kim, Theodore Zagurski, Behrang

Mahjoub, Vaneska Mayor, Emily Graham, as well as Dr. Abdullah Saleh Alsultan, Dr.

Yasuhiro Horita and Dr. Eric Egelund from the Department of Pharmacotherapy and

Translational Research.

I would like to thank all students, interns and post-docs from the Pharmaceutics

Department. Special thanks go to Dr. Aline B. Barth, Dr. Sherwin K. Sy, Dr. Eduardo P.

Asin, Dr. Luning Zhuang, Dr. Girish Bende, Dr. Satyawan B. Jadhav, Dr. Mirjam N.

Trame, Dr. Ravi Singh, Dr. Jatinder K. Mukker, Dr. Alexander Voelkner and Dr. Nivea F.

Voelkner.

I would also like to thank Dr. Vikram Sinha, Dr. Yaning Wang, Dr. Lily Mulugeta

and Dr. Kevin Krudys for giving me the opportunity to work in the Division of

Pharmacometrics at the U.S. Food and Drug Administration.

Finally, I would like to thank Uta Schilling, my parents and my sister Jana for their

love and friendship and unconditional support.

For Chapter 1: discrete portions of this chapter were published in the AAPS

Journal, an official journal of the American Association of Pharmaceutical Scientists,

Copyright © American Association of Pharmaceutical Scientists, [AAPS J. 2017

Mar;19(2):334-342. doi: 10.1208/s12248-016-0020-1].[1] For Chapter 2: this manuscript

6

was accepted for publication in the Journal of Antimicrobial Chemotherapy (JAC),

Copyright © Oxford University Press, [doi: 10.1093/jac/dkx421].[2] For Chapter 3: this

manuscript was submitted to the European Respiratory Journal. For Chapter 4: this

paper was published in the Journal of Antimicrobial Agents and Chemotherapy (AAC),

Copyright © American Society for Microbiology, [Antimicrob. Agents Chemother., 61:

e00226-17, June 2017, doi: 10.1128/AAC.00226-17].[3] For Chapter 5: this manuscript

was submitted to the Diagnostic Microbiology and Infectious Disease (DMID) journal.

7

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES .......................................................................................................... 10

LIST OF FIGURES ........................................................................................................ 11

LIST OF ABBREVIATIONS ........................................................................................... 13

ABSTRACT ................................................................................................................... 14

CHAPTER

1 INTRODUCTION .................................................................................................... 16

Tuberculosis ........................................................................................................... 16 Treatment of Tuberculosis ...................................................................................... 16 Microdialysis in Clinical Drug Development and Dose Optimization ....................... 17

Historical Background ...................................................................................... 17 Utility of Microdialysis in Mycobacterial Infections ............................................ 19

2 MOXIFLOXACIN SERUM AND TARGET SITE PHARMACOKINETICS ................ 20

Introduction ............................................................................................................. 20

Patients and Methods ............................................................................................. 22 Study Population .............................................................................................. 22 Ethics................................................................................................................ 22

Serum Pharmacokinetics.................................................................................. 22 Tissue Pharmacokinetics.................................................................................. 23

Laboratory ........................................................................................................ 23 Radiology ......................................................................................................... 24 Data Analysis ................................................................................................... 24

Results .................................................................................................................... 24 Study Population .............................................................................................. 24

Serum Pharmacokinetics.................................................................................. 25 Tissue Pharmacokinetics.................................................................................. 25

Radiology ......................................................................................................... 26 Laboratory Results ........................................................................................... 26

Discussion .............................................................................................................. 27

3 LINEZOLID SERUM AND TARGET SITE PHARMACOKINETICS ........................ 38

Introduction ............................................................................................................. 38 Methods .................................................................................................................. 40

8

Study Population .............................................................................................. 40

Pharmacokinetics ............................................................................................. 40 Laboratory ........................................................................................................ 42

Radiology ......................................................................................................... 42 Data Analysis ................................................................................................... 42

Results .................................................................................................................... 43 Study Population .............................................................................................. 43 Serum Pharmacokinetics.................................................................................. 43

Tissue Drug Concentrations ............................................................................. 44 Radiology ......................................................................................................... 44 Laboratory Results ........................................................................................... 45

Discussion .............................................................................................................. 45

4 PYRAZINAMIDE SERUM AND TARGET SITE PHARMACOKINETICS ................ 60

Introduction ............................................................................................................. 60

Methods .................................................................................................................. 62 Study Population .............................................................................................. 62

Pharmacokinetics ............................................................................................. 62 Laboratory ........................................................................................................ 63 Radiology ......................................................................................................... 65

Data Analysis ................................................................................................... 65 Results .................................................................................................................... 66

Study Population .............................................................................................. 66 Serum Pharmacokinetics.................................................................................. 66

Tissue Concentrations ...................................................................................... 66 Radiology ......................................................................................................... 67 Laboratory Results ........................................................................................... 67

Correlations with Tissue Pyrazinamide Concentrations and pH ....................... 68 Discussion .............................................................................................................. 69

5 COMPARISON OF MYCOBACTERIUM TUBERCULOSIS STRAIN H37RA VS H37RV .................................................................................................................... 84

Background ............................................................................................................. 84

Materials and Methods............................................................................................ 87 Preparation of Drug Susceptibility Plates ......................................................... 87 Bacterial Culture ............................................................................................... 88

Inoculation of Drug Susceptibility Plates .......................................................... 88

Minimum Inhibitory Concentration (MIC) Determination ................................... 89 Results .................................................................................................................... 89

Growth Inhibition of Two Mtb Strains in the Presence of Anti-TB Agents ......... 89

H37Ra as a Good Surrogate for H37Rv ........................................................... 90 Comparison to Clinical Susceptibility Data – Both Laboratory Strains Predict

Clinical Susceptibility Equally Well ................................................................ 90 Discussion .............................................................................................................. 91

Conclusion .............................................................................................................. 93

9

6 LINKING PHARMACOKINETICS TO PHARMACODYNAMICS ............................. 98

Introduction ............................................................................................................. 98 Methods .................................................................................................................. 99

Antimicrobial Agents ......................................................................................... 99 Microorganism ................................................................................................ 100 Susceptibility Studies and Mutation Frequencies ........................................... 100 Hollow Fiber Infection Model .......................................................................... 100 Experimental Setup ........................................................................................ 101

Pharmacokinetic Validation ............................................................................ 102 Bioassay ......................................................................................................... 102 Microbiologic Response ................................................................................. 103 Pharmacokinetic-Pharmacodynamic Modeling ............................................... 103

Simulations and Probability of Target Attainment (PTA) ................................ 104 Results .................................................................................................................. 105

Microbiology ................................................................................................... 105 Time-Kill Curves ............................................................................................. 105

PK-PD Modeling and Simulation .................................................................... 106 Discussion ............................................................................................................ 108

7 SUMMARY ........................................................................................................... 120

LIST OF REFERENCES ............................................................................................. 122

BIOGRAPHICAL SKETCH .......................................................................................... 136

10

LIST OF TABLES

Table page 2-1 Study population characteristics for seven patients with drug-resistant

pulmonary tuberculosis ....................................................................................... 35

2-2 Non-compartmental analysis of serum moxifloxacin concentrations .................. 36

2-3 Comparison of free serum and cavitary moxifloxacin concentrations among patients with drug-resistant pulmonary tuberculosis ........................................... 37

3-1 Study population characteristics for 8 patients with drug-resistant pulmonary tuberculosis ........................................................................................................ 56

3-2 Non-compartmental analysis of serum linezolid concentrations ......................... 57

3-3 Free serum and tissue linezolid concentrations among patients with drug-resistant pulmonary tuberculosis ........................................................................ 58

3-4 Comparison of free serum and tissue linezolid concentrations among patients with drug-resistant pulmonary tuberculosis ........................................................ 59

4-1 Study population characteristics for 10 patients with drug-resistant pulmonary tuberculosis ........................................................................................................ 79

4-2 Non-compartmental analysis of serum pyrazinamide concentrations ................. 80

4-3 Comparison of free serum and cavitary pyrazinamide concentrations among patients with drug-resistant pulmonary tuberculosis ........................................... 81

4-4 Chest computed tomography (CT) scan characteristics of the resected lesion (n=7) ................................................................................................................... 82

4-5 Pathology characteristics of resected pulmonary tissue ..................................... 83

5-1 Minimum inhibitory concentration (MIC) values of isoniazid, rifampicin, pyrazinamide and ethambutol against Mtb H37Rv and Mtb H37Ra. .................. 94

5-2 MICs of the tested anti-tuberculous drugs in H37Ra, H37Rv and comparison to literature-reported MIC in clinical strains ........................................................ 95

6-1 Time-kill study design moxifloxacin and linezolid .............................................. 116

6-2 Pharmacokinetic parameters moxifloxacin and linezolid .................................. 117

6-3 Final parameter estimates PK-PD model ......................................................... 118

6-4 Model diagnostics ............................................................................................. 119

11

LIST OF FIGURES

Figure page 2-1 Moxifloxacin free + bound serum concentrations versus time in adults with

drug-resistant tuberculosis. ................................................................................ 33

2-2 Comparison of radiology, moxifloxacin lung tissue/serum concentration ratios and free lung tissue concentration.. .................................................................... 34

3-1 A representative picture of a resected lung lesion demonstrating the placement of the two microdialysis probes into diseased and non diseased lung tissue. ......................................................................................................... 50

3-2 Serum concentrations of linezolid versus time after dosing in 8 adults with drug-resistant pulmonary tuberculosis. ............................................................... 51

3-3 Correlation between peak serum linezolid concentration and dosages. ............. 52

3-4 A representative picture of a chest computed tomography scan showing the predominant lesion and a corresponding picture of the resected lesion for each patient where available. ............................................................................. 52

4-1 Serum concentrations of pyrazinamide versus time after dosing in 10 adults with drug-resistant pulmonary tuberculosis. ....................................................... 75

4-2 (A) Correlation between peak serum pyrazinamide concentration and dosages. (B) Correlation between free serum pyrazinamide concentration and cavitary pyrazinamide concentration. .......................................................... 76

4-3 Representative transverse CT views from the seven patients with films available for review.. ........................................................................................... 77

4-4 Representative hematoxylin and eosin stained photomicrographs ..................... 78

5-1 Schematic of how quadrant plates were divided and sectioned (a) and pictures of blank plates (b) and agar plates after incubation (c) (d). ................... 96

5-2 Side-by-side comparison of H37Ra and H37Rv MIC values on a logarithmic scale (y-axis) for 16 anti-tuberculosis drugs (x-axis) ........................................... 97

6-1 Time-kill plot moxifloxacin on a semi-logarithmic scale .................................... 108

6-2 Time-kill plot linezolid on a semi-logarithmic scale ........................................... 113

6-3 Probability of target attainment for moxifloxacin doses in log-phase and acidic phase growth .......................................................................................... 114

12

6-4 Probability of target attainment for linezolid doses in log-phase and acidic phase growth .................................................................................................... 115

13

LIST OF ABBREVIATIONS

AUC Area under the curve

Cmax

CV

DV

HFIM

Maximum concentration

Coefficient of variation

Dependent variable

Hollow fiber infection model

IDPL Infectious Disease Pharmacokinetics Laboratory

MAP

MDR

Maximal a posteriori probability

Multidrug resistant

MIC Minimum inhibitory concentration

MXF

NCTLD

Moxifloxacin

National Center for Tuberculosis and Lung Diseases

PD Pharmacodynamics

PK

PTA

Pharmacokinetics

Probability of target attainment

PZA

RSE

SD

Pyrazinamide

Relative standard error

Standard deviation

TB Tuberculosis

Tmax Time to maximum concentration

XDR Extensively drug resistant

14

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

TARGET SITE PHARMACOKINETICS OF MOXIFLOXACIN, LINEZOLID AND

PYRAZINAMIDE IN PATIENTS WITH MULTIDRUG-RESISTANT TUBERCULOSIS, AND DOSE OPTIMIZATION BASED ON PHARMACOKINETIC-PHARMACODYNAMIC

MODELING AND SIMULATION

By

Marc Tobias Heinrichs

December 2017

Chair: Hartmut Derendorf Major: Pharmaceutical Sciences

With the rise of multidrug-resistant tuberculosis (TB) over the years and the

limited development of new antimicrobials, there is an urgent need for new efficacious

anti-TB drugs and the optimization of current TB treatment. We hypothesize that

antibiotic concentrations at the target site, i.e., in cavitary lung lesions, may be too low

leading to resistance development und ultimately to treatment failure. Therefore, we

conducted clinical pharmacokinetic studies in patients with drug resistant pulmonary

tuberculosis with the goal to quantify target site exposures of moxifloxacin, linezolid and

pyrazinamide in these unique patient populations. An innovative technique of

microdialysis was used to measure free drug (pharmacologically active) concentrations

in excised lung lesions.

While large clinical trials are costly and time-consuming, in vitro studies (when

bridged to human patients using Monte Carlo simulations) can help to select potent drug

candidates and drug combinations to shorten TB treatment and prevent further

emergence of resistance. Consequently, we quantified drug effects using the hollow

15

fiber infection model system, a state-of-the-art in vitro pharmacokinetic-

pharmacodynamic (PK-PD) system. Here, Mycobacterium tuberculosis was exposed to

different drug concentration-time profiles including the ones found in TB patients. Time-

kill curves were obtained by plotting the change in bacterial population over time. By

making use of mechanism based pharmacokinetic-pharmacodynamic models and

Monte-Carlo simulations, optimal dosage regimens were identified that maximize

bacterial kill and suppress further emergence of resistance.

16

CHAPTER 1 INTRODUCTION

Tuberculosis

Tuberculosis (TB) is a deadly infectious disease caused by Mycobacterium

tuberculosis. It predominantly affects a patient’s lung and is the number one global

infectious disease killer today, causing 1.8 million deaths a year [4]. One third of the

world population is currently infected with TB [5]. Global emergence of multidrug-

resistant (MDR-) TB (resistant to at least isoniazid and rifampicin) makes the TB

epidemic an even greater problem as treatment outcomes among such patients are

substantially lower than those for drug susceptible TB [4,5]. The World Health

Organization (WHO) reports approximately half a million new cases of MDR TB per year

[5]. These patients need prolonged therapy with second line drugs that are costly, less

effective and often highly toxic. Furthermore, successful treatment outcome can be

expected in only about 50% of MDR TB patients [4]. Extensively drug resistant (XDR-)

TB is defined as resistance to isoniazid, rifampicin, fluoroquinolones and injectable

agents. Treatment failure is experienced in at least two thirds of XDR TB patients [4]. All

this stresses the urgent need for new anti-TB drugs and the optimization of current TB

treatment.

Treatment of Tuberculosis

Ideally, and according to the WHO treatment guidelines, susceptible TB is

treated with isoniazid, rifampicin, pyrazinamide and ethambutal for 2 months (initial

phase), followed by 4 months treatment (continuation phase) with isoniazid and

rifampicin, the two best TB drugs. In practice, however, the duration of treatment often

takes 9-12 months and success rates are around 90% due to poor adherence and

17

resistance emergence. For the treatment of MDR TB, any first-line agent to which the

isolate is still susceptible is used. In addition, a fluoroquinolone such as moxifloxacin or

levofloxacin is chosen, as well as one of the injectable agents (amikacin, capreomycin,

streptomycin, kanamycin) based on susceptibilities [6]. From the remaining second-line

drugs (cycloserine, ethionamide, para-aminosalicylic acid, linezolid) agents are added

until the patient receives 4-6 drugs to which the isolate is susceptible. Among the third

line drugs are bedaquiline, delamanid, clofazimine, amoxicillin/clavulanate,

meropenem/clavulanate, imipenem, clarithromycin and high-dose isoniazid [6].

Experts in the field take the view that some doses including the ones for

pyrazinamide, rifampicin and moxifloxacin among others may be too low and require

optimization in order to cure the patient, prevent relapse of the disease, and suppress

further emergence of resistance. Little is known about drug concentrations at the target

site, i.e., in cavitary lesions. Poor target site drug exposure may lead to development

and amplification of resistance and ultimately to treatment failure. A better

understanding of drug concentrations at the site of infection may help optimize TB drug

development and dosing strategies. Microdialysis is an innovative tool that allows for the

measurement of unbound drug concentrations in virtually any tissue of interest, such as

TB diseased lung tissue.

Microdialysis in Clinical Drug Development and Dose Optimization1

Historical Background

The principle of microdialysis was first applied in the early 1960s when animal

__________________________

1 Subchapter ‘Microdialysis in clinical drug development and dose optimization’ was originally published in the AAPS Journal. Deitchman AN, Heinrichs MT, Khaowroongrueng V, Jadhav SB, Derendorf H. Utility of Microdialysis in Infectious Disease Drug Development and Dose Optimization. AAPS J 2017;19. doi:10.1208/s12248-016-0020-1.

18

tissue biochemistry was studied by inserting push-pull cannulas and dialytrodes, among

others, into the tissue of interest, most often cerebral tissue of rodents [7]. In 1974, the

hollow fiber was introduced and its further development led to the needle probe, today’s

most commonly used microdialysis tool [7].

In the 1990s, some of the first pharmacokinetic studies of antiinfective agents in

humans were reported including a study on rifampicin penetration into various regions

of the human brain [8]. Besides the brain, microdialysis has been utilized in countless

other organs, of note the lung [9], bone [10], adipose and muscle [11]. As a minimally

invasive sampling technique, it is an option for clinical drug monitoring purposes of

antimicrobials in critically ill patients [12,13].

Given its minimally invasive character and that minimal volume is being removed

from the patient during sampling, microdialysis has been utilized as a tool in therapeutic

drug monitoring in infants, an extremely vulnerable patient population where blood

volume is limited [14]. When compared to other sampling techniques such as saliva

sampling, skin blister, nuclear imaging techniques, tissue biopsy, and sampling

epithelial lining fluid, microdialysis appears to be the most accommodating and suitable

method to monitor drug concentrations in the critically ill [15].

Microdialysis is currently being used in drug development and the FDA has

suggested its potential for use in assessing bioavailability and bioequivalence of topical

generic drug products [13].

In summary, while the microdialysis technique has historically been used in

animal studies, it is increasingly employed in humans and continues to be the only

19

sampling technique that can monitor the unbound drug concentrations over time in the

interstitium of virtually any tissue.

Utility of Microdialysis in Mycobacterial Infections

Mycobacteria are aerobic, acid-fast pathogens responsible for life-threatening

illnesses such as tuberculosis (Mycobacterium tuberculosis) and leprosy

(Mycobacterium leprae). Very few clinical microdialysis studies have been published in

this subspecialty.

One study used microdialysis to determine the free concentrations of levofloxacin

in excised cavitary lesions in patients with pulmonary multidrug-resistant tuberculosis

(MDR-TB) [9]. MDR-TB patients who were scheduled to undergo adjunctive surgical

resection were approached for enrollment in a clinical study designed to investigate the

cavitary penetration of levofloxacin via ex vivo microdialysis. A microdialysis probe was

inserted into the center of each excised lesion and the no-net-flux methodology was

used for calibration. No significant difference was observed between free levofloxacin

cavitary concentrations and free serum concentrations from samples drawn during

surgery at the time of cavitary removal (the time at which maximum serum

concentration was expected). While there was a high interpatient variability, the majority

of patients (66%) had Cmax values below the recommended minimum Cmax value. Based

on the findings of this study, optimal dosing can be determined by ensuring optimal

serum concentrations.

Similar to this study we determined target site pharmacokinetics of moxifloxacin,

linezolid and pyrazinamide in patients with drug-resistant pulmonary tuberculosis.

20

CHAPTER 2 MOXIFLOXACIN SERUM AND TARGET SITE PHARMACOKINETICS1

Introduction

The global health impact of tuberculosis (TB) is substantial. TB has emerged as

the leading cause of death due to an infectious disease with an estimated 1.8 million

deaths per year; TB is now one of the top 10 causes of mortality worldwide [5]. The

global emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB

is an enormous public health threat and major barrier to effective TB control. In the

recently adapted “End TB Strategy” one of the three main pillars of the pathway to

eliminate TB was to intensify research and innovation including the optimization of new

and currently available drugs [16,17]. One promising area of research aimed at

optimizing available treatments is the study of the pharmacokinetics of anti-tuberculosis

drugs, and in particular the concentrations of drugs at the site of disease in pulmonary

TB [18].

The fluoroquinolones are considered cornerstone drugs for the treatment of

drug-resistant TB and their use has been associated with a significantly higher odds of

treatment success among patients with MDR and XDR TB [19]. Moxifloxacin in

particular is a promising higher generation fluoroquinolone with potent in vitro and early

bactericidal activity against Mycobacterium tuberculosis (Mtb) [20] and activity against

non-replicating Mtb persisters in vitro [21]. Fluoroquinolones exhibit concentration-

__________________________

1 Chapter 2 was accepted for publication in the Journal of Antimicrobial Chemotherapy. Heinrichs MT, Vashakidze S, Nikolaishvili K, Sabulua I, Tukvadze N, Bablishvili N, Gogishvili S, Little B, Bernheim A, Guarner J, Peloquin CA, Blumberg HM, Derendorf H, Kempker RR. Moxifloxacin Target Site Concentrations in Patients with Pulmonary Tuberculosis Utilizing Microdialysis: A Clinical Pharmacokinetic Study. J Antimicrob Chemother doi: 10.1093/jac/dkx421

21

dependent killing and the pharmacokinetic-pharmacodynamic (PK-PD) indices Cmax/MIC

and AUC/MIC are both important in determining optimal drug activity [22–24]. Serum

drug concentrations are used for these indices; however, for any drug to exert its

maximal pharmacological effect it has to get to the target site at sufficiently high free

concentrations [23].

The primary organ in which Mtb causes disease is in the lung and lesions are

varied ranging from a small infiltrate to a cavitary lesion which is a hallmark of

progressive pulmonary TB. Advanced lung lesions are characterized by necrosis and

decreased vascularization, features that may not be conducive for drug penetration.

Available clinical data have shown that cavitary lesions are associated with worse

clinical outcomes including increased risk of relapse and development of acquired drug

resistance. One hypothesis is that this is due to lower drug concentrations in such

cavitary lesions [25]. Recent advancements in technology have created new

opportunities to carry out studies to address the important issue of drug concentration at

the site of disease. Recent work by Prideaux and colleagues utilized a matrix-assisted

laser desorption/ionization (MALDI) mass spectrometry imaging technique to investigate

the spatial distribution of moxifloxacin in infected human lung tissue among patients with

TB [18]; however, there is a lack of additional data and in particular no information on

moxifloxacin free drug concentrations in the lungs of patients with TB. In regards to the

fluoroquinolones, only free drug can penetrate into the bacterial cell and bind to its

target, DNA gyrase. In order to quantitatively capture free moxifloxacin concentrations

inside lung lesions, we utilized the method of microdialysis, an emerging technique that

allows for the measurement of unbound drug in the extracellular space of virtually any

22

tissue [26,27]. Improved knowledge regarding tissue penetration of anti-TB drugs will

help guide drug development and optimize drug dosing and management.

Patients and Methods

Study Population

Patients with culture-confirmed pulmonary TB receiving moxifloxacin and

scheduled to undergo adjunctive surgical lung resection were enrolled from the National

Center for Tuberculosis and Lung Diseases (NCTLD) in Tbilisi, Georgia. All patients

were receiving 400 mg moxifloxacin orally given by directly observed therapy (DOT) and

on the day of surgery received moxifloxacin orally with a few milliliters of water

approximately 2 hours prior to surgical resection. Five of the seven patients included in

this study were part of a previous report on the pharmacokinetics of pyrazinamide

where detailed study methodologies can be found [3].

Ethics

All study participants provided informed consent and the study was approved by

the NCTLD (IRB00009508), Emory University (IRB00062584), and University of Florida

(IRB201300419) Institutional Review Boards.

Serum Pharmacokinetics

On the day of surgery, serum samples were collected at 0, 2, 4, and 8 h after

receiving moxifloxacin. Another serum sample was collected at the time of lung

resection (approximately 2 hours after drug administration which was the expected Tmax

of moxifloxacin). The collected samples were stored in a -80°C freezer until shipment to

the University of Florida (UF) Infectious Disease Pharmacokinetics Laboratory (IDPL).

At the IDPL, drug concentrations were measured using a validated LC-MS-MS assay on

a Thermo Scientific TSQ Quantum Ultra LC-MS-MS system (SN: TQU03470) and an

23

Accela 1250 UHPLC pump (SN: 925147) with a model Accela Open PAL autosampler

(SN: 240091), a Dell Dimension computer and a Thermo Scientific Corp. Xcalibur 2.2

SP1.48 analytical software. The lower limit of quantification (LLOQ) was 0.2 μg/mL. The

moxifloxacin recovery from human plasma was 100%. The overall inter-batch precision

of quality controls ranged from 1.88 to 8.39%.

Tissue Pharmacokinetics

Immediately after surgical resection, microdialysis (µD) was performed in the ex

vivo lung tissue. The µD probe was inserted into the central area of the resected lesion.

The inner lesion location of probe placement was confirmed after microdialysis when

the lesion was bisected and placement was verified visually. As previously described,

the no-net flux method was utilized for calibration and determination of tissue

concentrations [3,9]. To perform µD, four different concentrations of moxifloxacin (0.5, 3,

10, and 20 μg/mL) in ringer’s solution were infused for approximately 35-40 minutes

each. The collected microdialysates were kept in a −80°C freezer until shipment to the

UF IDPL. A modification of the assay described above was used to quantify

moxifloxacin in microdialysate solution (free drug). Here, samples utilized to prepare the

standard curves were diluted in saline. The LLOQ was 0.02 μg/mL, and the overall inter-

batch precision of quality controls ranged from 5.16 to 6.98%.

Laboratory

Acid fast bacillus (AFB) smear and culture examinations were performed on

obtained sputum and tissue samples. Tissue samples also underwent pathology

examination. All laboratory methods are as previously described [3].

24

Radiology

When available, preoperative chest computed tomography (CT) scans were

reviewed independently by two Emory University chest radiologists. They described the

dominant abnormality as either a mass, cavitary or infiltrate lesion.

Data Analysis

Non-compartmental analysis was performed in Phoenix WinNonlin® and

apparent total body clearance and volume of distribution (CL/F and V/F), half-life (t1/2),

elimination rate constant (kel), maximum serum concentration and time at which it

occurred (Cmax and Tmax) as well as area under the concentration-time curve (AUC)

were determined. Concentration values for data points below the LLOQ were replaced

with half the LLOQ value. A tissue to serum concentration ratio was calculated using the

free serum concentration at time of surgical resection. Free serum concentrations were

calculated by multiplying total serum concentrations times expected fraction unbound

(0.49) [28,29]. The Mann-Whitney U test (or Wilcoxon Rank Sum test) [30] was used to

investigate potential differences in median free moxifloxacin lung tissue concentrations

and lung tissue to serum ratios between culture positive and culture negative patients

as well as between patients with different lesion types. Further data analyses were done

using SAS® software, version 9.4.

Results

Study Population

Seven patients undergoing surgical resection for drug-resistant TB were enrolled

(Table 2-1). The median age was 25 years; over half were male (57%) and had no

history of prior TB treatment before TB diagnosis (57%). No patients had HIV infection

or diabetes mellitus; 3 (43%) were co-infected with either hepatitis B (2) or C (1) virus.

25

The median body mass index (BMI) was 19.5 kg/m2, while median creatinine clearance

was 95.4 mL/min and albumin was 4.0 g/dL. One patient had isoniazid resistant and

rifampin susceptible TB, while 3 had MDR-TB (resistance to both isoniazid and rifampin)

and 3 had XDR TB (resistance to isoniazid, rifampin, ofloxacin and at least one

injectable second-line agent (i.e., amikacin, kanamycin, or capreomycin)). All patients

were receiving 400 mg of moxifloxacin daily at the time of surgery for a median of 266

days prior to the surgical procedure and at a median dose of 7.7 mg/kg.


The total serum concentration-versus-time profiles are shown in Figure 2-1.

Among the 7 patients, only 2 (29%) had Cmax concentrations within the recommended

range of 3-5 µg/mL based on a 400 mg daily dose.[31] The median t1/2 (7.03 h) was

similar to values reported in the literature for TB patients, while the Tmax (2.0) was

slightly higher. There was no significant correlation between moxifloxacin dose (mg/kg)

and serum Cmax (R=0.40, P Value=0.37). Further non-compartmental analysis (NCA)

results are shown in Table 2-2.

Tissue Pharmacokinetics

The median lung tissue concentration of free (non-protein-bound) moxifloxacin

was 3.37 µg/mL with a range of 0.81-5.76 µg/mL. In comparison to the serum free

concentration of moxifloxacin at the time of surgical resection (imputed based on well

recognized moxifloxacin protein binding literature values),[28,29,32,33] the median

tissue/serum-concentration-ratio was 3.2 (range 0.66-28.08) (Table 2-3); with the

exception of one subject all patients had ratios greater than 1. There was no significant

correlation between moxifloxacin free serum and tissue concentrations (R=-0.13, P

Value=0.78).

26

Radiology

Among the 7 patients, 6 had chest CT scans available for review. Cavitary (3)

and mass (2) lesions were the dominant abnormalities with the other main lesion

identified as a consolidation (1) (Table 2-3). For the one patient without an available CT

for review, the official read of the CT scan in Georgia reported the presence of a

cavitary lesion. The lowest free moxifloxacin lung tissue concentrations and tissue to

serum ratios were observed in patients with cavitary lesions, followed by mass type

lesions and one patient with a consolidation (Figure 2-2). However, there were no

significant differences in the median free moxifloxacin lung tissue concentrations and

lung to serum concentration ratios among the four patients with cavitary disease as

compared to the two patients with mass lesions.

Laboratory Results

(i) Pathology. All tissue samples revealed the presence of granulomas and

necrosis with most having areas of moderate to severe necrosis (5 of 7, 71%). Six

(86%) of 7 demonstrated vascularization and fibrosis surrounding granulomas, and

were AFB smear positive. No significant correlations were found between lung tissue

moxifloxacin concentrations based on the level of necrosis (R=0.26, P=0.58) or AFB

quantification (-0.17, P=0.71). Similarly, there was no significant correlation found

between the lung tissue to serum moxifloxacin concentration ratio based on the level of

necrosis (R=-0.04, P=0.94) or AFB quantification (R=-0.38, P=0.40).

(ii) Microbiology. Tissue cultures from three patients were positive for M.

tuberculosis (Table 2-3). When comparing the 3 culture positive to 4 culture negative

patients, there was a trend towards lower median moxifloxacin lung tissue

concentrations (1.25 versus 3.87) and median lung tissue to serum concentration ratios

27

(1.01 versus 15.21) in patients who were culture positive but the results were not

statistically significant. Of note, two of the three patients with a positive tissue culture

had the two lowest moxifloxacin tissue concentrations.

Discussion

We found excellent lung tissue penetration (including cavitary lesions) of

moxifloxacin in a cohort of patients with drug-resistant pulmonary TB who were

undergoing adjunctive surgery. Overall serum total drug exposure was relatively low in

our study population; median AUC and Cmax were 28.3 h*µg/mL and 2.6 µg/mL,

respectively, and the majority of patients (71%) had suboptimal peak concentrations

(below the recommended range of 3-5 µg/mL). These findings suggest the need for

dose optimization and highlight the potential benefit of therapeutic drug monitoring

(TDM) in the treatment of drug-resistant TB.

The serum drug concentrations among our study cohort were lower as compared

to two other studies reported in the literature. Among 12 young healthy volunteers,

Lubasch and colleagues observed a Cmax of 4.34 µg/mL and total AUC of 39.3 h*µg/mL

after a single dose of 400 mg moxifloxacin [34]. In another clinical pharmacology study

among nine pulmonary TB patients from Brazil receiving 400 mg of moxifloxacin daily,

the median Cmax and AUC were 6.13 µg/mL (range, 4.47-9.00) and 55 h*µg/mL (range,

36-79), respectively. The patient characteristics (median age, body weight and

creatinine clearance) of these patients were similar to our Georgian study cohort [35].

One explanation for the lower serum concentrations in our study population may be a

cohort selection bias, since subjects enrolled in this study were chosen to undergo

surgery due in part to their lack of clinical improvement after prolonged treatment. In

addition, anesthesia may have affected drug absorption on the day of surgery [36].

28

Premedication with morphine, pethidine and anticholinergics have been shown to effect

PK parameters as by delaying gastric emptying and consequently drug absorption,

along with the small volume of water administered with moxifloxacin prior to surgery

[37].

Interestingly, even in patients with low serum concentration a considerable

amount of drug was found in their lung tissue, and the lung concentrations were

noticeably higher than the serum moxifloxacin concentrations. The median free

(unbound to proteins) lung tissue concentration was 3.37 (range, 0.81-5.76). Tissue

concentrations may have been higher when compared to free serum concentrations for

a variety of potential reasons: clearance from the tissue may have been different

compared to serum; a delay in target site penetration; accumulation of moxifloxacin in

macrophages from which drug can be released again into the extracellular space

(similar to a depot effect). The accumulation of moxifloxacin in macrophages in vitro

was previously reported [38]. Also, for reasons mentioned above serum concentrations

on the day of surgery may have been lower than usual while there still was drug in the

tissue (depot effect) resulting in a greater tissue to serum concentration ratio. We

observed a broad range of tissue to serum concentration ratios (range 0.66-28.08;

median 3.20), which is mainly due to very low serum concentrations (close to zero) in

subjects 6 and 7 (their tissue concentration was close to the median of 3.37 µg/mL).

Without these two subjects a narrower range is obtained (0.66-7.70).

In conformity with our results, Prideaux and colleagues reported an average

moxifloxacin caseum to plasma concentration ratio of approximately 3 in both patients

receiving a single dose and multiple doses (steady state group) [18]. Total drug

29

concentrations in caseum [ng per g tissue] were determined after homogenizing the

respective tissue and compared to total serum concentrations [ng/mL]. Their work also

illustrated a heterogeneous distribution of several drugs (including moxifloxacin) within

the tissue between cellular and acellular parts of diseased lung. In general, whole tissue

homogenates have certain limitations such as the unknown tissue binding of a drug

(including inter-patient variability), the potentially heterogeneous distribution of a drug

within the tissue before homogenization (surrounding uninvolved lung tissue, fibrous

wall, necrotic center/caseum), and neglection of the intracellular accumulation of certain

drugs, for instance, inside immune cells. In such a way a part of moxifloxacin

accumulates inside macrophages and thus, will not be available for bacterial kill outside

of the cell [38] where persisting bacilli are typically found. In contrast, microdialysis,

which was used in our study, overcomes these issues as it measures only the unbound

drug that is the pharmacologically active moiety. Microdialysis is a minimally invasive

technique that has been utilized for several decades in drug development, clinical drug

monitoring and dose optimization of anti-infective agents but has only been scarcely

used to measure drug concentrations in the lung [26]. While it has been used in patients

in vivo post cardiothoracic surgery [39]; our group has used resected lung ex vivo to

perform microdialysis [3,9]. While this disallows the measurement of certain PK

parameters such as Cmax and AUC, it does allow for the use of the no net flux method of

calibration [40], which is considered the optimal method to obtain an accurate drug

concentration measurement using microdialysis. Additionally, using ex vivo lung tissue

limits any risk of harm to the patient. Another advantage of microdialysis is that it

measures drug concentrations in the extracellular space [26] where persisting bacilli are

30

mainly located [41]; eradicating this small population of bacilli remains a major

therapeutic challenge.

In another prospective open-label PK study, Breilh et al. investigated the degree

of moxifloxacin lung tissue diffusion at steady state in 49 patients undergoing lung

surgery for bronchial cancer [42]. The mean ratios between lung tissue homogenate

and plasma concentrations after intravenous and oral administration were 3.53 (SD +/-

1.89) and 4.36 (SD +/- 1.48), respectively. Although whole tissue concentrations are

difficult to interpret with respect to clinical relevance, these results were slightly higher

and yet similar to the drug concentration ratios we found and provide further evidence of

the high degree of lung tissue penetration of moxifloxacin. Higher tissue protein binding

as compared to plasma protein binding may be an explanation for higher tissue/plasma

ratios when measuring whole lung concentrations. One important factor for a higher

lung tissue to serum ratio (when compared to a TB lesion to serum ratio) is that

moxifloxacin penetration from uninvolved lung tissue into TB lesions may be hindered to

a certain extent. Unfortunately, we did not measure drug concentrations in the

surrounding lung tissue, which is a limitation being addressed in future studies.

Our study is subject to certain limitations. First, a small number of patients were

enrolled into this study which contributed to a considerable variability in the data. Free

serum moxifloxacin concentrations at the time of surgical resection were imputed based

on well recognized literature values for moxifloxacin protein binding

(~51%).[28,29,32,33] Inter-individual variability in the protein binding may have

contributed to the variability in free-tissue/free-serum-concentration ratios. Further, after

removal of the lesion via surgical resection, microdialysis was immediately performed;

31

this process took approximately 3 hours. Given the heterogeneous distribution of

moxifloxacin in TB lesions,4 drug redistribution between regions of high concentrations

(e.g. macrophage layers) and lower concentrations (e.g. necrotic foci) may have

contributed to the relatively high variability in free-tissue/free-serum-concentration

ratios. Moreover, for ethical reasons the measurement of in vivo moxifloxacin lung

concentrations over time was not feasible. Hence, lung tissue concentrations at solely

one time point per patient (immediately after lung tissue resection) were determined.

This prevents the calculation of a target site AUC. Since the AUC/MIC ratio represents

the most relevant PK-PD index for moxifloxacin, the AUC at the infection site would be a

valuable parameter to ascertain in future studies. Additionally, the relatively small

number of patients made it hard to determine if there are any identifiable predictors of

higher tissue penetration such as radiological or pathological features and the clinical

significance of low tissue concentrations.

Based on the rather low Cmax values in our study cohort and the recommended

target Cmax range of 3-5 μg/mL (total drug),[31] most patients would require an

increased dose of 600-800 mg. The use of higher doses in the 600-800 mg range was

previously suggested by Gumbo et al. based on an in vitro study where mycobacteria

were exposed to free moxifloxacin serum concentrations in the hollow fiber infection

model system.[43] However, our measured free lung tissue concentrations suggest that

more than half of the patients had sufficient target site exposure at a daily dose of 400

mg. The accumulation of moxifloxacin at the target site should thus be taken into

account in future in vitro PK-PD studies to further improve the translation from in vitro

experiments to clinical application.

32

In summary, moxifloxacin showed excellent penetration into the diseased tissue

of patients with pulmonary TB including those with cavitary disease as well as a variety

of other radiological lesion types. The findings of our study emphasize the important role

of moxifloxacin in second-line therapy as well as in patients with progressive and severe

lung lesions.

33

Figure 2-1. Moxifloxacin free + bound serum concentrations versus time in adults with drug-resistant tuberculosis.

34

Lesion

Type

Representative transverse CT views MXF median

Lung

tissue/

serum

ratio

fConc

tissue

Cavity ID: 1, 2* and 4

1.01 1.25

Mass ID: 3* and 6*

14.23 3.05

Conso-

lidation

ID: 7*

28.08 3.37

MXF, moxifloxacin; fConc tissue, free concentration in lung tissue (µg/mL) *The results for subjects 2, 3, 6 and 7 were reported in part in a previous report evaluating the tissue penetration of pyrazinamide [3]

Figure 2-2. Comparison of radiology, moxifloxacin lung tissue/serum concentration ratios and free lung tissue concentration. Among six patients with films available for review three main lesion types were identified including cavitary lesions, mass lesions and one patient with an infiltrate (consolidation).

35

Table 2-1. Study population characteristics for seven patients with drug-resistant pulmonary tuberculosis

Parameter Value^ (n=7)

Demographic characteristics

Male sex 4 (57)

Age, years 25.2 (20-54)

Georgian ethnicity* 4 (57)

Hepatitis C antibody positive 1 (14)

Hepatitis B surface antigen positive 2 (29)

Current alcohol use 0

Current tobacco use 2 (29)

Prior treatment for tuberculosis 3 (43)

Weight, kg 52.0 (49-74)

Body mass index, kg/m2 19.5 (15-25)

Laboratory values

Creatinine clearance,# mL/min 95.4 (72-141)

Albumin level, g/dL 4.0 (3.5-4.9)

Hemoglobin level, g/dL 13.0 (10.7-15.5)

Alanine aminotransferase level, U/L 14 (10-133)

Tuberculosis characteristics and treatment

Drug susceptibility pattern

Isoniazid monoresistant 1 (14)

Multidrug-resistant 3 (43)

Extensively drug-resistant& 3 (43)

Receiving 400mg moxifloxacin% 7 (100)

Moxifloxacin, mg/kg 7.7 (5.4-8.2)

Days receiving moxifloxacin 266 (13-415)

Type of Surgery

Lobectomy 3 (43)

Segmentectomy 4 (57)

^ Data are presented either as number (percentage) or median value (range) * 1 Armenian, 1 Azeri, 2 other # Using the Cockcroft-Gault equation [44] & resistance to isoniazid, rifampin, ofloxacin and at least one injectable second-line agent (i.e., amikacin, kanamycin, or capreomycin) % At time of surgical resection

36

Table 2-2. Non-compartmental analysis of serum moxifloxacin concentrations

Parameter^ Moxifloxacin (n=7)

Median (range)

kel (h-1) 0.099 (0.032-0.792)

t½ (h) 7.0 (0.9-21.9)

Tmax (h) 2.0 (1.8-2.0)

Cmax (µg/mL) 2.6 (0.24-4.5)

AUClast (h· µg/mL) 14.2 (0.94-22.2)

AUC0-∞ (h· µg/mL) 28.3 (1.1-49.3)

CL/F (L/h) 14.1 (8.1-353.6)

V/F (L) 142.5 (94.2-896.7)

^ kel, elimination rate constant; t½, half-life; Tmax, time to Cmax; Cmax, maximum serum concentration; AUClast, area under the concentration-time curve from time zero to time of last measurable concentration; AUC0-∞, area under the concentration-time curve from time zero to infinity; CL, clearance; V, volume of distribution; F, bioavailability (assumed to be one for purposes of analysis).

37

Table 2-3. Comparison of free serum and cavitary moxifloxacin concentrations among patients with drug-resistant pulmonary tuberculosis

ID Dose

(mg/kg)

Serum

concentration at

time of resection^

(µg/mL)

Tissue

concentration

(µg/mL)

Tissue/

serum

ratio

Tissue

Culture

Radiology

(dominant

lesion)

Pathology

necrosis/A

FB

staining

1 5.4 1.23 0.81 0.66 Positive Cavity 1/1

2 8.0 1.24 1.25 1.01 Positive Cavity 2/2

3 8.0 1.40* 1.74 1.24 Negative Mass 3/3

4 8.2 0.46 3.55 7.70 Positive Cavity 3/3

5 7.7 1.80 5.76 3.20 Negative Cavity 2/1

6 6.4 0.16 4.36 27.21 Negative Mass 3/2

7 5.7 0.12 3.37 28.08 Negative Consolidation 1/0

Median

(range)

7.7

(5.4-8.2)

1.23

(0.12-1.80)

3.37

(0.81-5.76)

3.20

(0.66-

28.08)

AFB, acid fast bacillus; ^Free serum concentration=measured moxifloxacin concentration x 0.49 [28,29,32,33] *Serum concentration at time of resection was simulated for subject 3 using a one-compartment body model Necrosis: 0, not present; 1 (rare), scattered within a field; 2 (moderate), confluent within a field; 3 (severe), present in multiple confluent fields AFB staining: 0, not present; 1, rare; 2, scattered in a field; 3, many in a field

38

CHAPTER 3 LINEZOLID SERUM AND TARGET SITE PHARMACOKINETICS

Introduction

The most recent report from the World Health Organization (WHO) estimates that

the incidence of new cases of multidrug-resistant tuberculosis (MDR TB) is nearly half a

million worldwide each year, a sobering statistic. However, there are reasons for

optimism [5]. In addition to the roll out of molecular tests that have significantly reduced

the time for detection of drug-resistance and led to improvements in patient care, the

armamentarium of new and repurposed drugs available to treat drug-resistant

tuberculosis (TB) has expanded over the last few years [45,46]. This has led to a

resurgence in TB clinical trials and there are now several ongoing randomized

controlled trials evaluating the efficacy of new and repurposed drugs in treating MDR

TB. As the results of these clinical trials are awaited, the WHO has provided updated

guidelines on the use of newly introduced drugs including bedaquiline, delamanid, and

linezolid [5]. In order to optimize drug selection and dosing, data on the drug penetration

into lung tissue among patients with pulmonary TB is urgently needed [47].

The predominant form of TB remains pulmonary disease with approximately 85%

of TB cases involving the lung. There is a diverse spectrum of lung disease with severe

disease characterized by bronchiectasis, fibrosis, and cavitary lesions. While the

presence of cavitary lesions are associated with worse clinical outcomes including

acquired drug-resistance and relapse, the underlying reason for these associations is

unclear [25,48,49]. The consensus thinking has been that it is due in part to lack of

adequate drug penetration into these complex lesions, and in certain patients with

cavitary lesions a prolongation of anti-tuberculosis treatment is recommended. The

39

study of drug penetration into lung tissue has recently been emboldened by the

availability and use of novel and innovative methods including microdialysis and MALDI

mass spectrometry imaging [27,50]. Recent publications have characterized the lung

tissue penetration of first-line and selected second-line drugs but there are little to no

data available for newly introduced anti-tuberculosis drugs including linezolid. Linezolid

has become a frequent component of treatment regimens for pre-extensively and

extensively drug-resistant tuberculosis and is now listed as a category 4 drug in the

latest WHO treatment guidelines [5]. Linezolid has narrow therapeutic index and there is

no consensus on the optimal dose to use among patient with drug resistant TB. A better

understanding of the lung tissue penetration should provide needed insight on the ideal

dosing strategy for linezolid and whether it is a good drug to use in patients with severe

destructive lung lesions.

The primary purpose of our was to determine lung tissue concentrations of

linezolid and the serum to tissue ratio among patients with drug resistant TB undergoing

adjunctive surgical resection in Tbilisi, Georgia. We chose to study linezolid given its

recent role out in the country of Georgia and its expanding and key role in treating drug-

resistant TB in general as demonstrated by its inclusion in new treatment guidelines and

in most clinical trials enrolling drug-resistant TB patients. An additional study aim was

to compare linezolid tissue concentrations in diseased and non-diseased lung. To

evaluate the target site concentrations of linezolid, we utilized the technique of

microdialysis (µD) which allows for the measurement of unbound (pharmacologically

active) extracellular drug concentrations at the site of disease. We have previously

shown this method to be successful in measuring anti-tuberculosis drug concentrations

40

among patients with TB [9]. Our long term goal is to provide clinicians knowledge they

can use to construct optimal treatment regimens for their individual patients with highly

resistant TB.

Methods

Study Population

Study participants were enrolled from the National Center for Tuberculosis and

Lung Diseases (NCTLD) in Tbilisi, Georgia. Patients with culture-confirmed TB who

were receiving linezolid and scheduled to undergo adjunctive surgical resection were

eligible for study enrollment. Treatment regimens for patients with pre-XDR and XDR

TB were individualized based on drug susceptibility testing (DST) results per WHO and

national Georgian guidelines [51]. All treatment was given through directly observed

therapy (DOT). For dosing of linezolid, all patients were receiving 600mg by mouth

daily. On the day of surgery, linezolid was given orally with a few milliliters of water. The

recommendation to perform adjunctive surgery was made by the NCTLD drug-

resistance committee as previously described [9,52]. All study participants provided

informed consent and the study was approved by the Georgian NCTLD, Emory

University, and University of Florida Institutional Review Boards.

Pharmacokinetics

Serum: Patients fasted overnight for a minimum of 8 hours the day prior to

surgery and received their daily oral dose of linezolid approximately two hours before

surgical resection. Serum samples were collected immediately before and 2, 4 and 8

hours after receiving the drugs. A serum sample was also collected at the time of

resection. Samples were kept in a -80°C freezer until shipped to the University of

Florida Infectious Diseases Pharmacokinetics Laboratory, Gainesville, FL.

41

Concentrations were measured using a validated liquid chromatography-tandem mass

spectrometry (LC-MS-MS) assay on a ThermoAcella HPLC system and a Thermo Ultra

triple quadrupole massspectrometer, a Dell computer and the Thermo Xcaliburdata

management system. The six-point standard curves ranged from 0.3 to 30.0 mcg/ml

linezolid with linearity extending above and below this range. The recovery of linezolid

from human plasma was approximately 87%. The overall validation precision for

linezolid quality control samples was 0.75 to 2.73%, respectively. A modification of this

assay (range 0.3 to 120 mcg/ml) was used to measure linezolid in microdialysis

samples. The standard curves for these analyses were diluted in saline instead of

plasma.

Microdialysis: Microdialysis (μD) was performed ex vivo on resected lung tissue

immediately after surgical removal. Guided by visual and manual inspection, two

separate semi-permeable μD probes each with a total length of 10 mm attached to a μD

infusion pump (μ Dialysis AB, Stockholm, Sweden) were inserted into the diseased and

non-diseased resected lung (Figure 3-1). The first probe was placed in the center of the

resected diseased lesion using a slit cannula introducer and the second probe was

placed in non-diseased lung surrounding the diseased lesion. Four different

concentrations of linezolid (0.5, 5, 25, and 100 μg/ml) in ringer’s solution were each

infused for approximately 35 minutes at flow rate of 1 μl/minute, and the recovered fluid

“dialysate” was collected into separate microvials. Up to 35 μl of dialysate was collected

for each linezolid drug concentration infusion which was then stored in an -80°C freezer

until shipment to the USA.

42

Laboratory

AFB Testing: All sputum and tissue acid-fast bacilli (AFB) smear microscopy

and culture were performed at the NCTLD National Reference Laboratory using

standard methodologies [53,54]. Each patient had a pre-operative sputum sample

collected as well as five tissue cultures from the resected lung lesion and surrounding

resected lung tissue.

Radiology

Pre-operative chest computed tomography (CT) scans when available were

reviewed independently by two Emory University chest radiologists. The dominant

abnormality from the resected lung was described by lesion type (cavity, mass, nodule,

or consolidation), dimension, presence of calcification, connection to bronchus, and for

cavitary lesions maximum wall thickness was measured. All lobes, including the lobe

with the dominant abnormality, were scored for the presence, size, and number of other

nodules or cavities, and for consolidation, bronchiectasis, bronchial impaction,

and parenchymal distortion.

Data Analysis

Data analyses were performed using SAS software, version 9.4 and for non-

compartmental pharmacokinetic analysis (NCA) Phoenix WinNonlin version 7.0 was

utilized. The following pharmacokinetic parameters were determined: maximal serum

concentration (Cmax), the time at which it occurred (Tmax), area under the serum

concentration-versus-time curve (AUC), volume of distribution divided by bioavailability

(V/F), clearance over the bioavailability (Cl/F), half-life (t1/2), and elimination rate

constant (Ke). The fraction of the dose absorbed (F) was assumed to be 1 for data

analysis. Free linezolid serum concentrations were calculated by multiplying the

43

measured serum linezolid concentration by (100%-31% [the estimated percent protein

binding provided for linezolid]) [55]. In comparing free serum and tissue drug

concentrations, the serum concentration from the time of surgical resection was used. A

proc univariate procedure was used to evaluate whether the difference between serum

and lung tissue linezolid concentrations was significantly different than zero using the

non-parametric sign test.

Results

Study Population

Eight patients undergoing surgical resection for drug-resistant TB were enrolled

(Table 3-1). The median age was 34 years. All patients were male and half had a

history of prior TB treatment prior to the diagnosis of drug resistant TB. No patients had

HIV, hepatitis B virus or hepatitis C virus infection; 1 (12.5%) had diabetes. The median

body mass index (BMI) was 23.8 kg/m2 the median creatinine clearance was 104.2

ml/min, and albumin was 4.3 g/dl. Three patients had multidrug-resistant, two pre-

extensively drug-resistant, and three extensively drug-resistant TB. Patients were

receiving linezolid at the time of surgical resection for a median of 194 days. All patients

were receiving 600 mg of linezolid given once daily, and the median dose by weight was

8.3 mg/kg (range, 7.6-9.9).


The serum concentration versus time graph for linezolid is shown in Figure 3-2.

Among the 8 patients receiving linezolid, the median Cmax concentration was 12.98

µg/ml (range 9.43-15.75). The median Tmax and t1/2 were 2 and 4.5 hours, respectively.

There was a significant correlation between weight based dosage and serum Cmax

(R=0.82, p=0.01, Figure 3-3). Further NCA results for linezolid are shown in Table 3-2.

44

Tissue Drug Concentrations

Linezolid concentrations in diseased and non-diseased lung tissue were

available for all patients. The median free (non-protein-bound) linezolid concentration in

diseased lung tissue was 3.57 µg/ml with a range of 0.81 to 7.09 µg/ml while the

median concentration in non-diseased lung was 3.85 µg/ml with a range of 1.17 to

10.24 µg/ml. There was a significant correlation between linezolid concentrations in

diseased and non-diseased lung (R=0.77, p=0.03) but no significant difference between

the two lung tissue concentrations (p=0.73). There was a trend toward higher linezolid

lung tissue concentrations in new versus previously treated patients in both diseased

(4.68 vs. 2.81 µg/ml, p=0.28) and non-diseased tissue (5.42 vs. 2.92 µg/ml, p=0.27) but

the differences were not significant.

The median free serum concentration of linezolid at the time of surgical resection

was 7.77 µg/ml and the corresponding median diseased tissue/serum linezolid

concentration was 0.49 (range, 0.18-0.92). There were no significant correlation

between weight-based linezolid dosage and lung tissue linezolid concentrations or

between serum linezolid concentration and diseased or non-diseased lung tissue

linezolid concentration. All individual serum and lung tissue linezolid concentrations and

corresponding ratios are shown in Tables 3-3 and 3-4, respectively.

Radiology

There were seven patients with computed tomography (CT) scans available for

reading by study radiologists. The one patient without an available CT was reported to

have a cavitary lesion on their official chest CT clinical read. Among the seven patients,

the predominant lesion in five cases was a nodule, with one patient each having a

cavitary and consolidative lesion. Four patients had pleural thickening, and none had

45

effusion, lymphadenopathy, calcifications or lesions connected to the airways. No

significant differences in linezolid tissue concentrations were seen by lesion type (data

not shown). A representative CT slice of the predominant lesions along with a

corresponding picture of the resected lesion for study patients where available are

shown in Figure 3-4.

Laboratory Results

In 5 (63%) of 8 resected lesions there was at least one sample with a positive

AFB smear including three resected tissue specimens with only one of five samples

having a positive AFB smear, one tissue specimen with two positive AFB smear

samples and one with three positive AFB smear samples (all ≤ 2+). All tissue samples

were culture negative.

Discussion

Among a cohort of patients with chronic drug-resistant TB undergoing adjunctive

surgical resection, we found that free linezolid concentrations were similar in diseased

and non-diseased lung and less than half of serum drug concentrations. Our results

represent the first measurement of free “extracellular, non protein bound” linezolid

concentrations in the lung among patients with tuberculosis. Given the increasing

importance of linezolid in the treatment of drug-resistant tuberculosis including its

inclusion in most new regimens being tested in clinical trials, our findings provide novel

and important pharmacokinetic data regarding linezolid. A better understanding of the

pharmacology of linezolid is essential given the optimal dose for treating tuberculosis is

currently unclear and it is a drug with a narrow therapeutic index.

46

While linezolid was initially developed to treat gram positive infections, it was

found to have potent activity against Mycobacterium tuberculosis (and other

mycobacterium) early on in its development [56,57]. With the rise of increasingly drug-

resistant M. tuberculosis isolates with few if any remaining susceptible drugs, linezolid is

now frequently included in treatment regimens. A randomized clinical trial adding only

linezolid to an existing background regimen among patients with extensively drug-

resistant TB not responding to treatment demonstrated that linezolid use led to

increased and high rates of sputum culture conversion [58]. A subsequent meta-

analysis finding a high sputum culture conversion and cure rate among 239 patients

treated for drug resistant TB with linezolid provided further favorable data regarding

drug effectiveness [59]. These clinical data along with earlier studies demonstrating

good “non lung” tissue penetration and more recent data indicating linezolid may have

activity against non replicating M. tuberculosis isolates have made linezolid a promising

drug for drug-resistant tuberculosis [60–63]. However, high rates of adverse events

including peripheral neuropathy which is dose dependent and usually irreversible and

bone marrow suppression with twice a day 600 mg dosing and reports of acquired drug

resistance found with the use of a lower dose (300 mg a day) have led to calls for

further pharmacokinetic and pharmacodynamic studies in an effort to determine optimal

dosing regimens [58,64].

Our results indicate that there is a relatively low lung tissue penetration of

linezolid into both diseased and non-diseased lung tissue among patients with

multidrug-resistant tuberculosis. In all eight patients the free linezolid concentration in

diseased lung was lower than serum concentrations as was the case for seven of eight

47

patients in regards to non-diseased lung as compared to serum. The lung tissue

penetration of linezolid (lung/serum ratio 0.49) is lower than we what we have previously

shown for levofloxacin (lung/serum ratio 1.33) and pyrazinamide (lung/serum ratio 0.77)

utilizing the same microdialysis method [3,9]. While our sample size was too small to

adequately evaluate for predictors of lung penetration, the trend towards lower lung

tissue concentrations of linezolid in patients previously treated for tuberculosis warrants

further study. This finding suggests that accumulating lung damage from multiple

episodes of TB may result in a change in lung tissue architecture decreasing drug

penetration.

The clinical significance of this relatively low drug penetration into lung for

linezolid is unclear. Although linezolid minimum inhibitory concentration (MIC) testing

was not performed on baseline M. tuberculosis isolates, which were not available, the

free linezolid drug concentrations in diseased lung were higher than a suggested

epidemiological MIC cutoff of 0.5 mg/L in all cases and above the generally accepted

clinical susceptibility breakpoint of 1 mg/L in seven of eight patients [65]. Additionally, in

seven of eight patients the linezolid concentration in diseased lung were higher than the

mutant prevention concentration found in 90% (MPC90) of Mtb isolates in one study of

1.2 mg/L [66]. The one patient with a linezolid concentration in diseased lung of < 1

mg/L received the lowest weight based dose and correspondingly had the lowest serum

drug concentration. Additionally, all patients had negative tissue cultures which is in

contrast to high rates of positive lung tissue cultures we have found among patients with

multidrug-resistant TB receiving traditional second-line drug regimens and undergoing

adjunctive surgery from Georgia [3,67]. In regards to the negative cultures it is important

48

to note that all study patients also were receiving clofazimine and over half also were

receiving bedaquiline. While our results suggest once a day 600mg dosing may provide

adequate lung tissue concentrations they also urge caution when using doses less than

600mg in patients with severe lung lesions.

Our results build on prior research describing the tissue penetration of various

second-line anti-tuberculosis drugs utilizing the method of microdialysis, which allows

for the measurement of free “active” drug at the site of disease and add to the scant

literature on the lung penetration of linezolid. The only prior report of linezolid lung

tissue concentrations was in a pediatric patient with multidrug-resistant tuberculosis who

underwent lung resection surgery [68]. This patient received their last dose of linezolid

36 hours before surgery and drug concentrations were obtained using whole tissue

homogenates which measure total drug concentration including extracellular and

intracellular and protein bound and non bound drug. Two early studies among healthy

volunteers and patients with obstructive lung disease found that linezolid concentrations

were much higher in epithelial lining fluid (ELF) as compared to in blood [69,70], and a

subsequent further study among patients with ventilator-associated pneumonia found a

penetration in ELF of approximately 100% [71]. These findings highlight that it may be

difficult to infer linezolid lung tissue concentrations among patients with tuberculosis

from ELF measurements and/or from data obtained from patients without TB disease

and stress the need for measurements at the site of disease.

Our study is subject to certain limitations. Our results were derived from a small

cohort of patients with drug-resistant TB who were deemed to be not responding well to

treatment and thus may not be representative of all patients with tuberculosis. However,

49

it also important to note that patients with severe lung lesions in multiple lung lobes

were generally not offered lung resection and it is possible penetration may be worse in

these patients. The cohort we studied did have serum pharmacokinetic parameters

similar to those reported in the literature indicating that they were metabolizing linezolid

similar to most patients with tuberculosis [72]. Additionally, given feasibility and ethical

constraints, we measured linezolid lung concentrations at only one point at time (ex

vivo) and thus we could not measure variation over time or calculate key

pharmacokinetic parameters including tissue AUC/MIC and time > MIC. Lastly, probe

placement was guided visually into the center of lesions and surrounding non-diseased

tissue, and it is unclear how placement variation may have affected results.

In summary, our findings provide novel data on linezolid penetration into lung

tissue among patients with tuberculosis. While we found a lower lung tissue penetration

compared to serum, lung tissue concentrations among patients receiving 600mg once

daily of linezolid were above utilized MIC and MPC values in almost all patients. In

regards to clinical implications, our results suggest that in patients with severe lung

lesions it may be prudent to combine linezolid with drugs that have good lung tissue

penetration.

50

Figure 3-1. A representative picture of a resected lung lesion demonstrating the placement of the two microdialysis probes into diseased and non diseased lung tissue.

51

Figure 3-2. Serum concentrations of linezolid versus time after dosing in 8 adults with drug-resistant pulmonary tuberculosis.

52

Figure 3-3. Correlation between peak serum linezolid concentration and dosages.

Figure 3-4. A representative picture of a chest computed tomography scan showing the predominant lesion and a corresponding picture of the resected lesion for each patient where available.

0

2

4

6

8

10

12

14

16

18

4 5 6 7 8 9 10 11 12

Ser

um

Co

nce

ntr

atio

n

(µg

/ml)

Dosage (mg/kg)

R=0.82, p=0.01

53

Patient Chest computed tomography Resected lesion

1 NA

2

3

54

4

5

6

7 NA NA

55

8

56

Table 3-1. Study population characteristics for 8 patients with drug-resistant pulmonary tuberculosis



Male sex 8 (100)

Age, years 34 (26-49)


Diabetes mellitus$ 1 (13)

Hepatitis C Ab positive 0

Hepatitis B surface antigen positive 0

HIV positive 0

Alcohol use 0

Tobacco use 5 (63)

Prior treatment for tuberculosis 4 (50)

Weight, kg 72.0 (61-79)

Body mass index, kg/m2 23.8 (20.2-24.1)

Laboratory values%

Creatinine clearance,# ml/min 104.2 (72.7-117.4)

Albumin level, g/dl 4.3 (4.1-4.6)

Hemoglobin level, g/dl 14.6 (14.1-15.0)

Alanine aminotransferase level, U/liter 24 (15-41)



Multidrug-resistant 3 (37.5)

Pre extensively drug-resistant 2 (25)

Extensively drug-resistant 3 (37.5)

Receiving linezolid 600mg once daily 8 (100)

Linezolid, mg/kg 8.3 (7.6-9.9)

Days receiving linezolid prior to surgery 194 (6-380)

Companion Drugs

Clofazimine 8 (100)

Imipenem 4 (50)

Bedaquiline 5 (63)

Clarithromycin 2 (25)

Type of Surgery

Lobectomy 3 (38)


^ Data are presented either as number (percentage) or median value (range) *1 other; $On Insulin; #Using the Cockcroft-Gault equation; %At time of surgical resection Notes: 1) All patients had negative pre operative sputum AFB smears and cultures; 2) No patient experienced a surgical or post surgical complication

57

Table 3-2. Non-compartmental analysis of serum linezolid concentrations

Parameter^ Linezolid (n=8)

Median (range)

Ke (h-1) 0.16 (0.11-0.29)

t½ (h) 4.48 (2.42-6.15)

Tmax (h) 2.0 (-)

Cmax (µg/ml) 12.96 (9.43-15.75)

AUClast(h· µg/ml) 66.61 (40.37-88.82)

AUC0-∞ (h· µg/ml) 103.70 (46.61-144.68)

CL/F (liters/h) 5.80 (4.15-12.87)

V/F (liters) 39.31 (30.05-53.59)

^ Ke, elimination rate constant; t½, half-life; Tmax, time to Cmax; Cmax, maximal serum concentration; AUC, area under the concentration-time curve; CL, clearance; V, volume of distribution; F, bioavailability (assumed to be one for purposes of analysis).

58

Table 3-3. Free serum and tissue linezolid concentrations among patients with drug-resistant pulmonary tuberculosis

Subject Dose

(mg/kg)

Free serum

concentration at

time of resection^

(µg/L)

Non-diseased

Lung Tissue

concentration

(µg/L)

Diseased Lung

Tissue

concentration

(µg/L)

1 9.23 7.73 10.24 7.09

2 11.54 10.06 4.27 6.60

3 8.33 8.79 3.43 4.27

4 7.50 7.24 2.03 1.30

5 7.69 7.71 6.01 4.22

6 6.19 3.68 1.17 0.81

7 8.33 5.87 1.25 2.91

8 10.53 10.54 4.97 2.75

Median 8.33 7.77 3.85 3.56

^ Free serum concentration=measured linezolid concentration x 0.69

59

Table 3-4. Comparison of free serum and tissue linezolid concentrations among patients with drug-resistant pulmonary tuberculosis

Subject Diseased

Lung/Serum

Non-diseased

Lung/Serum

Diseased/Non-

Diseased Lung

1 0.92 1.32 0.68

2 0.66 0.42 1.41

3 0.49 0.41 1.24

4 0.17 0.27 0.64

5 0.55 0.78 0.70

6 0.22 0.32 0.69

7 0.50 0.21 2.33

8 0.26 0.47 0.55

Median 0.49 0.41 0.70

60

CHAPTER 4 PYRAZINAMIDE SERUM AND TARGET SITE PHARMACOKINETICS1

Introduction

While progress has been made in the fight against tuberculosis (TB), the disease

continues to be a major public health problem and is now the leading cause of infectious

disease related mortality worldwide [5]. Major impediments to improving TB control

include inadequate funding, HIV co-infection, and the scourge of drug-resistant

Mycobacterium tuberculosis. In 2015, there were an estimated 580,000 patients with

rifampin resistant or multi-drug resistant tuberculosis (MDR TB) and 250,000 MDR TB

related deaths [5]. Recently introduced drugs, diagnostics, and global strategic plans

have given hope and a way forward to enhancing TB control. The World Health

Organization (WHO) recently adopted the End TB Strategy which provides a long-term

plan for combatting TB and has a goal of reducing the number of TB deaths by 90% by

2030 [73]. The plan is anchored by three pillars of action, including one emphasizing

intensified research and innovation. An emerging area of research that may help

optimize drug selection and dosing is the evaluation of anti-tuberculosis drugs

penetration into lung tissue [47].

While TB can invade any organ, it is predominantly a disease of the lungs and

lesion types and size are heterogeneous. The hallmark of progressive pulmonary

disease is the cavitary lesion, and this indicator of increased disease severity has been

associated with higher rates of acquired drug resistance, treatment failure and relapse

__________________________

1 Chapter 4 was originally published in the Journal of Antimicrobial Agents and Chemotherapy (AAC). Kempker RR, Heinrichs MT, Nikolaishvili K, Sabulua I, Bablishvili N, Gogishvili S, Avaliani Z, Tukvadze N, Little B, Bernheim A, Read TD, Guarner J, Derendorf H, Peloquin CA, Blumberg HM, Vashakidze S. Lung Tissue Concentrations of Pyrazinamide among Patients with Drug-Resistant Pulmonary Tuberculosis. Antimicrob Agents Chemother. 2017 May 24;61(6)

61

[25,49,74]. A prevailing thought to explain these associations is inadequate drug tissue

penetration. However, currently there are limited data regarding drug concentrations at

the site of disease among patients with pulmonary TB, due in part to the complexities

and practicalities in obtaining such measurements. Recent advances in technology and

the utilization of innovative methods have made the study of drug tissue penetration

more feasible and have invigorated this area of investigation [50,75]. The majority of

recent data evaluating anti-tuberculosis drug lung concentrations has been obtained

from animal models [76–78]. Further data is needed in humans to better to characterize

tissue concentrations in the unique environment and milieu of the TB diseased human

lung.

Our main study aim was to measure the lung tissue concentrations of

pyrazinamide among patients with pulmonary TB undergoing adjunctive surgical

resection. We chose to study pyrazinamide given its key role in treating both drug-

susceptible and resistant TB, and its ability to preferentially target semi-dormant bacilli

and sterilize lesions. Additional study aims were to evaluate predictors of pyrazinamide

tissue concentrations, and to measure the pH of resected lesions. Pyrazinamide is

converted into its active moiety, pyrazinoic acid (POA), within Mycobacterium

tuberculosis, and a low pH outside of the mycobacteria favors accumulation of POA

within the mycobacteria, leading to cell death. Thus lesion pH measurements are

essential to understanding the role of prolonged pyrazinamide use in patients with

chronic pulmonary disease [79]. To evaluate the target site concentrations of

pyrazinamide, we utilized the technique of microdialysis (µD) which allows for the

measurement of unbound (pharmacologically active) extracellular drug concentrations

62

at the site of disease. We have previously shown this method to be successful in

measuring anti-tuberculosis drug concentrations among patients with pulmonary TB [9].

Methods

Study Population

Study participants were enrolled at the National Center for Tuberculosis and

Lung Diseases (NCTLD) in Tbilisi, Georgia. Patients with culture-confirmed TB who

were receiving pyrazinamide and scheduled to undergo adjunctive surgical resection

were included. Treatment regimens were individualized based on drug susceptibility

testing (DST) results per WHO and local guidelines [80]. All treatment was given

through directly observed therapy. For pyrazinamide dosing, patients weighing ≤ 55

kilograms received 1200 milligrams daily while those > 55 kilograms received 1600

milligrams daily. On the day of surgery, pyrazinamide was given orally with a few

milliliters of water. The recommendation to perform adjunctive surgery was made by the

NCTLD drug-resistance committee as previously described and following

recommendations from international guidelines [9,52,80,81]. All participants provided

informed consent and the study was approved by the NCTLD, Emory University, and

University of Florida Institutional Review Boards.

Pharmacokinetics

Patients fasted overnight the day prior to surgery and received pyrazinamide

approximately two hours before surgical resection. Serum samples were collected

before and 1, 4 and 8 hours after receiving pyrazinamide, and at the time of resection.

Serum samples were kept in a -80°C freezer until shipped to the University of Florida

Infectious Diseases Pharmacokinetics Laboratory (IDPL), Gainesville, Florida, USA.

Concentrations were measured using a validated liquid chromatography-tandem mass

63

spectrometry (LC-MS-MS) assay on a ThermoAcella HPLC system and a Thermo Ultra

triple quadrupole massspectrometer, a Dell computer and the Thermo Xcaliburdata

management system. The six-point standard curves ranged from 2-100 mcg/ml

pyrazinamide with linearity extending above and below this range. The recovery of

pyrazinamide from human plasma was approximately 91%. The overall

validation precision for pyrazinamide quality control samples was 2.92 to 15.12%. A

modification of this assay was used to measure pyrazinamide in microdialysis samples.

The standard curves for these analyses were diluted in saline.

Microdialysis (μD) was performed ex vivo on resected tissue immediately after

surgical removal as previously described [9]. Briefly, a semi-permeable μD probe with a

total length of 10 mm attached to a μD infusion pump (μ Dialysis AB, Stockholm,

Sweden) was inserted into the center of the resected lesion using a slit cannula

introducer. Four different concentrations of pyrazinamide (5, 10, 30, and 50 μg/ml) in

ringer’s solution were each infused for approximately 35 minutes at flow rate of 1

μl/minute, and the recovered fluid “dialysate” was collected into microvials and then

stored in an -80°C freezer until shipment to the IDPL.

Laboratory

All sputum and tissue acid-fast bacilli (AFB) smear microscopy and culture were

performed at the NCTLD National Reference Laboratory using standard methodologies.

Each patient had a pre-operative sputum sample collected as well as five tissue cultures

from the resected lung lesion and surrounding tissue. Prior to culture, all tissue samples

were first homogenized with a tissue grinder before inoculating on to Lowenstein-

Jensen (LJ)-based solid medium. For cultures with growth of M. tuberculosis, first and

64

second-line DST was performed as previously described [53,54]. DST for pyrazinamide

was not performed.

DNA extraction was performed using the QIAamp DNA mini kit (Qiagen Inc.,

Valencia, CA) for all available tissue and sputum cultures positive for M. tuberculosis.

Extracted DNA was frozen at the NCTLD until shipment to Emory University where

whole genome sequencing was performed using the Illumina HiSeq2000 instrument.

The FastQ sequencing files for all M. tuberculosis isolates were uploaded to the Phylo-

resistance Search Engine (PhyResSE, http://phyresse.org, accession

keys 593375378609f78d466ecec7ceff6768, 75ba5a7139084e9f061875f303b6d822)

which is a web based tool to delineate M. tuberculosis antibiotic resistance and lineage

from whole-genome sequencing data [82].

After microdialysis, a pH test strip was inserted into the center of the bisected

lesion for pH measurement. Subsequently, one half of the lesion was formalin-fixed and

paraffin-embedded. Four micron sections were stained with hematoxylin and eosin and

acid fast (Fite) stains. Histopathology assessed the amount of inflammation

(mononuclear cells including multinucleated giant cells and polymorphonuclear

neutrophils), necrosis, fibrosis, vascularization, hemorrhage and amount and location of

acid fast bacilli. The amount of necrosis was quantified as rare when necrosis was

scattered and confined to one block, moderate when there were confluent areas in

multiple blocks and severe when the confluent areas of necrosis spanned several fields

in a block and were present in multiple blocks. The amount of organisms was quantified

as few when 1-5 organisms were observed in the submitted slides and large when there

were abundant organisms.

http://phyresse.org/

65

Radiology

Pre-operative chest computed tomography (CT) scans when available were

reviewed independently by two Emory University chest radiologists. The dominant

abnormality from the resected lung was described by lesion type (cavity, mass, or

consolidation), dimension, presence of calcification, connection to bronchus, and for

cavitary lesions maximum wall thickness was measured. Any lesion that contained a

gas-filled area was defined as a cavity; whereas a solid space-occupying lesion without

a gas-filled area was defined as a mass lesion. Lesions characterized by replacement of

the alveolar space with liquid were defined as a consolidation.

Data Analysis

Data analyses were performed using SAS software and for non-compartmental

pharmacokinetic analysis Phoenix WinNonlin was utilized. The following

pharmacokinetic parameters were determined: maximal serum concentration (Cmax), the

time at which it occurred (Tmax), area under the serum-versus-time curve (AUC), volume

of distribution divided by bioavailability (V/F), clearance over the bioavailability (Cl/F),

half-life (t1/2), and elimination constant (Ke). The fraction of the dose absorbed (F) was

assumed to be 1 for data analysis. Free pyrazinamide serum concentrations were

calculated by multiplying the measured serum pyrazinamide concentration by (100%-

15% [the midpoint of the range provided in the package insert for pyrazinamide]). In

comparing free serum and tissue drug concentrations, the serum concentration from the

time of surgical resection was used. For one patient, a one compartment model was

used to calculate the serum pyrazinamide at the time of surgical resection as this

sample was unavailable.

66

Results

Study Population

Ten patients undergoing adjunctive surgical resection for drug-resistant TB were

enrolled (Table 4-1). The main indication for surgery (90%) was the presence of a

localized lesion along with a high likelihood of relapse based on clinical status, level of

drug resistance and radiological lesion appearance. The median age was 30 years;

most were male (80%) and had no history of prior TB treatment (70%). One (10%)

patient had diabetes, and 2 (20%) were co-infected with either hepatitis B or C virus.

The median body mass index was 19.5 kg/m2, while median creatinine clearance was

91.1 ml/min and albumin was 4.2 g/dl. Two patients had isoniazid-resistant, rifampin-

susceptible TB while 8 had MDR TB (including 2 with extensively drug-resistant [XDR]

TB). Patients were receiving pyrazinamide prior to surgical resection for a median of

363 days. Eight (80%) patients were receiving a pyrazinamide dose of 1600 mg per day

and the median dose by weight was 24.7 mg/kg (range, 22.5-33.3).


The serum concentration versus time graph for pyrazinamide is shown in Figure

4-1. Among the 10 patients, 9 (90%) had pyrazinamide Cmax concentrations within the

recommended range of 20-60 µg/ml. The median t1/2 (2 h) was similar to values reported

in the literature while the Tmax (11.7) was slightly higher. There was a significant

correlation between weight based dosage and serum Cmax, as shown in Figure 4-2a (R=

0.71, P=0.02). Further results are shown in Table 4-2.

Tissue Concentrations

Serum and tissue concentrations were available for 9 of 10 patients receiving

pyrazinamide. One patient was excluded due to inadequate collected dialysate volume.

67

The median free (nonprotein-bound) lung tissue concentration of pyrazinamide was

20.96 µg/ml, with a range of 13.95-40.17 µg/ml (Table 4-3). In comparison to the free

serum concentration of pyrazinamide at the time of surgical resection, the median

tissue/serum pyrazinamide concentration ratio was 0.77 (range, 0.54-0.93). There was

a significant correlation between free serum and tissue pyrazinamide concentrations as

shown in Figure 4-2b (R=0.88; P=<0.01).

Radiology

There were 7 patients with CT scans available for reading by study radiologists.

For the 3 patients without preoperative CT scans for review, obtained radiological

reports indicated all patients had cavitary lesions with a maximum diameter between 2.1

and 3.5 cm. Among the seven patients with CT scans available for review, mass (3),

and cavitary (3) lesions were most common and one patient had a consolidation lesion.

The majority of patients had pleural thickening (8) and lesions which were connected to

an airway (6). Lymphadenopathy was rare (1) and calcifications were present in four

patients. A representative CT slice of the predominated lesion for the seven patients

with available films for review is shown in Figure 4-3.

Laboratory Results

Pathology: Pathology examination was performed on all resected tissue

specimens and full results are shown in Table 4-4 and Table 4-5. Tissue specimens

from each patient had granulomas and necrosis present with most having areas of

moderate to severe necrosis (7 of 10, 70%). Tissue specimens for 8 of 10 (80%)

patients had a positive acid fast stain in areas of necrosis. Most tissue specimens

demonstrated vascularization (90%) and fibrosis (90%) surrounding granulomas.

68

pH: The median tissue pH value was 5.5 with a range of 5-7.2. Only two tissue

samples had a pH of ≥ 7.0; including one cavitary and one mass lesion. The two tissue

samples with a pH of 7.2 were the only two to have severe necrosis and a high numbers

of acid-fast staining organisms on histopathology examination.

Microbiology and Sequencing: Tissue cultures from two patients (20%) were

positive for M. tuberculosis. One patient had 3 of 5 positive tissue cultures while the

other had all 5 tissue cultures positive. The tissue pH values of these patients were 5.5

and 7.2 . None of the M. tuberculosis isolates had any pncA or rpsA genetic mutations

identified on whole genome sequencing to indicate pyrazinamide resistance.

Correlations with Tissue Pyrazinamide Concentrations and pH

In comparing the association of lesion type and drug tissue penetration, there

was no significant difference between the mean free tissue concentrations (22.1 versus

24.5 µg/ml, P=0.71) or tissue to serum pyrazinamide concentration ratios (0.78 versus

0.73, P=0.67) in cavitary versus mass lesions, respectively. Furthermore, in the seven

patients with a CT for review, no significant differences were seen in pyrazinamide

tissue concentrations or tissue to serum concentration ratios in regards to lesions with

and without calcifications or lesions open or not open to an airway. In correlating

pathology findings with drug tissue penetration, there was a significant negative

correlation with free tissue pyrazinamide concentrations and increasing amounts of

necrosis (R= -0.66, P=0.04) and AFB staining organisms (R= -0.75, P=0.01) as

quantified on pathology examination. A representative hematoxylin and eosin

photomicrograph displaying the level of necrosis in the resected lesions of the nine

patients with a tissue pyrazinamide concentration available is shown in Figure 4-4.

There was a similar trend of negative correlation found between the ratio of tissue to

69

serum pyrazinamide concentrations and amounts of necrosis and AFB organisms;

however, the association was nonsignificant (data not shown). In comparing tissue

samples with a pH ≤ 5.5 versus ≥7.0 there was an association with higher pH and

amount of AFB staining organisms (p=0.01) but no association with amount of necrosis

or inflammation as measured by amount of polymorphonuclear leukocytes.

Discussion

Among a cohort of chronic TB patients undergoing adjunctive surgical resection,

we found good penetration of pyrazinamide into TB diseased pulmonary tissue including

in cavitary, mass and consolidation type lesions. All patients had a tissue to serum

concentration ratio ≥ 0.54 (range 0.54-0.93) and there was a significant correlation of

serum and tissue pyrazinamide concentrations indicating that optimizing serum

concentrations should correspondingly optimize lung tissue concentrations. Additionally,

we report the first pH lung tissue measurements among TB patients in over fifty years.

Our findings of an acidic pH in the large majority (80%) of chronic lesions provides

reassuring evidence of an environment conducive to the activity of pyrazinamide. Our

findings of drug tissue penetration and acidic pH tissue measurements support the use

of pyrazinamide among patients with pulmonary TB and highlight its importance in both

drug-susceptible and multi-drug resistant anti-tuberculosis treatment regimens.

Our study results demonstrating that pyrazinamide penetrates well into various

lesions types among patients with pulmonary TB are reassuring given the importance of

pyrazinamide in targeting dormant M. tuberculosis organisms and hence being a key

sterilizing agent. The range of tissue to serum free pyrazinamide drug concentration

ratios was narrow with most patients having a penetration ratio close to the median

value of 0.77, indicating that good tissue penetration can likely be expected in most

70

patients. It is also worth highlighting that our results were among patients with chronic

pulmonary TB disease who had lesions characterized histopathologically by fibrosis and

necrosis; lesions expected to be harder for drugs to penetrate. Prideaux et al, recently

published the only other study to date evaluating the lung penetration of pyrazinamide

among human patients [83]. Utilizing tissue homogenate drug concentrations they found

an average caseum/plasma pyrazinamide ratio of approximately 0.50 with all patients

having a ratio less than one as in our study. While similar to our results, the slight

difference in tissue penetration ratio may have been due to differences in technique as

we compared free unbound pyrazinamide concentrations in contrast to total

pyrazinamide (protein-bound and unbound and extracellular and intracellular)

concentrations [83]. Prideaux et al, also used a matrix-assisted laser

desorption/ionization (MALDI) mass spectrometry imaging method to demonstrate a

homogenous distribution of pyrazinamide and its active metabolite pyrazinoic acid

throughout lesions including the cavitary wall, caseum, and cellular components of

lesions. These findings complement our study results which focused on measuring the

amount of free pyrazinamide in the center of diseased lung lesions and highlight the

pervasive spread of pyrazinamide throughout TB lung lesions.

Our findings revealed an inverse association between pyrazinamide tissue

concentrations and increasing amounts of tissue necrosis and AFB staining organisms

on histopathology examination. To our knowledge this is the first time this relationship

has been demonstrated and while the causal pathway of association is unclear, it

suggests that pyrazinamide either has lower penetration into more severe lung lesions

as characterized by necrosis and bacilli burden or that lower penetration may be

71

associated with increased progression of lung lesions. Efforts to find a clinical correlate

of pathology findings such as high resolution CT scan would be beneficial and needed

in order to study the clinical utility of this association.

Our tissue pH results are the first reported lung tissue pH measurements among

patients with pulmonary TB since 1953. Our results showing an acidic and favorable

extracellular environment (median pH 5.5) to the activation of pyrazinamide are in

contrast to the prior report from Wesier et al. in which they found tissue pHs ranging

from 6.1-7.2 [84]. For their measurements they tested the supernatant from frozen and

subsequently homogenized resected lung tissue where as we measured pH in the

center of resected lesions specifically targeting the liquefied caseum directly after

surgery. Further study and validation of lung tissue pH measurements among TB

patients is needed for a better understanding of extracellular conditions at the site of

disease; data especially important in regards to activity of pH dependent drugs such as

pyrazinamide which is up to 20 times more active at a pH of 5.5 compared to 6.8 [85]. If

chronic lung lesions due to TB maintain a low pH environment for a prolonged period as

our findings suggest this would provide rationale for potentially continuing pyrazinamide

for longer than two months.

In agreement with a mice study by Lanoix et al, we did not find pyrazinamide

drug resistant mutations to explain the persistent growth of M. tuberculosis [78]. In non-

responding C3HeB/FeJ mice, Lanoix et al found that pyrazinamide resistant M.

tuberculosis isolates from lung caseous lesions never exceeded 1% of the total

population which is in line with the lack of pncA or rpsA drug mutations among 11 M.

tuberculosis isolates from our two patients with positive tissue cultures. There are

72

various possible explanations for the persistent culture positivity in our two patients

including the presence of highly drug-resistant M. tuberculosis isolates (pre-XDR and

XDR) and inadequate treatment regimens. It is also possible that the neutral tissue pH

(7.2) found in one patient contributed to pyrazinamide inactivity and persistent culture

growth. While this patient had unavailable tissue pyrazinamide concentrations, the free

serum pyrazinamide concentration was high at 41.04 µg/ml and assuming a low

penetration of 0.54, a low tissue concentration is an unlikely explanation.

Our study results demonstrate that when selecting pyrazinamide dose based on

the WHO endorsed dose of 25 mg/kg, peak pyrazinamide concentrations with the

recommended range of 20-60 µg/ml can reliably be achieved. However, there is

renewed debate on whether higher serum concentrations of pyrazinamide would be

beneficial. Early studies using daily doses of pyrazinamide between 30-50 mg/kg

indicated higher efficacy but concerns for hepatotoxicity led to a decreased dose [86]. A

recent analysis of data from three clinical trials evaluating high dose rifampin found a

steep exposure-response relationship between pyrazinamide Cmax concentrations

(range 15-55 µg/ml) and time to sputum culture conversion irrespective of rifampin dose

[87]. If these results are confirmed and a higher pyrazinamide dose is shown to be well

tolerated the use of higher pyrazinamide doses is likely to be revisited. In the scenario

of aiming for increased pyrazinamide exposure, our results along with previous reports

suggest that you can predictably achieve a higher serum concentration with a higher

weight based dose [86,88]. Similar to a prior study, it is also important to note we found

a high variability in pharmacokinetic parameters including clearance and volume of

73

distribution among our small sample of patients [89]. Larger studies will be needed to

study predictors of pyrazinamide pharmacokinetic parameters.

Our study is subject to certain limitations. These include the measurement of

pyrazinamide tissue concentrations at only one time point and in one location within the

resected lesion. We timed the administration of the pyrazinamide on the day of surgery

to correlate with expected time to serum Tmax; however, it is not known if the time to

tissue Tmax is similar or whether there is a delay which could have potentially led to an

underestimation of tissue pyrazinamide concentrations. Additionally, our microdialysis

approach allowed us to obtain free pyrazinamide concentrations at only one

intralesional location preventing us from determining lesional distribution. We targeted

the caseous center of resected lesions as this has been considered to be the area with

numerous extracellular bacilli and limited immune response [90]. It is also unclear how

the delay from lung resection to the measurement of tissue pH (~3 hours) may have

affected pH results. The targeting of the relatively acellular caseous center of resected

lesions is likely to have limited any effect of cellular death on lesion pH. To resolve this

uncertainty, we implementing the use of a micro pH electrode and will compare tissue

pH readings intraoperatively using the electrode to measures taken three hours later

with both the electrode and pH test strips. In regards to lung tissue culture results, the

use of solid versus liquid culture medium may have decreased the sensitivity of

detection of M. tuberculosis growth while the discordance between tissue AFB smear

and culture results may have been a result either of M. tuberculosis organisms that

were nonviable or in a metabolically dormant nonculturable state [91]. Further study

would be required to address these culture based questions and their implications.

74

In summary, our results provide encouraging data in regards to both the reliable

and good tissue penetration of pyrazinamide into diseased lung and the favorable acidic

environment of most chronic tuberculous lesions which promotes the bactericidal and

sterilizing activity of pyrazinamide. These data offer confirmation and possible rationale

for the importance of pyrazinamide in treatment regimens for both drug-susceptible and

resistant TB and inclusion in most new drug combinations being tested.

75

Figure 4-1. Serum concentrations of pyrazinamide versus time after dosing in 10 adults with drug-resistant pulmonary tuberculosis.

76

Figure 4-2. (A) Correlation between peak serum pyrazinamide concentration and dosages. (B) Correlation between free serum pyrazinamide concentration and cavitary pyrazinamide concentration.

77

Figure 4-3. Representative transverse CT views from the seven patients with films available for review. Three main lesions types were identified including a) cavitary lesions, b) mass lesions, and c) one patient with a consolidation.

78

Figure 4-4. Representative hematoxylin and eosin stained photomicrographs for each of the nine patients with tissue pyrazinamide concentrations (listed) available (original magnification 4X). Cases in row a) were classified as confluent severe necrosis as in addition to what is presented in the photomicrograph there was necrosis in other blocks (2 to 3) studied. Cases in row b) were classified as moderate necrosis, and cases in row c) were classified as having rare necrosis as this was only present in one block of 2 to 3 studied.

79

Table 4-1. Study population characteristics for 10 patients with drug-resistant pulmonary tuberculosis



Male sex 8 (80)

Age, years (range) 30.2 (15-54)


Diabetes mellitus& 1 (10)

Hepatitis C antibody positive 1 (10)

Hepatitis B surface antigen positive 1 (10)

Alcohol user 0

Tobacco user 3 (30)

Retreatment TB Case 3 (30)

Weight, kg 53.0 (48-71)

Body mass index, kg/m2 19.5 (15-22)

Laboratory values

Creatinine clearance,# ml/min 91.1 (52-155)

Albumin level, g/dl 4.2 (3.5-4.9)

Hemoglobin level, g/dl 13.7 (12.4-15.5)

Alanine aminotransferase level, U/liter 18 (10-133)



Isoniazid monoresistant 1 (10)

Isoniazid and ofloxacin resistant 1 (10)

Multidrug-resistant 6 (60)

Extensively drug-resistant 2 (20)

Receiving pyrazinamide% 10 (83)

1200 mg daily dose 2 (20)

1600 mg daily dose 8 (80)

Pyrazinamide, mg/kg 24.7 (22.5-33.3)

Days receiving pyrazinamide prior to surgery 363 (120-504)

Indication for surgical resection

Treatment failure and localized lesion 1 10)

High risk of relapse and localized lesion 9 (90)

Type of Surgery

Lobectomy 5 (50)


^ Data are presented either as number (percentage) or median value (range) * 1 Armenian, 1 Azeri, 2 other &On insulin # Using the Cockcroft-Gault equation % At time of surgical resection

80

Table 4-2. Non-compartmental analysis of serum pyrazinamide concentrations

Parameter^ Pyrazinamide (n=10)

Median (range)

Ke (h-1) 0.059 (0.039-0.13)

t½ (h) 11.7 (5.3-17.6)

Tmax (h) 2.0 (1.7-4)

Cmax (µg/ml) 37.8 (27.1-54.7)

AUClast(h· µg/ml) 246.7 (69.6-353.1)

AUC0-∞ (h· µg/ml) 827.6 (208.5-1139.7)

CL/F (liters/h) 1.9 (1.4-7.7)

V/F (liters) 36.4 (28.6-58.5)

^ Ke, elimination rate constant; t½, half=life; Tmax, time to Cmax; Cmax, maximal serum concentration; AUC, area under the curve; CL, clearance; V, volume of distribution; F, bioavailability (assumed to be one for purposes of analysis).

81

Table 4-3. Comparison of free serum and cavitary pyrazinamide concentrations among patients with drug-resistant pulmonary tuberculosis

Subject Dose of

pyrazinamide

(mg/kg)

Serum concentration at time of

resection^ (µg/ml)

Tissue

concentration

(µg/ml)

Tissue/serum

concentration ratio

1 33.33 41.04 NA& NA

2 24 28.03 25.06 0.89

3 24 25.67* 13.95 0.54

4 30.77 28.91 19.78 0.68

5 25.40 25.44 19.29 0.76

6 32 44.71 40.17 0.90

7 22.53 34.13 21.98 0.64

8 29.63 27.72 25.76 0.93

9 22.86 26.95 20.96 0.78

10 22.86 23.00 17.75 0.77

Median 27.87 20.96 0.77 (0.54-0.93)

^ Free serum concentration=measured pyrazinamide concentration x 0.85[92] &No cavitary concentration was available for subject 1 due to low dialysate volume *Serum concentration at time of surgical resection was estimated for this patient with a one-compartment pharmacokinetic model

82

Table 4-4. Chest computed tomography (CT) scan characteristics of the resected lesion (n=7)*

ID Dominant

Lesion

Maximum

Wall

Thickness

(mm)

Maximum

Transverse

Diameter

(mm)

Maximum

Sagittal

Diameter

(mm)

Connection to Bronchus

Calcification

1 NA - - - - - 2 Cavity 8 14 36 Yes No 3 Mass - 34 37 Yes Yes 4 NA - - - - - 5 Mass - 58 54 No Yes 6 Mass - 77 60 No Yes 7 NA - - - - - 8 Cavity - 54 70 Yes No 9 Consolidation - 62 31 Yes No 10 Cavity 8 49 34 Yes No

* 7 patients had chest CT scans available for review by study radiologists NA, not available; For the three patients without a preoperative CT scan for review, obtained radiological reports indicated all patients had cavitary lesions with a maximum diameter between 2.1 and 3.5 centimeters

83

Table 4-5. Pathology characteristics of resected pulmonary tissue^

ID Necrosis PMNs Mononuclear

Cells

Fibrosis Vascularization AFB

Staining

Tissue

pH

1 3 1* 2 2 0 3 7.2

2 2 2* 3 1&2 1 2 5.5

3 3 0 3 1&2 1 3 7.2

4 2 2 3 2 1 1 5.5

5 3 0 3 2 1 2 5.5

6 1 1 3 2 1 0 5.5

7 3 1* 3 2 1 1 5.5

8 1 1 3 2 1 1 5.5

9 1 0 3 1 1 0 5.5

10 3 1 3 2 1 2 5.5

PMNs, polymorphonuclear cells; AFB, acid fast bacillus *Eosinophils present ^Grading system using 4x magnification is as follows for each variable: Necrosis: 0, not present; 1 (rare), scattered within a field; 2 (moderate), confluent within a field; 3 (severe), present in multiple confluent fields. PMNs: 0, not present; 1, scattered within a field; 2, present within fields Mononuclear: 1, small granuloma that fits in a field; 2, separate fields with granulomas; 3, mostly granulomatous inflammation Fibrosis: 1, interspersed with granuloma; 2, surrounding granuloma Vascularization: 0, not present; 1, present AFB staining: 0, not present; 1, rare; 2, scattered in a field; 3, many in a field

84

CHAPTER 5 COMPARISON OF MYCOBACTERIUM TUBERCULOSIS STRAIN H37RA VS H37RV

Background

Tuberculosis is a disease caused by Mycobacterium tuberculosis (Mtb) and still a

leading cause of death in countries with low gross domestic product per capita [93].

There are two widely used Mtb laboratory reference strains, of which both were derived

from the Mtb H37 parent strain. H37 was isolated in 1905 from the sputum of a

tuberculosis patient. In 1935 William Steenken managed to obtain two differing strains

based on morphology and virulence by performing a dissociation study on glycerol egg

media of different pH. The study resulted in the emergence of H37Rv (v for virulent) and

H37Ra (a for avirulent) [94,95]. However, it should be noted that Mtb H37Ra is regarded

as an attenuated strain rather than being completely avirulent because considerable

bacterial growth has been observed in macrophages in vitro [96]. There are several

more differences between the two strains; for example Mtb H37Rv has a smooth colony

morphology while Mtb H37Ra is rough [97]. The attenuated strain also shows a

decreased survival rate inside macrophages and under anoxic conditions [98,99].

Zheng et al. conducted a full comparative genomic analysis and found 272 genetic

variations (insertions, deletions, single nucleotide variations) between the two strains

[100]. A recent study from Jena et al. identified 172 proteins with mutations in Mtb

H37Ra relative to Mtb H37Rv; 89 integral membrane proteins and 74 cytoplasmic

proteins have amino acid variations [101].

We conducted a large-scale literature research to examine the range of minimum

inhibitory concentrations (MICs) for the four most common antibiotics (rifampicin (RIF),

isoniazid (INH), ethambutol (EMB) and pyrazinamide (PZA)) against these two Mtb

85

strains. Table 5-1 showed the results of the search which included an explanation of the

method used. Our literature search indicates that there are significantly less

experiments in which MIC values for Mtb H37Ra were determined than those for Mtb

H37Rv. Over the years researchers have developed numerous methods to determine

reliable and reproducible MIC values. The most commonly used method appears to be

the radiometric method (BACTEC).

The MIC values in Table 5-1 were not collected from a consistent and

standardized experimental procedure, as these values vary depending on the chosen

method. EMB MIC results are inconsistent ranging from 0.06 to 4 µg/ml against Mtb

H37Rv and from 0.62 to 3.05 µg/ml against Mtb H37Ra. We found that EMB

susceptibility evaluation procedures were also quite variable between Mtb strains

compared to other anti-TB drugs. The first-line anti-TB drug PZA shows strong pH

dependency in its potency which resulted in incompatibility between experiments

conducted with different pH values of the culture media [102]. Consequently, there are

not many reported PZA MIC values against Mtb strains compared to EMB. The analysis

shows more consistencies for INH and RIF across studies. The BACTEC results for INH

against Mtb H37Rv from different papers are virtually identical, whereas the MIC results

using other susceptibility testing methods against Mtb H37Ra strain were not markedly

different. The reported RIF MIC values using various methodologies do not exhibit large

variability.

Differences between Mtb H37Rv and Mtb H37Ra are due to the genetic and

proteomic differences [100,101]. Differences in membrane proteins and in particular

differences in carrier proteins may have an impact on the influx and efflux of antibiotics.

86

Even small mutations of target proteins for the antibiotics are also highly likely to have a

large impact on the MIC value. In context of this literature review, the reader should

refer to the analysis of six Mtb H37Rv strains from different labs surveyed by Ioerger et

al [97]. They demonstrated that genetic differences among those strains evolved

through an “in vitro evolution” [97]. So it should be noted that there might be differences

even between the reference strain H37Rv from different laboratories depending on how

often the isolate has been re-cultured in the laboratory.

Our literature analysis showed a lack of reliable data especially for Mtb H37Ra

and a large discrepancy between MIC values reported in the literature even though

similar methods have been used. In addition, the question of whether Mtb H37Ra can

be used as a reliable surrogate for Mtb H37Rv could not be answered sufficiently.

Consequently, we generated susceptibility data (MIC values) of anti-TB drugs against of

both Mtb strains. The current study examined 16 different anti-TB agents.

By comparing the MICs of the most important antibiotics against both strains under the

same experimental conditions [103,104], the objective of this study is to determine

whether the less virulent strain is comparable to the virulent strain in terms of their

response to various antimicrobial agents. There are important advantages of working

with the attenuated Mtb H37Ra strain. Foremost, Biosafety Level II is sufficient when

working with the attenuated strain, which makes the experiments more cost-efficient to

run. The information is particularly relevant for high TB burden countries (e.g. sub-

Saharan African countries) such that these experiments can also be conducted by

organizations in countries that do not have access to Biosafety Level III facilities. It

87

should be noted that there are also major genomic differences which may also manifest

in phenotypic differences between Mtb H37Rv and actual clinical isolates.

Materials and Methods

Preparation of Drug Susceptibility Plates

Drug susceptibility plates were prepared as described by Heifets and Sanchez

[103,104] in the following doubling concentrations [µg/ml]: bedaquiline 0.002-0.5,

capreomycin 0.5-8, clofazimine 0.064-0.25, cycloserine 6.25-400, ethambutol 0.5-8,

ethionamide 0.25-4, isoniazid 0.125-0.5, kanamycin 1-16, levofloxacin 0.5-2, linezolid

0.125-2, moxifloxacin 0.25-1, p-aminosalicylic acid 0.125-2, pyrazinamide 18.75-75,

rifabutin 0.004-0.064, rifampicin 0.016-0.5 and streptomycin 0.5-8. Concentration

ranges were chosen based on reported MIC values against the two Mtb strains,

evaluated on solid agar medium. Capreomycin, clofazimine, cycloserine, ethambutol,

ethionamide, isoniazid, kanamycin, levofloxacin, p-aminosalicylic acid, pyrazinamide

and rifampicin were purchased from Sigma Aldrich, St. Louis, MO, US. Bedaquiline was

from Advanced ChemBlocks Inc, Burlingame, CA, US; moxifloxacin from Thermo Fisher

Scientific, Waltham, MA, US, and linezolid and rifabutin were from Sequoia Research

Products Ltd, Pangbourne, United Kingdom. Culture medium (Middlebrook 7H11

[Sigma Aldrich] with monopotassium phosphate [Thermo Fisher Scientific], glycerol

[Sigma Aldrich] and bovine calf serum [Sigma Aldrich] supplement) was identical for

both Mtb strains and prepared at the same time with the same batch of medium. 7H11

agar base, monopotassium phosphate and glycerol were dissolved in distilled water by

stirring with a magnetic bar on a magnetic stir plate. After autoclaving at 121°C for 15

minutes the pH was measured using a pH-meter. Agar was cooled down to 54°C in a

water bath and sterile bovine calf serum was added to a final concentration of 10% v/v.

88

The 100 x 15 mm petri dishes [Parter Medical Products Inc, Carson, CA, US] were

divided into 4 separate quadrants (Figure 5-1). Cooled medium was poured into

quadrant 1 of each plate as a non-drug control, approximately 5 mL per quadrant. For

quadrants 2, 3 and 4, sterile filtered drug solutions diluted from a stock were spiked into

liquid TB agar and stirred on a magnetic stirring hot plate. The solutions were then

poured into quadrants. Stock solutions were prepared for bedaquiline in acetonitrile,

clofazimine and rifabutin in dimethyl sulfoxide, ethionamide in ethylene glycol and H2O,

linezolid in ethanol, moxifloxacin and rifampicin in methanol, and the remaining drugs in

deionized water.

Bacterial Culture

Cultures of M. tuberculosis were grown from a frozen stock of ATCC 25618 and

25177 strains in a Mycobacteria Growth Indicator Tube (MGIT) prepared per package

insert and incubated in a BD MGIT machine at 37oC until the machine called it positive

plus 2 days, which is equivalent to ~106 CFU/mL (confirmed by plating studies). Both

strains were grown in Middlebrook 7H9 [Sigma Aldrich] with 10% OADC (Oleic Albumin

Dextrose Catalase) [Sigma Aldrich] supplement and 0.05% w/v Tween 80 [Sigma

Aldrich] and were at a similar stage of growth when inoculated onto the plates.

Inoculation of Drug Susceptibility Plates

Tubes containing bacterial cultures were vortexed for 20 seconds and diluted to

final concentrations of 103 CFU/mL and 104 CFU/mL (inoculum concentrations were

confirmed via CFU count on agar plates). 0.1 mL of these concentrations were

inoculated on each quadrant of the previously prepared agar plates. The plates were

then sealed in CO2 permeable plastic bags with a heat sealer. The sealed plates were

inoculated at 37oC and monitored weekly for adequate growth of the control quadrant.

89

Minimum Inhibitory Concentration (MIC) Determination

After 25 days of incubation, plates were removed from the incubator and colonies

were counted to compare the control vs. the quadrants containing anti-TB agents. MIC

was defined as the lowest concentration that resulted in no visible bacterial growth.

Each drug concentration were tested in triplicates. The modal MIC value is reported in

this study.

Results

Growth Inhibition of Two Mtb Strains in the Presence of Anti-TB Agents

Eight antibiotic agents demonstrated similar growth inhibition for both the

attenuated (H37Ra) and the virulent strain (H37Rv). Among these agents are

capreomycin (8µg/mL), ethambutol (8µg/mL), isoniazid (0.5µg/mL), kanamycin

(4µg/mL), linezolid (0.5µg/mL), p-aminosalicylic acid (2µg/mL), and streptomycin

(4µg/mL). Interestingly, even pyrazinamide, being one of the first line drugs against Mtb

infections, showed identical MIC values against both Mtb strains (75µg/mL).

We also found slightly differing MIC values for several drugs. One would expect

that the MIC for bedaquiline, being one of the newer antituberculotic agents, should not

differ much against both H37Ra and H37Rv. Interestingly, we observed a minimum

inhibitory concentration of 0.064µg/mL against the attenuated strain and a roughly 2-fold

higher value for the virulent strain (0.125µg/mL). Also, the MIC of clofazimine against

H37Rv was higher than the MIC against H37Ra (0.25µg/mL). Similar observations were

made for ethionamide and rifabutin. Furthermore, the MIC of cycloserine was roughly

two fold higher against the virulent strain than for the attenuated strain (200µg/mL for

H37Ra vs. 400µg/mL for H37Rv). Lastly, we discovered a roughly 8-fold difference in

90

MIC of rifampicin against H37Rv as compared to H37Ra (0.5µg/mL vs 0.064µg/mL,

respectively).

The virulent strain seems to be more susceptible to the two commonly used

fluoroquinolones, levofloxacin and moxifloxacin (levofloxacin: 1µg/mL against H37Ra

vs. 0.5µg/mL against H37Rv; moxifloxacin: 0.5µg/mL against H37Ra vs. 0.25µg/mL

against H37Rv). All results are shown in Table 5-2. A bar graph of H37Ra and H37Rv

MIC values for all drugs is shown in Figure 5-2. The pH measured in Heifets-Sanchez‘

TB agar was 6.0-6.1.

H37Ra as a Good Surrogate for H37Rv

In summary, we observed equivalent MIC values against both strains for half of

the agents tested. Both fluoroquinolones showed a 2-fold higher MIC against H37Ra as

compared to H37Rv, whereas 4 drugs had 2-fold lower MIC values against H37Ra as

compared to H37Rv. However, 2-fold differences are considered within the errors of

determination and therefore not considered a significant difference.

With the exception of rifampicin (being one of the oldest anti-TB drugs) no

significant differences were observed between the two strains with respect to drug

susceptibility. Thus, overall H37Ra seems to be a good surrogate for H37Rv.

Comparison to Clinical Susceptibility Data – Both Laboratory Strains Predict Clinical Susceptibility Equally Well

Our results were compared to published susceptibility data of clinical isolates

listed in the database from The European Committee on Antimicrobial Susceptibility

Testing (EUCAST) [105] and to several other published results for those not being listed

in EUCAST. The goal was to identify the strain that better predicts clinical susceptibility

as it is the susceptibility of clinical isolates that truly matters at the end of the day.

91

For 8 out of 16 tested drugs (capreomycin, ethambutol, isoniazid, kanamycin,

linezolid, p-aminosalicylic acid, pyrazinamide, streptomycin), the MIC of anti-TB agents

against both strains are equally suitable inference of MICs of the same anti-TB drugs

against clinical isolates (Table 5-2). MIC values determined in H37Ra was a better

predictor for 3 out of 16 drugs (bedaquiline, cycloserine, ethionamide) while MIC against

H37Rv was a better predictor for 4 out of 16 drugs (levofloxacin, moxifloxacin,

rifampicin, rifabutin). No formal comparison was done for clofazimine.

Discussion

It should be noted that the MIC we found for PAS (2 µg/mL) should be taken with

caution. It does not match the generally accepted MIC of 1 µg/mL which is often stated

in the literature [104,106,107], although 2-fold differences are considered within the

errors of determination. Furthermore, PAS does not give 99% inhibition, which

contributes to the error of determination, thus a wider MIC range may be acceptable. In

our literature search, we found that the MIC does not only depend on the medium used,

but also on the formulation of PAS and the inoculum size [104]. Additionally, the method

of susceptibility determination plays an important role [108]. In our case, commercially

available pure PAS was added to quad plates. Counts were then taken visually with the

help of a digital counter pen.

The MIC values observed in this study tend to be higher when compared to

previously published work, in particular, when compared to data coming from BACTEC

experiments (2-10 fold higher) [109–111]. This observation supports the thesis that

different experimental systems yield (slightly) differing MIC data. Even with the same

methodology being used, there may still be an ‘inter-laboratory variability’ with respect

to the generated MIC data. There are obvious differences between the experimental

92

system at hand and the BACTEC system that uses liquid medium and a higher pH

compared to the acidified pH in Heifets-Sanchez’ TB agar. However, the primary

objective of this study was not to investigate the effect of different experimental systems

on the MIC data they produce, but to draw a comparison between H37Ra and H37Rv

under identical experimental conditions. Heifets-Sanchez TB agar plates were identified

as the experimental method of choice as they are easy to prepare, inexpensive and

yield highly reproducible results.

Our study has a number of limitations. There are more aspects to antimicrobial

pharmacodynamics, for instance, the kinetics of the drug effects. These could be

determined through lengthy time-kill experiments, which was beyond the scope of our

study. Further, the Heifets-Sanchez TB agar medium has a lower pH of 6.0-6.1 instead

of the usual for agar media, pH 6.8. This may explain, in part, an increased MIC as the

antibiotic activity of several antibiotics decreases with decreasing pH (with the exception

of PZA) [112–115]. The main reason for a lower efficacy (i.e., an increased MIC) at

acidified pH may be the dependence of cellular uptake on drug ionization state. Yet, the

choice of a lower pH is a reasonable one and even somewhat closer to actual in vivo

conditions as clinicians have recently reported a slightly acidified pH in infected lung

tissue of TB patients (median: 5.5, range 5.0-7.2) [3].

Although some consider H37Rv the preferred strain for in vitro experiments, our

work has shown that H37Ra results predict clinical susceptibility equally well as the

H37Rv results. Neither H37Ra nor H37Rv is a clinical strain, however, both strains have

been shown to be good in vitro predictors for clinical outcome. The current study

addresses one aspect of interchangeability of Ra and Rv strains as inference for

93

susceptibility evaluation of anti-TB agents against clinical isolates from tuberculosis

patients. The applicability of the Ra strain as inference can bring significant cost

efficiency to laboratories worldwide, given that the use of Ra does not require a

Biosafety Level III environment.

Conclusion

The H37Ra strain is equally useful as the H37Rv strain in its response to anti-TB

agents and is also inferential of the responses of clinical isolates of tuberculosis to these

agents. The H37Ra strain can be used to evaluate potency of anti-TB agents to Mtb

bacilli.

94

Table 5-1. Minimum inhibitory concentration (MIC) values of isoniazid, rifampicin, pyrazinamide and ethambutol against Mtb H37Rv and Mtb H37Ra from the literature.

INH = Isoniazid, RIF = Rifampin, PZA = Pyrazinamide, EMB = Ethambutol

fMABA = fluorometric microplate Alamar blue assay, AP = Agar proportion method, REMA = Resazurin microtitre plate

assay, BMM = broth microdilution method

* multiple tests performed/multiple results stated

MIC [µg/ml]

Strain Mtb H37Rv Mtb H37Ra

Method AP 7H10 agar

BACTEC fMABA AP 7H11 agar

Etest 7H9 pH5.8

24-well plate assay 7H10

REMA BMM AP 7H10 agar

BACTEC fMABA AP 7H11 agar

pH5.5

INH 0.125 [116]

0.031 [109] 0.03 [110] 0.03 [111]

0.05 [109]

0.125 [117]

0.016-0.06

[118]*

0.125-0.2

[119]*

0.05 [120]

0.025 [109]

0.05 [109]

RIF 0.25 [116]

0.16 [109] 0.08-2 [110]*

0.25 [111] 0.06 [121]

0.11 [109]

1.00 [117]

0.06-0.25

[118]*

0.05 [120]

0.006 [109]

0.005 [109]

PZA 25-200 [122]*

12.5 [123]

100 [124]

≤ 12.5 [124]

25-200 [122]*

32 [85]

EMB 2 [116] 1.17 [109] 2.5 [110] 1.0 [111]

1.64 [109]

4.00 [117]

0.06-0.25

[118]*

0.62 [120]

1.06 [109]

3.05 [109]

95

Table 5-2: MICs of the tested anti-tuberculous drugs in H37Ra, H37Rv and comparison to literature-reported MIC in clinical strains

Drug MIC [µg/mL] H37Ra

comparison MIC [µg/mL] H37Rv

Literature value(s) Clinical Strains

Bedaquiline 0.064 < 0.125 0.064, 0.002-1*

Capreomycin 8 = 8 2, 0.25-64*

Clofazimine 0.25 < >0.25 1 [125]

Cycloserine 200 < 400 8-32 [65]

Ethambutol 8 = 8 2.5-5 [126]

Ethionamide 1 < 2 0.3-1.25 [127]

Isoniazid 0.5 = 0.5 0.1-0.2 [116,128]

Kanamycin 4 = 4 2, 0.5-512*

Levofloxacin 1 > 0.5 0.125-0.5 [129]

Linezolid 0.5 = 0.5 0.25, 0.064-8*

Moxifloxacin 0.5 > 0.25 0.25, 0.032-8*

p-Aminosalicylic acid

2 = 2 1 [130]

Pyrazinamide 75 = 75 32, 16-512*

Rifabutin 0.016 < 0.032 0.032, 0.004-16*

Rifampicin 0.064 < 0.5 0.12-0.5 [104]

Streptomycin 4 = 4 0.5, 0.125-512*

*EUCAST data. The mode and observed range of an MIC distribution is shown in the table. MIC distributions were not always normally distributed [105]

96

Figure 5-1. Schematic of how quadrant plates were divided and sectioned (a) and pictures of blank plates (b) and agar plates after incubation (c) (d). Quadrant 1 contained a non-drug growth control, quadrant 2 contained the highest drug concentration, 2-fold higher than quadrant 3 (intermediate drug conc.) and 4-fold higher than quadrant 4 (lower drug conc.). MIC was defined as the lowest concentration that resulted in no visible bacterial growth. With visible growth on all quadrants the MIC was higher than the drug concentration in quadrant 2; with no visible growth on quadrants 2-4 the MIC was less than or equal to the concentration in quadrant 4.

(b)

(a) (c) (d)

97

Figure 5-2. Side-by-side comparison of H37Ra and H37Rv MIC values on a logarithmic scale (y-axis) for 16 anti-tuberculosis drugs (x-axis)

98

CHAPTER 6 LINKING PHARMACOKINETICS TO PHARMACODYNAMICS

Introduction

Tuberculosis (TB) is the leading infectious disease killer globally, resulting in 1.8

million deaths a year.[4] A third of the world population is infected with TB today.[5]

Global emergence of multidrug-resistant (MDR) TB (resistant to at least isoniazid and

rifampicin) makes the TB epidemic an even greater problem as treatment outcomes

among such patients are substantially lower than those for drug susceptible TB.[4,5]

The World Health Organization (WHO) reports approximately half a million new cases of

MDR TB per year.[5] These patients require prolonged therapy with second line drugs

that are costly, less effective and often highly toxic, while successful treatment outcome

can be expected in only about 50% of MDR TB patients.[4] Extensively drug resistant

(XDR) TB is defined as resistance to isoniazid, rifampicin, and at least one

fluoroquinolone and injectable agent. Treatment failure is experienced in at least two

thirds of XDR TB patients.[4] There is an urgent need for new anti-TB drugs and an

optimization of current TB treatment.

Moxifloxacin and linezolid are key second-line and third line agents, respectively,

that are valuable options for the treatment of MDR TB. Given the limited amount of

potent drug candidates against drug resistant TB, it is crucial to find a dose, at which

these drugs not only show high efficacy but also can suppress the development of

further drug resistance. Toxicity presents a limiting factor; moxifloxacin can cause QT

interval prolongation and linezolid is known to cause neurotoxicity and

thrombocytopenia in some patients. In order to find the right dose and to not allow the

development of bacterial resistance to these potent drugs, a better understanding of the

99

relationship between target site pharmacokinetics (PK) and pharmacodynamics (PD) is

needed. There also is a lack of clarity on whether linezolid exhibits time-dependent or

concentration-dependent effect, and whether it is bacteriostatic or bactericidal. While

some consider linezolid a time-dependent antibacterial agent, especially against S.

aureus,[131] it was shown that linezolid killed M. tuberculosis in an exposure-dependent

manner,[132] with toxicity being driven by trough concentrations.[133]

The pH measured in TB diseased lung tissue of patients with progressive drug

resistant TB and severe lung lesions is approximately 5.5 (median, range 5.0-7.2).[3] It

is known that pH has a significant influence on the activity of many antibiotics including

moxifloxacin;[112–114] it also affects mycobacterial growth.[123]

Using the hollow fiber infection model, we investigated the interplay of lung tissue

pH as measured in patients with drug resistant TB,[3] clinical target site drug

exposure,[2] and pharmacodynamic response. By making use of mechanism-based

mathematical models and simulations, we determined the dose required to kill the bacilli

during both log-phase growth and slow growth in an acidic environment (‘acidic phase’)

while suppressing resistance emergence.

Methods

Antimicrobial Agents

Moxifloxacin hydrochloride powder (potency 91.7%, LOT: M280) was purchased

from Matrix Scientific (Columbia, SC, USA). The drug was dissolved in sterile water to a

stock solution of 2 mg/mL. Sterile infusion bags of linezolid (ZYVOX®, 600 mg/300 mL,

LOT: 15B06U94) were purchased from Pfizer (Morrisville, NC, USA). Stock solutions

were serially diluted to the desired concentrations with Middlebrook 7H9 broth (Becton

Dickinson).

100

Microorganism

Mycobacterium tuberculosis strain H37Ra (ATCC 25177) was purchased from

American Type Culture Collection (Manassas, VA, USA) and stored at -80°C. Bacterial

stocks were incubated in 7H9 broth with OADC supplement at 37°C with shaking

conditions for 4 days to achieve exponential growth phase.

Susceptibility Studies and Mutation Frequencies

The minimum inhibitory concentration (MIC) at neutral pH was performed as

described by CLSI.[134] At acidified pH, MIC was determined as described by Heifets

and Sanchez.[103] MIC was defined as the lowest drug concentration that allowed less

than 1% growth compared to drug-free controls. Mutation frequencies were determined

by plating approximately 5 x 106 CFU/mL (200 µL) of mycobacteria on Middlebrook

7H10 agar plates with and without drug supplementation at 3 times the MIC. Fifteen

plates for each drug were incubated for 25 days at 37°C in a humidified incubator with

5% CO2 atmosphere. A total bacterial population of approximately 1.5 x 107 CFU was

evaluated for each drug.

Hollow Fiber Infection Model

The concept of the system has been previously described.[135,43] Briefly,

mycobacteria in the extra-capillary space of a hollow fiber cartridge (peripheral

compartment) were exposed to dynamically changing drug concentrations over time.

Clinically relevant doses and corresponding concentration-time profiles as they had

been observed in TB patients were simulated in the hollow fiber infection model system

(based on maximum concentration [Cmax], time to Cmax [tmax], and an elimination half-life

[t1/2]) (Table 6-1).[72,136] With the use of computer-programmed peristaltic pumps, drug

solution was infused over 2 hours directly into the central compartment, mimicking a tmax

101

of 2 hours as observed in patients taking oral doses of moxifloxacin and linezolid. A

pump maintained a constant circulation of fluid between central and peripheral

compartment and thereby allowed drugs to quickly distribute throughout the entire

system. The peripheral compartment was separated from the central compartment by

semipermeable hollow fibers that cannot be crossed by bacteria. These membranes,

however, do allow for free diffusion of drug, nutrients and bacterial metabolites based

on a concentration gradient. More computer-programmed peristaltic pumps allowed for

a gradual dilution of the drug concentration in the system by infusing drug-free fresh

7H9 medium into and isovolumetrically withdrawing drug-containing medium from the

central compartment, similar to a first-order elimination process.

Experimental Setup

Mycobacterium tuberculosis was grown to log-phase growth and bacterial density

was determined via optical density (OD) measurement at a wavelength of 600 nm

(calibration curve bacterial density [CFU/mL] versus log(OD): y = 0.9253x + 8.3411, R2

= 0.9796). 10 mL of the bacterial suspension (1 x 106 CFU/mL, total inoculum: 107 CFU)

was then inoculated into the peripheral compartment of 14 hollow fiber cartridges that

had been preconditioned with 7H9 medium for 3 days at 37°C. The bacteria were

allowed to adapt to the hollow fiber system environment for another 3 days, to make

sure exponential-growth phase is present when the first dose was administered at day

0.

The first two arms were left untreated (A and B); the pH of the 7H9 medium for

one growth control (B) was acidified with citric acid (Sigma Aldrich) to a final pH of 5.8.

According to experiments conducted by Gumbo et al., a pH of 5.8 still allows for

bacterial net growth, although at rates lower than those of bacilli in log-phase growth at

102

pH 6.8; no net growth can be expected at a pH as low as 5.5.[123] Arms C, D and E

were treated with moxifloxacin daily doses of 400, 600 and 800 mg (Table 6-1). To

evaluate the drug effect under conditions similar to the ones observed in TB lung

lesions of patients with progressive disease, the same moxifloxacin doses were tested

under acidified pH and a previously reported lesion penetration coefficient was taken

into account, in that doses were multiplied by this coefficient (arms F, G, H).[2]

For linezolid, dosing regimens of 600 mg q24h, q12h and q8h were simulated

under both neutral (arms I, J, K) and acidified pH (arms L, M, N) conditions.

Humanized half-lives with respect to drug exposure were simulated; 7 hours for

moxifloxacin,[136] and 3 hours for linezolid.[72] Unbound or free drug concentration-

time profiles were simulated in the in vitro system accounting for 50% and 31% protein

binding for moxifloxacin and linezolid, respectively (Table 6-1).[33,137]

Pharmacokinetic Validation

Serial samples from the central compartment of each infection model were drawn

at 2, 4, 7.8, 23.8, 26, 28, 31.8, 47.8, 50, 71.8, 599.8 and 602 hours after the start of the

first 2-hours infusion. Moxifloxacin and linezolid concentrations in these samples were

measured using validated bioassay methods as described below. A one-compartment

PK model with zero-order input and first-order elimination was fitted to the data (see

Equation 1 below). PK measures are shown in Table 6-2.

Bioassay

The collected PK samples were stored in a -80°C freezer until quantification at

the University of Florida (UF) Infectious Disease Pharmacokinetics Laboratory (IDPL).

Drug concentrations were measured using validated LC-MS-MS assays on a DIONEX

UltiMate 3000 RS pump and a DIONEX UltiMate 3000 RS autosampler (Thermo

103

Scientific), column compartment and diode array detector, a TSQ Endura LC-MS-MS

system, a Dell Dimension computer and a Xcalibur 2.2 SP1.48 analytical software

(Thermo Scientific). The lower limit of quantification was 0.2 μg/mL for moxifloxacin and

0.3 μg/mL for linezolid. The moxifloxacin and linezolid recoveries from 7H9 broth were

99.89% and 100%, respectively. The overall inter-batch precision for quality control

samples ranged from 0.72 to 5.64% for moxifloxacin, and from 1.34 to 3.57% for

linezolid.

Microbiologic Response

The mycobacteria containing hollow fiber cartridge of each infection model was

sampled at baseline (day 0) and on days 1, 2, 3, 7, 15, 18, 22, 25, and 28 just before

the next scheduled drug dose. 10-fold serial dilutions (100 - 10-4 for treatment arms, and

10-1 - 10-5 for growth controls) were plated onto drug-free 7H10 agar plates and

incubated as described above. In order to detect and quantify a less susceptible

subpopulation, 100 - 10-2 dilutions of each study arm were also plated onto 7H10 agar

plates containing drug at 3 times the MIC. To evaluate the microbiologic response to

different drug exposures, time-kill curves were obtained by plotting the change in total

bacterial density (CFU/mL) over time.

Pharmacokinetic-Pharmacodynamic Modeling

Nonparametric adaptive grid program (Big NPAG)[138] was used to

simultaneously analyze measured drug concentrations, total bacterial population counts

and counts of a less susceptible subpopulation of all drug regimens. Several PK-PD

models were fit to the data. Parameter estimates were calculated by maximal a

posteriori probability (MAP) Bayesian techniques. The equations of the final

mathematical model (Eq. 6-1- Eq. 6-6) are shown below:[43]

104

dX1/dt = R0 - (CL/Vc) • X1 (6-1)

dNS/dt = Kgmax-S • NS • E - Kkmax-S • MS • NS - Knat-S • NS (6-2)

dNR/dt = Kgmax-R • NR • E - Kkmax-R • MR • NR - Knat-R • NR (6-3)

E = 1 - (NR + NS)/POPMAX (6-4)

MS = (X1/Vc)H-S/[(X1/Vc)H-S + EC50-SH-S] (6-5)

MR = (X1/Vc)H-R/[(X1/Vc)H-R + EC50-RH-R] (6-6)

where dX1/dt represents the change in drug amount in the central compartment

over time, R0 represents the infusion rate, CL and Vc the clearance and volume of the

central compartment. Ns and Nr represent the bacterial density of a susceptible and a

less susceptible subpopulation. Kgmax and Kkmax are the maximum growth and kill rates.

Knat, a the naturally occurring death rate constant, was included to describe slow

bacterial growth under acidified pH. POPMAX in the logistic growth term E is the

maximum bacterial density based on the growth control. H is the Hill coefficient (slope

factor) and EC50 is the drug concentration that produces half maximum bacterial kill.

Simulations and Probability of Target Attainment (PTA)

Simulations were run using the mathematical modeling software package

Berkeley Madonna version 8.3.23 (University of California, Berkeley, CA, USA). Final

PK-PD model parameter estimates were used to simulate microbiological outcome for

varying drug exposures. We identified the exact drug exposure (relative to MIC)

required to achieve a specific pharmacodynamic target. The objectives for both

moxifloxacin and linezolid treatment were resistance suppression during log-phase

growth while maximizing antimicrobial kill of the susceptible bacterial subpopulation,

and a 1.0 log10 kill relative to baseline in the acidic milieu. Monte Carlo simulations were

performed to evaluate how many patients of a virtual clinical trial would achieve the drug

105

exposure breakpoints related with the defined targets at different doses. The simulated

clinical trials consisted 1,000 virtual patient concentration-time profiles per dosing

regimen based on literature values for clearance, volume of distribution and absorption

rate constants (7.7 L/h, 76.4 L and 0.529 h-1 for moxifloxacin and 6.0 L/h, 47.0 L and

0.583 h-1 for linezolid),[136,139] and accounted for inter-patient variability in these PK

parameters (30% CV). We calculated the probability of target attainment for each dose

and at each clinically relevant MIC.[105]

Results

Microbiology

At neutral pH the MIC was 0.25 µg/mL for moxifloxacin and 0.5 µg/mL for

linezolid. The MIC at acidified pH was 0.5 µg/mL for both drugs. The mutation frequency

(MF) for moxifloxacin was 2.02 x 10-7; MF for linezolid was <6.73 x 10-8.

Time-Kill Curves

Time-kill curves for moxifloxacin and linezolid are shown in Figures 6-1 and 6-2.

While the growth control at neutral pH (green and red open circles, solid line) grew by

approximately 2 log10 CFU/mL, there was a reduction in bacterial count in the control

arm in acidified pH (blue and purple open circles, dashed line).

Moxifloxacin: A clear dose-response was observed for the different moxifloxacin

doses at neutral pH (green solid lines). A dose of 800 mg q24h caused a rapid kill while

a completely resistant bacterial population grew back at the lowest dose of 400 mg

q24h. 600 mg q24h did not sterilize the system. Under acidified pH, moxifloxacin’s

activity was significantly decreased (blue dashed lines). Bacteria did not regrow likely

due to the unfavorable pH conditions.

106

Linezolid: In the least frequent dosage regimen (600mg q24h) and at neutral

pH, linezolid showed bacteriostatic activity (red triangles, solid line). Two doses a day

eradicated the bacteria within 25 days – an additional third dose per day did not

increase the efficacy indicating the drug’s effect had achieved a maximum level at 1200

mg a day. An acidified pH did not seem to affect linezolid’s activity; reduction in log10

CFU/mL compared to control appeared to be similar for study arms under neutral and

acidified pH. A dose of 600 mg once-daily did not eradicate the bacteria. No significant

difference in bacterial response was observed between two and three daily doses of

600 mg.

PK-PD Modeling and Simulation

Free drug exposures including free peak and trough levels for each treated

hollow fiber study arm are shown in Table 6-2. Final PK-PD model parameter estimates

and model diagnostics are shown in Tables 6-3 and 6-4. No resistance emergence was

observed in the acidic phase, therefore, all model parameters related to a resistant

subpopulation were fixed to 0 in this particular scenario. The moxifloxacin concentration

that produced 50% of the maximum killing effect in the sensitive bacterial subpopulation

(EC50k-s) was significantly higher at acidified pH (1.71 mg/L +/- 0.19) compared to

neutral pH (0.54 mg/L +/- 0.14), indicating that there is a considerable loss of activity

against slowly replicating TB bacilli in the acidic phase. A slight but non-significant

increase in linezolid’s EC50k-s was observed in acidified medium as compared to

neutral pH. The 24-hour free moxifloxacin AUC at steady-state (fAUC24hr,ss) required to

suppress resistance and maximize antimicrobial killing during log-phase growth was

24.03 mg*h/L. This resulted in a fAUC24hr,ss/MIC ratio of 96.12 (MIC of M. tuberculosis

strain H37Ra was 0.25 mg/L at neutral pH). At acidified pH the fAUC24hr,ss/MIC ratio

107

needed to achieve 1.0 log10 CFU/mL kill relative to baseline after one month of

treatment was 132.88. Linezolid fAUC24hr,ss/MIC ratios of 71.12 and 88.80 (neutral and

acidic pH, respectively) were needed to achieve the same targets, i.e., resistance

suppression during log-phase growth and a 1.0 log10 CFU/mL kill relative to baseline in

the acidic phase.

In simulated clinical trials, the probability of target attainment (PTA) during

bacterial exponential growth phase was 60.4% for patients taking the currently

approved moxifloxacin dose of 400 mg QD, versus 95.4% at 600 mg and 99.4% at 800

mg (at an MIC of 0.25 mg/L that represented the mode of a clinical MIC distribution).

MIC distributions were reported by the European Committee on Antimicrobial

Susceptibility Testing (EUCAST).[105] At MIC of 0.5 mg/L which is relatively close to the

susceptibility breakpoint of 1.5 mg/L, resistance suppression occurred in only 1.8% at

400 mg versus 22.4% at 600 mg and 58.7% at 800 mg. In the acidic phase, 600 mg and

800 mg once daily performed equally well up to an MIC of 0.5 mg/L; 98.5% versus

99.9% PTA (Figure 6-3).

Another clinical trial was simulated with four linezolid study arms (300, 600, 900

and 1200 mg QD) consisting of 1,000 virtual patients each. For log-phase growth, no

marked differences were observed between the dosing arms at the modal value of the

MIC distribution (MIC: 0.25 mg/L, PTA: 98.4% at 300 mg and 100.0% at 600 mg and

above). 600 mg QD performed well up until an MIC of 0.5 mg/L (98.4% PTA). Clear

differences in outcome between various doses were observed for clinical isolates

wherein linezolid MIC against these isolates are as high as 1.0 mg/L: 0.5% at 300 mg,

108

46% at 600 mg, 90.4% at 900 mg and 98.6% at 1200 mg QD. Similar results were seen

in the acidic phase (Figure 6-4).

Discussion

We studied the activity of moxifloxacin and linezolid against M. tuberculosis in

different physiologic conditions, in exponential phase growth under neutral pH and

acidic phase where slowly growing bacilli are found, and determined the doses that

achieved maximum bacterial kill while suppressing the emergence of drug resistance.

The hollow fiber infection model (HFIM) system of TB is a nonclinical drug development

tool (DDT) with predictive accuracy for clinical and microbiological outcomes,[140]

advanced by the Critical Path to TB Drug Regimens (CPTR) Initiative, and has been

endorsed by leading global regulatory authorities.[141] Through Monte Carlo

simulations the quantitative output of our in vitro study could be bridged to the human

patient population to inform optimal dosage regimens.

Our results indicate that a moxifloxacin dose of 600-800 mg per day would have

sufficient efficacy against M. tuberculosis in an acidified environment, under the

condition that the drug accumulates in TB lung lesions as shown by Heinrichs et al.[2]

To kill M. tuberculosis in log-phase growth and to prevent the emergence of drug

resistance, a daily dose of 800 mg is likely required. These findings are in agreement

with previously published work by Gumbo et al. who recommended a daily dose of 600-

800 mg.[43] Further evaluation of tolerability of such a high dose is needed. Serious

side effects of moxifloxacin include severe diarrhea, tendonitis that can lead to tendon

rupture, joint problems, and a less arrhythmogenic prolongation of the QTc interval.[142]

Higher doses of 600 and 800 mg a day are currently being investigated in a large phase

III trial, “the evaluation of a standard treatment regimen of anti-tuberculosis drugs for

109

patients with MDR-TB (STREAM)”, ClinicalTrials.gov Identifier: NCT02409290.

Although the trial’s estimated primary completion date is April 2021, rates of serious

adverse drug effects have been low so far for moxifloxacin.

For isolates with the most frequently observed linezolid MIC of 0.25 mg/L, a

linezolid dose of 300 mg QD is predicted to have high target attainment rates during

both log-phase growth and in the acidic phase. For less susceptible isolates, however,

900–1200 mg once a day would be needed to suppress resistance and maximize

antimicrobial kill. At these high doses, however, there will be some trade-off in terms of

adverse drug events, in particular at a dose of 1200 mg QD. Linezolid can cause a

decrease in platelet count within the first few weeks of treatment. Peripheral neuropathy

and bone marrow suppression are serious adverse effects that were observed in some

patients during long-term use of linezolid. Toxicity is therefore a limiting factor for

linezolid use in MDR-TB patients who are usually treated for multiple months. A

compromise may therefore be an initial daily dose of 900 mg allowing for dose

reductions to be made when exposure-related side effects are observed. Brown et al.

showed that linezolid toxicity is driven by trough levels.[133] As a consequence, we

strongly recommend to administer the entire daily dose all at once instead of dividing it

into multiple daily doses (e.g. 600 mg QD versus 300 mg BID), since this would result in

increased trough levels and thereby in a higher risk of toxicity. Since resistance

suppression is also achieved through combination therapy, a daily dose of 600 mg of

linezolid might be sufficient if implemented in a robust drug regimen. This hypothesis

can be tested in clinical trials. Our results are in conformity with the outcome of another

linezolid hollow fiber study conducted by Brown et al. who showed that with linezolid

110

monotherapy, a dose higher than 600 mg is likely needed to prevent drug

resistance.[133]

Our findings also stress the need for improved and more cost-efficient TB

diagnostics. Usually, the only information available on a clinical isolate is whether or not

it is susceptible to a certain drug based on susceptibility breakpoints. Information on the

individual MIC of a patient’s isolate would be very useful as doses could be adjusted

accordingly. This, of course, would lead to a significant increase in TB treatment costs.

Our study is subject to certain limitations. The absence of an immune system in

the HFIM system may have led to an underestimation of microbial kill inside the human

body. On the other hand, the activity against non-replicating persistent bacilli was not

addressed, which may actually result in higher drug exposure breakpoints and therefore

requiring somewhat higher doses. For safety reasons, we used the attenuated M.

tuberculosis strain H37Ra in this study. Similarity to the virulent strain H37Rv with

respect to drug susceptibility and log-phase growth has been shown

previously.[109,143,144] Furthermore, in the clinic, resistance suppression can be

achieved through combination therapy, although there obviously is some room for

improvement considering the increasing numbers of drug-resistant cases. In our study,

we aimed to determine the dose that maximizes activity of moxifloxacin and linezolid.

This information is pivotal when designing and testing new combination therapy

regimens against MDR TB in clinical trials or in future in vitro experiments.

In summary, we have shown that moxifloxacin’s activity significantly decreased in

an acidified environment as measured inside severe lung lesions of MDR-TB

patients.[145] The loss in activity, however, is - to some extent - compensated by the

111

accumulation of the drug in TB lung lesions, therefore, moderate efficacy can be

expected. 800 mg/day is the dose that most likely leads to resistance suppression

during log-phase growth while exerting maximum bacterial kill.

Linezolid was shown to have very good activity against M. tuberculosis even at a

decreased pH. It is therefore a vital option for kill of bacilli in the acidic phase, in

particular, if the isolate is also resistant to pyrazinamide. 900 mg QD is very likely to

achieve a maximum killing effect and prevent the emergence of drug resistance. 600

mg QD in a robust drug regimen may have similar potential.

112

Figure 6-1. Time-kill plot moxifloxacin on a semi-logarithmic scale

113

Figure 6-2. Time-kill plot linezolid on a semi-logarithmic scale

114

Figure 6-3. Probability of target attainment for moxifloxacin doses in log-phase and

acidic phase growth, taking into account the accumulation of moxifloxacin in lung lesions. The targets for log-phase growth and acidic phase growth were, respectively, resistance suppression and 1.0 log10 kill relative to baseline. EUCAST MIC distribution included 1,467 observations.

115

Figure 6-4. Probability of target attainment for linezolid doses in log-phase and acidic

phase growth. The targets for log-phase growth and acidic phase growth were, respectively, resistance suppression and 1.0 log10 kill relative to baseline. EUCAST MIC distribution included 828 observations.

116

Table 6-1. Time-kill study design moxifloxacin and linezolid

Arm# Drug pH^ Simulated dosage regimen [mg]

Free fraction

Actual dose infused [mg]

Lesion/serum ratio*

C m

oxiflo

xa

cin

6.8 400 q24h 0.50 200 q24h

D 600 q24h 300 q24h

E 800 q24h 400 q24h

F 5.8 400 q24h 200 q24h 3.2

G 600 q24h 300 q24h 3.2

H 800 q24h 400 q24h 3.2

I

line

zo

lid

6.8 600 q24h 0.69 414 q24h

J 600 q12h 414 q12h

K 600 q8h 414 q8h

L 5.8 600 q24h 414 q24h

M 600 q12h 414 q12h

N 600 q8h 414 q8h

# arms A and B were untreated growth controls at neutral and at acidified pH

^ acidified pH was measured inside severe lung lesions of MDR-TB patients[145]

* accounting for moxifloxacin accumulation in lung lesions (penetration coefficient: 3.2)[2]

117

Table 6-2. Pharmacokinetic parameters moxifloxacin and linezolid

Arm^ Dose [mg]

fCmaxSS#

[mg/L] fAUC24hr,SS

# [mg*h/L]

fCminSS#

[mg/L]

C 400 1.35 12.87 0.21

D 600 2.03 19.07 0.17

E 800 2.60 26.81 0.31

F 400* 4.02 41.77 0.50

G 600* 6.46 65.18 0.73

H 800* 8.99 91.43 1.04

I 600 q24h 8.57 33.69 0.003

J 600 q12h 8.74 81.76 0.62

K 600 q8h 9.88 123.63 1.85

L 600 q24h 8.91 41.05 0.02

M 600 q12h 8.10 87.33 0.99

N 600 q8h 10.27 127.87 1.89

^ moxifloxacin was administered in arms C-H, linezolid was administered in arms I-N; arms A and B were untreated growth controls

# f: free (protein-unbound), SS: at steady state *due to the accumulation of moxifloxacin in TB lesions,[2] doses in arms F, G and H resulted in higher peak & trough concentrations and drug exposures compared to the respective doses in arms C, D and E

118

Table 6-3. Final parameter estimates PK-PD model

*population medians are reported for moxifloxacin acidic phase growth model, while population means are reported for the remaining three models

Moxifloxacin log-phase growth

Moxifloxacin acidic phase growth*

Linezolid log-phase growth

Linezolid acidic phase growth

Parameter Estimate SD Estimate SD Estimate SD Estimate SD

Vc [L] 140.879 8.784 145.541 10.841 29.834 10.761 31.171 12.604

CL [L/hr] 15.378 0.294 14.604 0.482 9.297 2.788 9.414 0.636

Kgmax-s [log10 CFU/mL*h-1] 0.290 0.162 0.405 0.088 0.367 0.258 0.346 0.147

Kkmax-s [log10 CFU/mL*h-1] 0.897 0.003 0.561 0.684 2.644 2.166 0.249 0.166

EC50k-s [mg/L] 0.542 0.136 1.709 0.193 4.130 3.127 5.738 2.987

Hk-s 7.909 6.555 2.943 3.281 12.519 5.087 11.025 5.500

Knat-s [log10 CFU/mL*h-1] 0 FIX - 0.353 0.057 0 FIX - 0.323 0.179

Kgmax-r [log10 CFU/mL*h-1] 0.017 0.018 0 FIX - 0.125 0.171 0 FIX -

Kkmax-r [log10 CFU/mL*h-1] 1.335 0.118 0 FIX - 1.939 0.493 0 FIX -

EC50k-r [mg/L] 3.907 2.283 0 FIX - 6.842 2.498 0 FIX -

Hk-r 15.025 4.096 0 FIX - 11.400 5.834 0 FIX -

Knat-r [log10 CFU/mL*h-1] 0 FIX - 0 FIX - 0 FIX - 0 FIX -

POPMAX [log10 CFU/mL] 7.432 7.625 6.001 0.666 7.879 7.604 8.674 8.638

Total population [log10 CFU/mL] 4.780 2.398 4.544 0.100 4.628 3.636 4.455 3.757

Resistant population [CFU/mL] 0.907 0.789 0 FIX - 1.851 1.272 0 FIX -

119

Table 6-4. Model diagnostics: regression line characteristics of plots of predicted versus observed values for moxifloxacin and linezolid concentrations, the resultant change in the total bacterial population, and the changes in the resistant subpopulation, as well as bias and precision measures

Drug Growth DV a b R^2 p-value MWE BAMWSE

Moxifloxacin Log-

phase Concentrations 0.05 0.97 0.967 <<0.001 -0.126 0.466 Total bact. Pop. 0.00 0.99 0.967 <<0.001 0.152 1.606 Resist. Subpop. -1.50 1.58 0.982 <0.005 -0.076 0.367

Acidic

phase Concentrations

0.07 0.98 0.987 <<0.001 -0.039 0.179 Total bact. Pop.

1.14 0.68 0.870 <<0.001 -0.257 11.973 Linezolid Log-

phase Concentrations 0.15 1.00 0.976 <<0.001 -0.440 1.103 Total bact. Pop. 0.00 1.01 0.983 <<0.001 -0.192 0.727 Resist. Subpop. -0.69 1.36 0.798 0.053 0.051 0.512

Acidic

phase Concentrations 0.08 1.01 0.973 <<0.001 -0.238 1.129 Total bact. Pop. 0.00 1.00 0.949 <<0.001 0.002 0.876

DV, dependent variable; a, intercept of the best least squares line YOBS = a + b * YPRED; b, slope of the regression line; MWE, mean weighted error (PRED - OBS); BAMWSE, bias-adjusted mean weighted squared error

120

CHAPTER 7 SUMMARY

TB has emerged as the number one infectious disease killer (with an estimated

1.8 million deaths per year), and the global emergence of MDR and XDR TB is an

enormous public health threat and major barrier to effective TB control. There is an

urgent need to optimize current TB treatment and suppress further development of

resistance.

One promising area of research aimed at optimizing available treatments is the

study of the pharmacokinetics of anti-TB drugs, and in particular the concentrations of

drugs at the site of disease in pulmonary TB. The ability of a TB drug to penetrate into

the lung and TB lesions, the main site of action, is a vital piece of information when

designing effective drug regimens.

A better understanding of the clinical pharmacokinetics of new drug regimens will

help ensure optimal and responsible use of new drug combinations. We used an

innovative technique of microdialysis to measure protein-unbound extracellular

concentrations of pyrazinamide, moxifloxacin and linezolid in TB diseased lung tissue.

Pyrazinamide is a first line drug with sterilizing activity, moxifloxacin a

cornerstone drug in the treatment of MDR TB, and linezolid a newly-introduced drug for

the treatment of MDR- and XDR TB.

Pharmacokinetic modeling was performed to determine typical PK parameter

values and identify predictors of optimal drug concentrations. Although not statistically

significant, we observed a trend towards lower free drug concentrations in larger TB

lesions (lesion diameter and fibrous wall thickness). Based on clinical PK observations

121

and PK-PD modeling, the current doses need to be increased. For linezolid we propose

an initial dosage regimen of 900 mg once-daily, which may be reduced when exposure

related side effects are observed. Similar, we propose a daily dose of 600-800 mg of

moxifloxacin. For pyrazinamide, a dose of at least 35 mg/kg should ensure optimal

target site exposure.

122

LIST OF REFERENCES

[1] Deitchman AN, Heinrichs MT, Khaowroongrueng V, Jadhav SB, Derendorf H. Utility of Microdialysis in Infectious Disease Drug Development and Dose Optimization. AAPS J 2017;19(2):334-342.

[2] Heinrichs MT, Vashakidze S, Nikolaishvili K, Sabulua I, Tukvadze N, Bablishvili N,

Gogishvili S, Little B, Bernheim A, Guarner J, Peloquin C, Blumberg H, Derendorf H, Kempker RR. Moxifloxacin Target Site Concentrations in Patients with Pulmonary Tuberculosis Utilizing Microdialysis: A Clinical Pharmacokinetic Study (OUP accepted manuscript). J Antimicrob Chemother 2017.

[3] Kempker RR, Heinrichs MT, Nikolaishvili K, Sabulua I, Bablishvili N, Gogishvili S,

et al. Lung Tissue Concentrations of Pyrazinamide among Patients with Drug-Resistant Pulmonary Tuberculosis. Antimicrob Agents Chemother 2017;61(6): e00226-17.

[4] World Health Organization. Prioritization of pathogens to guide discovery,

research and development of new antibiotics for drug resistant bacterial infections, including tuberculosis. Geneva: World Health Organization (WHO/EMP/IAU/2017.12); 2017.

[5] World Health Organization. Global tuberculosis report 2016. Geneva: World

Health Organization (WHO/HTM/TB/2016.13); 2016. [6] Curry International Tuberculosis Center. Drug-Resistant Tuberculosis: a Survival

Guide for Clinicians. 3rd Edition; 2016. [7] Chaurasia CS, Müller M, Bashaw ED, Benfeldt E, Bolinder J, Bullock R, et al.

AAPS-FDA workshop white paper: microdialysis principles, application and regulatory perspectives. Pharm Res 2007;24:1014–25.

[8] Mindermann T, Zimmerli W, Gratzl O. Rifampin concentrations in various

compartments of the human brain: a novel method for determining drug levels in the cerebral extracellular space. Antimicrob Agents Chemother 1998;42:2626–9.

[9] Kempker RR, Barth AB, Vashakidze S, Nikolaishvili K, Sabulua I, Tukvadze N, et

al. Cavitary penetration of levofloxacin among patients with multidrug-resistant tuberculosis. Antimicrob Agents Chemother 2015;59:3149–55.

[10] Traunmüller F, Schintler M V., Spendel S, Popovic M, Mauric O, Scharnagl E, et

al. Linezolid concentrations in infected soft tissue and bone following repetitive doses in diabetic patients with bacterial foot infections. Int J Antimicrob Agents 2010;36:84–6.

123

[11] Burkhardt O, Brunner M, Schmidt S, Grant M, Tang Y, Derendorf H. Penetration of ertapenem into skeletal muscle and subcutaneous adipose tissue in healthy volunteers measured by in vivo microdialysis. J Antimicrob Chemother 2006;58:632–6.

[12] Müller M. Monitoring tissue drug levels by clinical microdialysis. Altern Lab Anim

2009;37 Suppl 1:57–9. [13] Schmidt S, Banks R, Kumar V, Rand KH, Derendorf H. Clinical microdialysis in

skin and soft tissues: an update. J Clin Pharmacol 2008;48:351–64. [14] Schroepf S, Burau D, Muench HG, Derendorf H, Adam D, Kloft C. Microdialysis

for therapeutic drug monitoring in infants. Poster Abstract Presented at the 8th International Symposium on Microdialysis; 2016 May 25-27; Uppsala, Sweden.

[15] Deitchman AN, Derendorf H. Measuring drug distribution in the critically ill patient.

Adv Drug Deliv Rev 2014;77:22–6. [16] World Health Organization. A Global Action Framework for TB Research: In

Support of the Third Pillar of WHO’s END TB Strategy. Geneva: World Health Organization (WHO/HTM/TB/2015.26); 2015.

[17] Lienhardt C, Lönnroth K, Menzies D, Balasegaram M, Chakaya J, Cobelens F, et

al. Translational Research for Tuberculosis Elimination: Priorities, Challenges, and Actions. PLoS Med 2016;13:e1001965.

[18] Prideaux B, Via LE, Zimmerman MD, Eum S, Sarathy J, O’Brien P, Chen C, Kaya

F, Weiner DM, Chen PY, Song T, Lee M, Shim TS, Cho JS, Kim W, Cho SN, Olivier KN, Barry CE, Dartois V. The association between sterilizing activity and drug distribution into tuberculosis lesions. Nat Med 2015;21:1223–7.

[19] Bastos ML, Hussain H, Weyer K, Garcia-Garcia L, Leimane V, Leung CC, et al.

Treatment outcomes of patients with multidrug-resistant and extensively drug-resistant tuberculosis according to drug susceptibility testing to first- and second-line drugs: an individual patient data meta-analysis. Clin Infect Dis 2014;59:1364–74.

[20] Pletz MWR, De Roux A, Roth A, Neumann K-H, Mauch H, Lode H. Early

bactericidal activity of moxifloxacin in treatment of pulmonary tuberculosis: a prospective, randomized study. Antimicrob Agents Chemother 2004;48:780–2.

[21] Lakshminarayana SB, Huat TB, Ho PC, Manjunatha UH, Dartois V, Dick T, Rao

S. Comprehensive physicochemical, pharmacokinetic and activity profiling of anti-TB agents. J Antimicrob Chemother 2015;70:857–67.

124

[22] Vaddady PK, Lee RE, Meibohm B. In vitro pharmacokinetic/pharmacodynamic models in anti-infective drug development: focus on TB. Future Med Chem 2010;2:1355–69.

[23] Drusano G. Antimicrobial pharmacodynamics: critical interactions of “bug and

drug.” Nat Rev Microbiol 2004;2:289–300. [24] Scaglione F. Pharmacokinetic/pharmacodynamic (PK/PD) considerations in the

management of Gram-positive bacteraemia. Int J Antimicrob Agents 2010;36 Suppl 2:S33-9.

[25] Kempker RR, Kipiani M, Mirtskhulava V, Tukvadze N, Magee MJ, Blumberg HM.

Acquired Drug Resistance in Mycobacterium tuberculosis and Poor Outcomes among Patients with Multidrug-Resistant Tuberculosis. Emerg Infect Dis 2015;21:992–1001.

[26] Deitchman AN, Heinrichs MT, Khaowroongrueng V, Jadhav SB, Derendorf H.

Utility of Microdialysis in Infectious Disease Drug Development and Dose Optimization. AAPS J 2017;19:334–42.

[27] Azeredo FJ, Dalla Costa T, Derendorf H. Role of microdialysis in

pharmacokinetics and pharmacodynamics: current status and future directions. Clin Pharmacokinet 2014;53:205–12.

[28] Stass, H; Dalhoff, A; Kubitza, D; Schühly U. Pharmacokinetics, safety, and

tolerability of ascending single doses of moxifloxacin, a new 8-methoxy quinolone, administered to healthy subjects. Antimicrob Agents Chemother 1998;42:2060–5.

[29] Ostergaard, C; Sørensen, TK; Knudsen, JD; Frimodt-Møller N. Evaluation of

moxifloxacin, a new 8-methoxyquinolone, for treatment of meningitis caused by a penicillin-resistant pneumococcus in rabbits. Antimicrob Agents Chemother 1998;42:1706–12.

[30] LaMorte WW. Mann Whitney U Test (Wilcoxon Rank Sum Test) 2017.

http://sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_nonparametric/BS704_Nonparametric4.html

[31] Alsultan A, Peloquin CA. Therapeutic drug monitoring in the treatment of

tuberculosis: an update. Drugs 2014;74:839–54. [32] Müller M, Stass H, Brunner M, Möller JG, Lackner E, Eichler HG. Penetration of

moxifloxacin into peripheral compartments in humans. Antimicrob Agents Chemother 1999;43:2345–9.

[33] U.S. Food and Drug Administration. NDA 21-085 Avelox Clinical Pharmacology

and Biopharmaceutics Review 1998.

125

[34] Lubasch A, Keller I, Borner K, Koeppe P, Lode H. Comparative pharmacokinetics

of ciprofloxacin, gatifloxacin, grepafloxacin, levofloxacin, trovafloxacin, and moxifloxacin after single oral administration in healthy volunteers. Antimicrob Agents Chemother 2000;44:2600–3.

[35] Peloquin CA, Hadad DJ, Molino LP, Palaci M, Boom WH, Dietze R, Johnson J.

Population pharmacokinetics of levofloxacin, gatifloxacin, and moxifloxacin in adults with pulmonary tuberculosis. Antimicrob Agents Chemother 2008;52:852–7.

[36] Nimmo WS, Peacock JE. Effect of anaesthesia and surgery on pharmacokinetics

and pharmacodynamics. Br Med Bull 1988;44:286–301. [37] Wood M. Pharmacokinetic drug interactions in anaesthetic practice. Clin

Pharmacokinet 1991;21:285–307. [38] Michot JM, Seral C, Van Bambeke F, Mingeot-Leclercq MP, Tulkens P. Influence

of efflux transporters on the accumulation and efflux of four quinolones (ciprofloxacin, levofloxacin, garenoxacin, and moxifloxacin) in J774 macrophages. Antimicrob Agents Chemother 2005;49:2429–37.

[39] Hutschala D, Skhirtladze K, Kinstner C, Mayer-Helm B, Müller M, Wolner E, et al.

In vivo microdialysis to measure antibiotic penetration into soft tissue during cardiac surgery. Ann Thorac Surg 2007;84:1605–10.

[40] de Lange ECM. Recovery and Calibration Techniques: Toward Quantitative

Microdialysis. In: Mueller M, editor. Microdialysis in Drug Development XII, Springer; 2013, p. 13–33.

[41] Grosset J. Mycobacterium tuberculosis in the extracellular compartment: an

underestimated adversary. Antimicrob Agents Chemother 2003;47:833–6. [42] Breilh D, Jougon J, Djabarouti S, Gordien JB, Xuereb F, Velly JF, et al. Diffusion

of oral and intravenous 400 mg once-daily moxifloxacin into lung tissue at pharmacokinetic steady-state. J Chemother 2003;15:558–62.

[43] Gumbo T, Louie A, Deziel MR, Parsons LM, Salfinger M, Drusano GL. Selection

of a moxifloxacin dose that suppresses drug resistance in Mycobacterium tuberculosis, by use of an in vitro pharmacodynamic infection model and mathematical modeling. J Infect Dis 2004;190:1642–51.

[44] National Kidney Foundation. Cockcroft-Gault Formula 2017.

https://www.kidney.org/professionals/KDOQI/gfr_calculatorCoc

126

[45] Lauzardo M, Peloquin CA. Tuberculosis therapy for 2016 and beyond. Expert Opin Pharmacother 2016;17:1859–72.

[46] Kipiani M, Mirtskhulava V, Tukvadze N, Magee M, Blumberg HM, Kempker RR.

Significant clinical impact of a rapid molecular diagnostic test (Genotype MTBDRplus assay) to detect multidrug-resistant tuberculosis. Clin Infect Dis 2014;59:1559–66.

[47] Lienhardt C, Kraigsley AM, Sizemore CF. Driving the Way to Tuberculosis

Elimination: The Essential Role of Fundamental Research. Clin Infect Dis 2016;63:370–5.

[48] Shin SS, Keshavjee S, Gelmanova IY, Atwood S, Franke MF, Mishustin SP, et al.

Development of extensively drug-resistant tuberculosis during multidrug-resistant tuberculosis treatment. Am J Respir Crit Care Med 2010;182:426–32.

[49] Hamilton CD, Stout JE, Goodman PC, Mosher A, Menzies R, Schluger NW, et al.

The value of end-of-treatment chest radiograph in predicting pulmonary tuberculosis relapse. Int J Tuberc Lung Dis 2008;12:1059–64.

[50] Cornett DS, Reyzer ML, Chaurand P, Caprioli RM. MALDI imaging mass

spectrometry: molecular snapshots of biochemical systems. Nat Methods 2007;4:828–33.

[51] World Health Organization. Companion handbook to the WHO guidelines for the

programmatic management of drug-resistant tuberculosis (WHO/HTM/TB/2014.11). Geneva: World Health Organization; 2014.

[52] Vashakidze S, Gogishvili S, Nikolaishvili K, Dzidzikashvili N, Tukvadze N,

Blumberg HM, et al. Favorable outcomes for multidrug and extensively drug resistant tuberculosis patients undergoing surgery. Ann Thorac Surg 2013;95:1892–8.

[53] Parsons LM, Somoskövi A, Gutierrez C, Lee E, Paramasivan CN, Abimiku A, et

al. Laboratory diagnosis of tuberculosis in resource-poor countries: challenges and opportunities. Clin Microbiol Rev 2011;24:314–50.

[54] Tukvadze N, Kempker RR, Kalandadze I, Kurbatova E, Leonard MK,

Apsindzelashvili R, et al. Use of a molecular diagnostic test in AFB smear positive tuberculosis suspects greatly reduces time to detection of multidrug resistant tuberculosis. PLoS One 2012;7:e31563.

[55] Stalker DJ, Jungbluth GL. Clinical pharmacokinetics of linezolid, a novel

oxazolidinone antibacterial. Clin Pharmacokinet 2003;42:1129–40.

127

[56] Cynamon MH, Klemens SP, Sharpe CA, Chase S. Activities of several novel oxazolidinones against Mycobacterium tuberculosis in a murine model. Antimicrob Agents Chemother 1999;43:1189–91.

[57] Zurenko GE, Yagi BH, Schaadt RD, Allison JW, Kilburn JO, Glickman SE, et al. In

vitro activities of U-100592 and U-100766, novel oxazolidinone antibacterial agents. Antimicrob Agents Chemother 1996;40:839–45.

[58] Lee M, Lee J, Carroll MW, Choi H, Min S, Song T, et al. Linezolid for treatment of

chronic extensively drug-resistant tuberculosis. N Engl J Med 2012;367:1508–18. [59] Zhang X, Falagas ME, Vardakas KZ, Wang R, Qin R, Wang J, et al. Systematic

review and meta-analysis of the efficacy and safety of therapy with linezolid containing regimens in the treatment of multidrug-resistant and extensively drug-resistant tuberculosis. J Thorac Dis 2015;7:603–15.

[60] Gee T, Ellis R, Marshall G, Andrews J, Ashby J, Wise R. Pharmacokinetics and

tissue penetration of linezolid following multiple oral doses. Antimicrob Agents Chemother 2001;45:1843–6.

[61] Dehghanyar P, Bürger C, Zeitlinger M, Islinger F, Kovar F, Müller M, et al.

Penetration of linezolid into soft tissues of healthy volunteers after single and multiple doses. Antimicrob Agents Chemother 2005;49:2367–71.

[62] Zhang M, Sala C, Dhar N, Vocat A, Sambandamurthy VK, Sharma S, et al. In

vitro and in vivo activities of three oxazolidinones against nonreplicating Mycobacterium tuberculosis. Antimicrob Agents Chemother 2014;58:3217–23.

[63] Zhao W, Guo Z, Zheng M, Zhang J, Wang B, Li P, et al. Activity of linezolid-

containing regimens against multidrug-resistant tuberculosis in mice. Int J Antimicrob Agents 2014;43:148–53.

[64] Wasserman S, Meintjes G, Maartens G. Linezolid in the treatment of drug-

resistant tuberculosis: the challenge of its narrow therapeutic index. Expert Rev Anti Infect Ther 2016;14:901–15.

[65] Schön T, Juréen P, Chryssanthou E, Giske CG, Sturegård E, Kahlmeter G, et al.

Wild-type distributions of seven oral second-line drugs against Mycobacterium tuberculosis. Int J Tuberc Lung Dis 2011;15:502–9.

[66] Rodríguez JC, Cebrián L, López M, Ruiz M, Jiménez I, Royo G. Mutant

prevention concentration: comparison of fluoroquinolones and linezolid with Mycobacterium tuberculosis. J Antimicrob Chemother 2004;53:441–4.

128

[67] Kempker RR, Rabin AS, Nikolaishvili K, Kalandadze I, Gogishvili S, Blumberg HM, et al. Additional drug resistance in Mycobacterium tuberculosis isolates from resected cavities among patients with multidrug-resistant or extensively drug-resistant pulmonary tuberculosis. Clin Infect Dis 2012;54:e51-4.

[68] Akkerman OW, van Altena R, Klinkenberg T, Brouwers AH, Bongaerts AHH, van

der Werf TS, et al. Drug concentration in lung tissue in multidrug-resistant tuberculosis. Eur Respir J 2013;42:1750–2.

[69] Conte JE, Golden JA, Kipps J, Zurlinden E. Intrapulmonary pharmacokinetics of

linezolid. Antimicrob Agents Chemother 2002;46:1475–80. [70] Honeybourne D, Tobin C, Jevons G, Andrews J, Wise R. Intrapulmonary

penetration of linezolid. J Antimicrob Chemother 2003;51:1431–4. [71] Boselli E, Breilh D, Rimmelé T, Djabarouti S, Toutain J, Chassard D, et al.

Pharmacokinetics and intrapulmonary concentrations of linezolid administered to critically ill patients with ventilator-associated pneumonia. Crit Care Med 2005;33:1529–33.

[72] McGee B, Dietze R, Hadad DJ, Molino LPD, Maciel ELN, Boom WH, et al.

Population pharmacokinetics of linezolid in adults with pulmonary tuberculosis. Antimicrob Agents Chemother 2009;53:3981–4.

[73] World Health Organization. The End TB Strategy: Global strategy and targets for

tuberculosis prevention, care and control after 2015 n.d. [74] Kim H-R, Hwang SS, Kim HJ, Lee SM, Yoo C-G, Kim YW, et al. Impact of

extensive drug resistance on treatment outcomes in non-HIV-infected patients with multidrug-resistant tuberculosis. Clin Infect Dis 2007;45:1290–5.

[75] Azeredo FJ, Dalla Costa T, Derendorf H. Role of microdialysis in

pharmacokinetics and pharmacodynamics: current status and future directions. Clin Pharmacokinet 2014;53:205–12.

[76] Kjellsson MC, Via LE, Goh A, Weiner D, Low KM, Kern S, et al. Pharmacokinetic

evaluation of the penetration of antituberculosis agents in rabbit pulmonary lesions. Antimicrob Agents Chemother 2012;56:446–57.

[77] Lanoix J-P, Lenaerts AJ, Nuermberger EL. Heterogeneous disease progression

and treatment response in a C3HeB/FeJ mouse model of tuberculosis. Dis Model Mech 2015;8:603–10.

129

[78] Lanoix J-P, Ioerger T, Ormond A, Kaya F, Sacchettini J, Dartois V, et al. Selective Inactivity of Pyrazinamide against Tuberculosis in C3HeB/FeJ Mice Is Best Explained by Neutral pH of Caseum. Antimicrob Agents Chemother 2016;60:735–43.

[79] Zhang Y, Shi W, Zhang W, Mitchison D. Mechanisms of Pyrazinamide Action and

Resistance. Microbiol Spectr 2014;2:MGM2-0023-2013. [80] World Health Organization. Companion handbook to the WHO guidelines for the

programmatic management of drug-resistant tuberculosis (WHO/HTM/TB/2014.11); 2014.

[81] Partners In Health. Adjuvant Therapies and Strategies. PIH Guide to the Medical

Management of Multidrug-Resistant Tuberculosis, Boston, MA: Partners in Health; 2003, p. 29–32.

[82] Feuerriegel S, Schleusener V, Beckert P, Kohl TA, Miotto P, Cirillo DM, et al.

PhyResSE: a Web Tool Delineating Mycobacterium tuberculosis Antibiotic Resistance and Lineage from Whole-Genome Sequencing Data. J Clin Microbiol 2015;53:1908–14.

[83] Prideaux B, Via LE, Zimmerman MD, Eum S, Sarathy J, O’Brien P, et al. The

association between sterilizing activity and drug distribution into tuberculosis lesions. Nat Med 2015;21:1223–7.

[84] Weiser OL, Howard OP. Assay of Streptomycin in Resected Lung Tissue. In:

Transactions of the 12th Conference on the Chemotherapy of Tuberculosis 1955 n.d.:198–201.

[85] Zhang Y, Permar S, Sun Z. Conditions that may affect the results of susceptibility

testing of Mycobacterium tuberculosis to pyrazinamide. J Med Microbiol 2002;51:42–9.

[86] Donald PR, Maritz JS, Diacon AH. Pyrazinamide pharmacokinetics and efficacy in

adults and children. Tuberculosis (Edinb) 2012;92:1–8. [87] Savic R, Peloquin CA, Boeree M, Weiner M, Heinrich N, Bliven-Sizemore E, et al.

The relationship between pyrazinamide pharmacokinetics (PK) and microbiologic outcomes in patients with pulmonary TB receiving standard- or high-dose rifampicin: PK/PD results from TBTC trials 27 and 28 and PanACEA MAMS. 9th International Workshop on Clinical Pharmacology of Tuberculosis Drugs, Liverpool, United Kingdom, 2016 October 24-26.

[88] Ellard GA. Absorption, metabolism and excretion of pyrazinamide in man.

Tubercle 1969;50:144–58.

130

[89] Zhu M, Starke JR, Burman WJ, Steiner P, Stambaugh JJ, Ashkin D, et al. Population pharmacokinetic modeling of pyrazinamide in children and adults with tuberculosis. Pharmacotherapy 2002;22:686–95.

[90] Kaplan G, Post FA, Moreira AL, Wainwright H, Kreiswirth BN, Tanverdi M, et al.

Mycobacterium tuberculosis growth at the cavity surface: a microenvironment with failed immunity. Infect Immun 2003;71:7099–108.

[91] Chengalroyen MD, Beukes GM, Gordhan BG, Streicher EM, Churchyard G,

Hafner R, et al. Detection and Quantification of Differentially Culturable Tubercle Bacteria in Sputum from Patients with Tuberculosis. Am J Respir Crit Care Med 2016;194:1532–40.

[92] Woo J, Cheung W, Chan R, Chan HS, Cheng A, Chan K. In vitro protein binding

characteristics of isoniazid, rifampicin, and pyrazinamide to whole plasma, albumin, and alpha-1-acid glycoprotein. Clin Biochem 1996;29:175–7.

[93] World Health Organization. The top 10 causes of death 2014. Geneva: World

Health Organization; 2014. [94] Steenken W. Lysis of Tubercle Bacilli in Vitro. Exp Biol Med 1935;33:253–5. [95] Steenken W, Gardner LU. History of H37 strain of tubercle bacillus. Am Rev

Tuberc 1946;54:62–6. [96] Hart PD, Armstrong JA. Strain virulence and the lysosomal response in

macrophages infected with Mycobacterium tuberculosis. Infect Immun 1974;10:742–6.

[97] Ioerger TR, Feng Y, Ganesula K, Chen X, Dobos KM, Fortune S, et al. Variation

among genome sequences of H37Rv strains of Mycobacterium tuberculosis from multiple laboratories. J Bacteriol 2010;192:3645–53.

[98] Heplar JQ, Clifton CE, Raffel S, Futrelle CM. Virulence of the tubercle bacillus. I.

Effect of oxygen tension upon respiration of virulent and avirulent bacilli. J Infect Dis n.d.;94:90–8.

[99] Li AH, Waddell SJ, Hinds J, Malloff CA, Bains M, Hancock RE, et al. Contrasting

transcriptional responses of a virulent and an attenuated strain of Mycobacterium tuberculosis infecting macrophages. PLoS One 2010;5:e11066.

[100] Zheng H, Lu L, Wang B, Pu S, Zhang X, Zhu G, et al. Genetic basis of virulence

attenuation revealed by comparative genomic analysis of Mycobacterium tuberculosis strain H37Ra versus H37Rv. PLoS One 2008;3:e2375.

131

[101] Jena L, Kashikar S, Kumar S, Harinath BC. Comparative proteomic analysis of Mycobacterium tuberculosis strain H37Rv versus H37Ra. Int J Mycobacteriology 2013;2:220–6.

[102] Zhang Y, Mitchison D. The curious characteristics of pyrazinamide: a review. Int J

Tuberc Lung Dis 2003;7:6–21. [103] Heifets L, Sanchez T. New agar medium for testing susceptibility of

Mycobacterium tuberculosis to pyrazinamide. J Clin Microbiol 2000;38:1498–501. [104] Heifets LB. Antituberculosis drugs: antimicrobial activity in vitro. In: Drug

susceptibility and chemotherapy, mycobacterial infections. Boca Raton, FL: CRC Press; 1991, p. 13–58.

[105] European Committee on Antimicrobial Susceptibility Testing (EUCAST) database.

www.eucast.org [106] de Kock L, Sy SKB, Rosenkranz B, Diacon AH, Prescott K, Hernandez KR, et al.

Pharmacokinetics of para-aminosalicylic acid in HIV-uninfected and HIV-coinfected tuberculosis patients receiving antiretroviral therapy, managed for multidrug-resistant and extensively drug-resistant tuberculosis. Antimicrob Agents Chemother 2014;58:6242–50.

[107] Sy SKB, de Kock L, Diacon AH, Werely CJ, Xia H, Rosenkranz B, et al. N-

acetyltransferase genotypes and the pharmacokinetics and tolerability of para-aminosalicylic acid in patients with drug-resistant pulmonary tuberculosis. Antimicrob Agents Chemother 2015;59:4129–38.

[108] Saifullah B, Arulselvan P, El Zowalaty ME, Fakurazi S, Webster TJ, Geilich B, et

al. Development of a highly biocompatible antituberculosis nanodelivery formulation based on para-aminosalicylic acid-zinc layered hydroxide nanocomposites. ScientificWorldJournal; 2014:401460.

[109] Collins L, Franzblau SG. Microplate alamar blue assay versus BACTEC 460

system for high-throughput screening of compounds against Mycobacterium tuberculosis and Mycobacterium avium. Antimicrob Agents Chemother 1997;41:1004–9.

[110] Chakravorty S, Aladegbami B, Motiwala AS, Dai Y, Safi H, Brimacombe M, et al.

Rifampin resistance, Beijing-W clade-single nucleotide polymorphism cluster group 2 phylogeny, and the Rv2629 191-C allele in Mycobacterium tuberculosis strains. J Clin Microbiol 2008;46:2555–60.

[111] Chung GA, Aktar Z, Jackson S, Duncan K. High-throughput screen for detecting

antimycobacterial agents. Antimicrob Agents Chemother 1995;39:2235–8.

132

[112] Burian A, Erdogan Z, Jandrisits C, Zeitlinger M. Impact of pH on activity of trimethoprim, fosfomycin, amikacin, colistin and ertapenem in human urine. Pharmacology 2012;90:281–7.

[113] Lemaire S, Tulkens PM, Van Bambeke F. Contrasting effects of acidic pH on the

extracellular and intracellular activities of the anti-gram-positive fluoroquinolones moxifloxacin and delafloxacin against Staphylococcus aureus. Antimicrob Agents Chemother 2011;55:649–58.

[114] Irwin NJ, McCoy CP, Carson L. Effect of pH on the in vitro susceptibility of

planktonic and biofilm-grown Proteus mirabilis to the quinolone antimicrobials. J Appl Microbiol 2013;115:382–9.

[115] Giacobbe RA, Huband MD, DeJonge BLM, Bradford PA. Effect of Susceptibility

Testing Conditions on the In Vitro Antibacterial Activity of ETX0914. Diagn Microbiol Infect Dis 2017;87:139–42.

[116] Schön T, Juréen P, Giske CG, Chryssanthou E, Sturegård E, Werngren J, et al.

Evaluation of wild-type MIC distributions as a tool for determination of clinical breakpoints for Mycobacterium tuberculosis. J Antimicrob Chemother 2009;64:786–93.

[117] Coban AY. Blood agar validation for susceptibility testing of isoniazid, rifampicin,

ethambutol, and streptomycin to Mycobacterium tuberculosis isolates. PLoS One 2013;8:e55370.

[118] Wanger A, Mills K. Testing of Mycobacterium tuberculosis susceptibility to

ethambutol, isoniazid, rifampin, and streptomycin by using Etest. J Clin Microbiol 1996;34:1672–6.

[119] Wedajo W, Schön T, Bedru A, Kiros T, Hailu E, Mebrahtu T, et al. A 24-well plate

assay for simultaneous testing of first and second line drugs against Mycobacterium tuberculosis in a high endemic setting. BMC Res Notes 2014;7:512.

[120] Norden MA, Kurzynski TA, Bownds SE, Callister SM, Schell RF. Rapid

susceptibility testing of Mycobacterium tuberculosis (H37Ra) by flow cytometry. J Clin Microbiol 1995;33:1231–7.

[121] Heifets L, Sanchez T, Vanderkolk J, Pham V. Development of rifapentine

susceptibility tests for Mycobacterium tuberculosis. Antimicrob Agents Chemother 1999;43:25–8.

[122] Woodley CL, Smithwick RW. Radiometric method for pyrazinamide susceptibility

testing of Mycobacterium tuberculosis in egg-yolk-enriched BACTEC 12A medium. Antimicrob Agents Chemother 1988;32:125–7.

133

[123] Gumbo T, Dona CSWS, Meek C, Leff R. Pharmacokinetics-pharmacodynamics of pyrazinamide in a novel in vitro model of tuberculosis for sterilizing effect: a paradigm for faster assessment of new antituberculosis drugs. Antimicrob Agents Chemother 2009;53:3197–204.

[124] Campanerut PAZ, Ghiraldi LD, Spositto FLE, Sato DN, Leite CQF, Hirata MH, et

al. Rapid detection of resistance to pyrazinamide in Mycobacterium tuberculosis using the resazurin microtitre assay. J Antimicrob Chemother 2011;66:1044–6.

[125] Pfyffer GE, Bonato DA, Ebrahimzadeh A, Gross W, Hotaling J, Kornblum J, et al.

Multicenter laboratory validation of susceptibility testing of Mycobacterium tuberculosis against classical second-line and newer antimicrobial drugs by using the radiometric BACTEC 460 technique and the proportion method with solid media. J Clin Microbiol 1999;37:3179–86.

[126] Madison B, Robinson-Dunn B, George I, Gross W, Lipman H, Metchock B, et al.

Multicenter evaluation of ethambutol susceptibility testing of mycobacterium tuberculosis by agar proportion and radiometric methods. J Clin Microbiol 2002;40:3976–9.

[127] Heifets LB, Lindholm-Levy PJ, Flory M. Comparison of bacteriostatic and

bactericidal activity of isoniazid and ethionamide against Mycobacterium avium and Mycobacterium tuberculosis. Am Rev Respir Dis 1991;143:268–70.

[128] Suo J, Chang CE, Lin TP, Heifets LB. Minimal inhibitory concentrations of

isoniazid, rifampin, ethambutol, and streptomycin against Mycobacterium tuberculosis strains isolated before treatment of patients in Taiwan. Am Rev Respir Dis 1988;138:999–1001.

[129] Angeby KA, Jureen P, Giske CG, Chryssanthou E, Sturegård E, Nordvall M, et al.

Wild-type MIC distributions of four fluoroquinolones active against Mycobacterium tuberculosis in relation to current critical concentrations and available pharmacokinetic and pharmacodynamic data. J Antimicrob Chemother 2010;65:946–52.

[130] Chakraborty S, Gruber T, Barry CE, Boshoff HI, Rhee KY. Para-aminosalicylic

acid acts as an alternative substrate of folate metabolism in Mycobacterium tuberculosis. Science 2013;339:88–91.

[131] Estes KS, Derendorf H. Comparison of the pharmacokinetic properties of

vancomycin, linezolid, tigecyclin, and daptomycin. Eur J Med Res 2010;15:533. [132] Srivastava S, Magombedze G, Koeuth T, Sherman C, Pasipanodya JG, Raj P, et

al. Linezolid Dose That Maximizes Sterilizing Effect While Minimizing Toxicity and Resistance Emergence for Tuberculosis. Antimicrob Agents Chemother 2017;61.

134

[133] Brown AN, Drusano GL, Adams JR, Rodriquez JL, Jambunathan K, Baluya DL, et al. Preclinical Evaluations To Identify Optimal Linezolid Regimens for Tuberculosis Therapy. MBio 2015;6:e01741-15.

[134] NCCLS. Susceptibility testing of Mycobacteria, Nocardiae, and other aerobic

Actinomycetes: approved standard [NCCLS document M24- A.2003]. Wayne, PA: NCCLS, 2003.

[135] Bilello, J A; Bauer, G; Dudley, M N; Cole, G A; Drusano GL. Effect of 2’,3’-

didehydro-3’-deoxythymidine in an in vitro hollow-fiber pharmacodynamic model system correlates with results of dose-ranging clinical studies. Antimicrob Agents Chemother 1994;38:1386–91.

[136] Ito F, Ohno Y, Toyoshi S, Kaito D, Koumei Y, Endo J, et al. Pharmacokinetics of

consecutive oral moxifloxacin (400 mg/day) in patients with respiratory tract infection. Ther Adv Respir Dis 2016;10:34–42.

[137] Ford C, Hamel J, Stapert D, Moerman J, Hutchinson H, Barbachyn M, et al.

Oxazolidinones: a new class of antimicrobials. Infect Med 1999;16:435–45. [138] Leary, R; Jelliffe, R; Schumitzky, A; Van Guilder M. An adaptive grid non-

parametric approach to pharmacokinetic and dynamic (PK/PD) population models. Proc. 14th IEEE Symp. Comput. Based Med. Syst., Bethesda, MD: IEEE Computer Society: 2001, p. 389–94.

[139] Abe S, Chiba K, Cirincione B, Grasela TH, Ito K, Suwa T. Population

pharmacokinetic analysis of linezolid in patients with infectious disease: application to lower body weight and elderly patients. J Clin Pharmacol 2009;49:1071–8.

[140] Gumbo T, Pasipanodya JG, Nuermberger E, Romero K, Hanna D. Correlations

Between the Hollow Fiber Model of Tuberculosis and Therapeutic Events in Tuberculosis Patients: Learn and Confirm. Clin Infect Dis 2015;61 Suppl 1:S18-24.

[141] Romero K, Clay R, Hanna D. Strategic Regulatory Evaluation and Endorsement

of the Hollow Fiber Tuberculosis System as a Novel Drug Development Tool. Clin Infect Dis 2015;61 Suppl 1:S5-9.

[142] Inghammar M, Svanström H, Melbye M, Pasternak B, Hviid A. Oral

fluoroquinolone use and serious arrhythmia: bi-national cohort study. BMJ 2016;352:i843.

[143] Zhang M, Gong J, Lin Y, Barnes PF. Growth of virulent and avirulent

Mycobacterium tuberculosis strains in human macrophages. Infect Immun 1998;66:794–9.

135

[144] Heinrichs MT, May RJ, Heider F, Reimers T, Peloquin CA, Derendorf H.

Mycobacterium tuberculosis strain H37Ra is equivalent to H37Rv in estimating in vivo pharmacodynamics of anti-tuberculous drugs. 2nd International Caparica Conference in Antibiotic Resistance; Lisbon, Portugal, 2017 June 12-15.

[145] Kempker RR, Heinrichs MT, Nikolaishvili K, Sabulua I, Bablishvili N, Gogishvili S,

et al. Lung Tissue Concentrations of Pyrazinamide among Patients with Drug-Resistant Pulmonary Tuberculosis. Antimicrob Agents Chemother 2017;61.

136

BIOGRAPHICAL SKETCH

M. Tobias Heinrichs received his professional degree in pharmacy from the

University of Mainz, Germany, in 2012, and was honored with the award for the best

pharmacy graduate that year. A year later, he passed his board examination in the state

of Rhineland-Palatinate, Germany. Tobias worked at a community pharmacy and for

Boehringer Ingelheim in Biberach, Germany, before joining the PhD program at the

University of Florida in 2014. At Dr. Hartmut Derendorf’s laboratory, Tobias’ research

embraced the pharmacokinetic and pharmacodynamic evaluation and dose optimization

of moxifloxacin, linezolid and pyrazinamide in patients with multidrug resistant

tuberculosis using mechanism-based mathematical models and simulations.

At the U.S. Food and Drug Administration (Division of Pharmacometrics), Tobias

worked on a Critical Path project in 2016, with focus on disease progression and

exposure-response similarity between adults and pediatrics and extrapolation of adult

efficacy in pediatric patients with chemotherapy-induced nausea and vomiting (CINV)

and postoperative nausea and vomiting (PONV).

He received his Doctor of Philosophy in pharmaceutical sciences in December

2017.

Date post:	03-Mar-2021
Category:	Documents
Upload:	others
View:	2 times
Download:	0 times

© 2017 Marc Tobias Heinrichstarget site pharmacokinetics of moxifloxacin, linezolid and...

Documents