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Pharmacokinetics/Pharmacodynamics of Antibiotics: Refresher Part 1CHS Pharmacy Education Series

ProCE, Inc.www.ProCE.com 1

CHSPSC, LLC Antimicrobial Stewardship Education Series

March 8, 2017Pharmacokinetics/Pharmacodynamics of Antibiotics: Refresher Part 1

Featured Speaker:

Larry Danziger, Pharm.D.Professor of Pharmacy and MedicineUniversity of Illinois at Chicago

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Submission of an online post‐test and evaluation is the only way to obtain CE credit for this webinar

Go to www.ProCE.com/CHSRx Webinar attendees will also receive an email with a direct link to the

web page Print your CE statement of completion online

– Credit for live or enduring (not both)

Deadline: April 7, 2017 CPE Monitor (applicable to pharmacists)

– CE credit automatically uploaded to NABP/CPE Monitor upon completion of post‐test and evaluation (user must complete the “claim credit” step)

Online Evaluation, Self-Assessmentand CE Credit

Attendance Code

Code will be provided at the end of today’s activity



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2016 Pharmacy Education Series

5

It is the policy of ProCE, Inc. to ensure balance, independence, objectivity and scientific rigor in all of its continuing education activities. Faculty must disclose to participants the existence of any significant financial interest or any other relationship with the manufacturer of any commercial product(s) discussed in an educational presentation. Dr. Danziger has disclosed the following financial/commercial relationships: Speaker for Allergan, MedCo, and Merck.

Please note: The opinions expressed in this activity should not be construed as those of the CME/CE provider. The information and views are those of the faculty through clinical practice and knowledge of the professional literature. Portions of this activity may include unlabeled indications. Use of drugs and devices outside of labeling should be considered experimental and participants are advised to consult prescribing information and professional literature.

March 8, 2017Pharmacokinetics/Pharmacodynamics of Antibiotics: Refresher Part 1

Featured Speaker:

Larry Danziger, Pharm.D.Professor of Pharmacy and MedicineUniversity of Illinois at Chicago

CE Activity Information & Accreditation

ProCE, Inc. (Pharmacist CE)

– 1.0 contact hour

6

Funding:This activity is self‐funded through CHSPSC.



Antimicrobial Pharmacokinetics / Pharmacodynamics: Optimizing Therapeutic Outcomes

March 8, 2017

Larry H. Danziger, Pharm.DProfessor of Pharmacy and MedicineUniversity of Illinois at Chicago

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ObjectivesUpon completion of this presentation, the participant should be able to:

• Describe the pharmacodynamic (PD) properties of antimicrobials

• Identify strategies to maximize the PD properties in selecting and dosing antimicrobials

• Describe the factors to consider to safely prescribe Gentamicin and Vancomycin, to be able to monitor levels logically and interpret them

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DeSear: Previous Discussion

• Selecting an antimicrobial agent and dosing scheme is based on a complex set of considerations

– What is the best pharmacodynamic (PD) predictor of efficacy for the drug chosen?

• AUC/MIC

• T>MIC

• Cmax: MIC

– How does the MIC impact PD?

9

Background

• The rational use of antibacterial drugs should be based upon two principles

• First, the specific identity of the infecting organism must be determined

• Second, a test must be devised which will provide an accurate estimate that the antibiotic will be effective in vivo

Petersdorf and Plorde Annu. Rev. Med. 14:41-56; 1963

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Background

Science has made tremendous progress over the last 30 years:

– Established critical values for outcome parameters that predict clinical & microbiologic success

– Identified PK parameters linked to a biologic measure of action, the MIC

– Devised tests to determine antibiotic performance characterized as concentration dependent or independent

– Established pharmacodynamic outcome parameters

11

Background

• Minimum inhibitory concentration (MIC)

– The lowest concentration of drug that prevents visible bacterial growth after 24 hours of incubation in a specified growth medium

– Organism and antimicrobial specific

– Interpretation• Pharmacokinetics/Pharmacodynamics of the drug in humans

• Drug’s activity versus the organism

• Site of infection

• Drug resistance mechanisms

12



HOST

BUG

DRUG

Factors Influencing Clinical Outcome

13

Site of infection

Infecting pathogen

Resistance of infecting pathogen

Host - Protein binding

Host - Immune system

Drug class

Dosing regimen (dose & duration)

Treatment endpoint

Factors Influencing Clinical Outcome

14



Bug: How Do We Predict Antimicrobial Effect?

Parameter Definition Limitations

MIC(Minimum inhibitory

concentration)

Concentration at which a standard inoculum of 105

organisms are inhibited after 24-48 hours

• In vitro conditions differ from those at infection site

• Only reflects a specific time point

• In vitro drug concentrations remain constant

• Measured against standard inoculum

• Lacks information on:

- Rate of bactericidal activity

- Persistent effects

• In vitro tests may not adequately predict outcome

MBC(Minimum bactericidal

concentration)

Concentration at which a 99.9% reduction in the standard inoculum occurs

Levison ME. Infect Dis Clin North Am 2000;14:281-291. Craig WA. Clin Infect Dis 1998;26:1-12.

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• Site of Infection

• Site defines the most likely organisms

– Especially helpful in empiric antimicrobial selection

• Site also determines the dose and route of administration of antimicrobial

– Efficacy determined by adequate concentrations of antimicrobial at site of infection

– Serum concentrations vs tissue concentrations and relationship to MIC

Host and Drug Factors

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Optimizing Antimicrobial Therapy

[C] @Infection

Site

PathogenMIC

DRUGPharmacokinetics

Pharmacodynamic

Profile

BacteriaKilled

Host

17

Basic Pharmacokinetic Model

Drug at Absorption

Site

Drug in Body

Excreted Drug

Metabolite in Body

Eliminated Metabolite

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Basic Pharmacodynamics Model

Dosage regimen

Concentration vs. time in serum

Concentration vs. time at site of

infection

Concentration vs. time in tissue and other body fluids

Pharmacologic or toxic effect

Antimicrobial effect versus time

Pharmacokinetics Pharmacodynamics

Craig WA. Clin Infect Dis 1998;26:1-12.

Absorption

Distribution

Elimination

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C Min = Trough

AUC

C Max = Peak

Time

Concentration

Pharmacokinetic Definitions

20



PK / PD DefinitionsAUC = area under the serum concentration curve, measurement of drug absorbed and persistence

AUC24/MIC ratio = AUC over 24 hours divided by the MIC, predicts efficacy of concentration-dependent antibiotics

Cmax = peak plasma level, highest concentration of drug in the blood

Cmax/MIC ratio = Peak/MIC ratio, predicts efficacy of concentration-dependent antibiotics

21

PK / PD Definitions

Cmin = trough level

T>MIC = time above MIC, percentage of time over 24 hours that drug concentration exceeds the MIC

PAE = Post Antibiotic Effect, delayed regrowth of bacteria following exposure to an antibiotic

Varies according to drug-bug combination

22



Efficacy and PK /PD Relationships

• Pharmacokinetics (PK)– serum concentration profile

– penetration to site of infection

• Pharmacodynamics (PD)– susceptibility – MIC (potency)

– concentration- vs. time-dependent killing

– persistent (post-antibiotic) effects (PAE)

Jacobs. Clin Microbiol Infect 2001;7:589–96

23

Antimicrobial Pharmacodynamics

• Correlates the drug concentration and the clinical effect (ie, bacteria killed)

• Often use surrogate marker such as minimum inhibitory concentration (MIC)

• Index serum concentration (pharmacokinetic profile) to MIC

• The pharmacodynamic relationship is different for different antimicrobial classes

24



PK / PD RelationshipsMicrobiology

•Susceptibility Testing

•MIC

•Bactericidal Rate

Pharmacokinetics

•Peak/Trough concentration

•AUC

•Half-life

Pharmacodynamics

•AUC / MIC

•Peak / MIC

•Time > MIC

25

Important PD Parameters• Concentration dependent

– Cmax/MIC: Optimize dose to produce higher unbound drug concentrations

– AUC/MIC: Optimize the dose and exposure to unbound drug concentrations

– Concentration Dependent agents bacterial killing as the drug concentrations exceed the MIC

• Peak/MIC (AUC/MIC) ratio important

• Quinolones, aminoglycosides

Craig WA. Clin Infect Dis 2001;33(Suppl 3):S233-37.

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Concentration Dependent

Concentration

Time

Cmax = peak

MIC

Cmin = trough

Cmax/ MIC

AUC/ MIC

Aminoglycosides

Fluoroquinolones

Metronidazole

Daptomycin

Glycopeptides

Adapted from: Roberts JA, et al. Crit Care Med.2009;37:840-85127

Bacterial KillingTime-Kill Curves of P. aeruginosa

Conc.-Dependent

Lo

g1

0CF

U/

mL

Time (hours)

9

8

7

6

5

4

3

2

0 2 4 6 0 2 4 6 8

Control¼ MIC1 MIC

4 MIC

16 MIC64 MIC

Time-Dependent

Craig WA, et al. Scand J Infect Dis, 1991;Suppl (74)

Tobramycin Ticarcillin

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Relationship between AUC/MIC ratio for the nonprotein bound fraction of levofloxacin and ciprofloxacin

Scaglione F, et al. Antimicrob Agents Chemother. 2003 Sep;47(9):2749-55.

AUC/MIC and Survival Relationship for Quinolones

29

Important PD Parameters• Concentration independent

– T > MIC: Optimize duration of unbound drug concentration at or above the MIC

– Concentration Independent (Time-Dependent) agents kill bacteria when the drug concentrations exceed the MIC

• Time>MIC important

• Penicillins, cephalosporins, vancomycin

Craig WA. Clin Infect Dis 2001;33(Suppl 3):S233-37.

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Concentration Independent

Concentration

Time

Cmax = peak

MIC

Cmin = troughT > MIC

Beta-lactams

Clindamycin

Macrolides

Linezolid

Vancomycin


3 10 30 100 300 1000 3000

24 h AUC/MIC ratio

5

6

7

8

9

10

0 20 40 60 80 100

Time above MIC (%)

5

6

7

8

9

10R² = 94%

Peak MIC ratio

01 1 10 100 1000 10000

Log 1

0C

FU p

er lu

ng a

t 24

h

5

6

7

8

9

10

Craig. Diagn Microbiol Infect Dis 1996; 25:213–217

Relationship between Time above MIC and efficacyin animal infection models

Cefotaxime in K. pneumoniae

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0 20 40 60 80 100

0

20

40

60

80

100

Time above MIC (%)

Penicillins

Cephalosporins

Craig. Diagn Microbiol Infect Dis 1996; 25:213–217

Relationship between Time above MIC and efficacyin animal infection models

S. pneumoniae

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PD of Specific Antimicrobials

PD Parameter

Cmax/MIC AUC/MIC T > MIC

• Aminoglycosides

• Fluoroquinolones• Metronidazole

• Aminoglycosides

• Azithromycin

• Daptomycin

• Glycopeptides

• Ketolides

• Quinupristin/dalfopristin

• Beta-lactams

• Aztreonam

• Erythromycin

• Clarithromycin

• Linezolid

• Clindamycin

•Vancomycin

Rodvold KA. Pharmacotherapy 2001;21:319S-330S. Nicolau DP. J Infect Chemother 2003;9:292-296.

34



Pharmacodynamic Parameters for Prediction of Successful Outcomes

0

1

2

3

4

5

6

7

0 4 8 12 16 20 24

Time (h)

Co

nce

ntr

atio

n (

mg

/L) Peak/MIC 10x ( Gm - ) Aminoglycosides / Fluoroquinolones

AUC/MIC >125 ( Gm - ) or >30 ( Gm + ) Fluoroquinolones

Time > MIC>50% Cephalosporins / Macrolides

MIC

AUC/MIC >100 Daptomycin or >50 Colistin

35

Post Antibiotic Effect (PAE)

Concentration

Time

Cmax = peak

MICPAE

Cmin = trough

Persistent suppression of bacterial regrowth following brief exposure to an antimicrobial




Post Antibiotic Effect (PAE)• Gram-positive organisms

– Most antibiotics (beta-lactams) exhibit PAE ~1-2 hours

– Aminoglycosides exhibit PAE < 1 hour

– Prolonged for Fluoroquinolones

• Gram-negative organisms

– Most beta-lactams (except imipenem) have a negligible PAE

– Aminoglycosides and quinolones have PAE > 2-3 hours

– Prolonged for Fluoroquinolones

• Clinical significance unknown

– Helps choose appropriate dosing interval

Craig w, et al. The Post Antibiotic Effect. Ann Inter Med1987;106(6):900-902.

37

Clinical Applications

Using PK and PD

to predict

patient outcome

38



Relationship Between Cmax:MIC Ratio and Clinical Response

Aminoglycosides

55

6570

8389 92

0

10

20

30

40

50

60

70

80

90

100

2 4 6 8 10 12+

Cmax:MIC

Clinical response

(%)

Moore RD et al. J Infect Dis. 1987;155:93-99.

39

Relationship Between AUC / MIC and Clinical Response

Ciprofloxacin in Seriously Ill Patients

16Clinical100% -

50% -

75% -

25% -

% o

f Pat

ient

s C

ured

9

0 - 62.5 62.5 - 125 125 - 250

10

250 - 500

7

> 500

22Microbiologic

Forrest A., et al. Antimicrob Agents Chemother 1993;37:1073.40



Clinical Failure Rate 43% 11.5% 1%

Relationship Between AUC / MIC and Clinical Response

Levofloxacin

Jacobs. Clin Microbiol Infect 2001;7:589–96 ; [Adapted from Preston et al. JAMA 1998;279:125–9]

4 3

23

3

100

10

102030405060708090

100

No

. o

f p

atie

nts

AUC:MIC <25 Peak:MIC <3

AUC:MIC 25–100Peak:MIC 3–12

AUC:MIC >100 Peak:MIC >12

SuccessFailure

134 hospitalized patients with respiratory tract, skin or complicated urinary tract infections treated with 500 mg qd for 5–14 days

41

Limitation of Pharmacodynamics

Bacterial sample should be in the fluid where the bacteria is obtained: difficult if not impossible to obtain

Technology for measuring MIC’s has 100% variability (1-2 fold dilutions)

Antibiotic PD parameters, f-AUC/MIC & f-Peak/MIC incorporate MIC in the denominator

One tube dilution can double or half the value of your PD outcome predictor or change the amount of time where f-antibiotic concentration > MIC

42



Limitation of Pharmacodynamics

All methods of determining MIC are not equal

PD outcome parameter should specify MIC method

Remember: Bacteria differ in their susceptibility to antibiotics, even among same species

43

Limitations of Pharmacokinetics

Young healthy volunteers: worst case

Most PK studies done in males

Actual patients: clinically appropriate, usually not available

May or may not account for protein-binding

44



Other Considerations

45

Will the antibiotic get to the site of Infection?

Blood and tissue concentrations

• Ampicillin/piperacillin concentrations in bile

• Fluoroquinolones concentrations in bone

• Quinolones, TMP/SMX, cephalosporins, amoxicillin concentrations in prostate

46



Will the antibiotic get to the site of Infection?

Ability to cross blood-brain barrier

• Dependent on inflammation, lipophilicity, low mw, low protein binding, low degree of ionization

• 3rd or 4th generation cephalosporins, chloramphenicol, ampicillin, PCN, oxacillin

47

Other Problems

Local infection problems

• Aminoglycosides inactivated by low pH and low oxygen tension

• Beta-lactams inoculum effect

–More vulnerable to hydrolysis of beta-lactamases

48



Timing of Antibiotics

49

Early treatment of infection

Compliance with the 6-hour sepsis bundle and hospital mortality (n = 101). NNT, number needed to treat; RR, relative risk

Gao F, et al. Critical Care. 2005; 9:R76450



Requirements For Short Course Antibiotic Therapy

Fully susceptible pathogen; no risk of selection of resistance

Bactericidal antibiotics (or combination) with optimum dose/dosing regimen

Rapid onset of antibiotic action

Good penetration of antibiotic into the infection site

Antibiotic active against non-dividing bacteria

Antibiotic action not affected by adverse infection conditions

No foreign body present

No abscess formation

No signs of immunodeficiency

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Disease Longer Treatment (days) Equally Effective Shorter Treatment (days)

Abdominal infection 10 4

Bronchitis in people with Chronic Obstructive Pulmonary Disease (COPD)

7 or more 5 or fewer

Bacterial sinus infection 10 5

Cellulitis (skin infection) 10 5 to 6

Chronic bone infection 84 42

Kidney infection 10 to 14 5 to 7

Pneumonia acquired in the hospital

10 to 15 8 or fewer

Pneumonia acquired outside the hospital

10 to 14 3 to 5

Short Course Antimicrobial Therapy

Adapted from: Spellberg B, The New Antibiotic Mantra: "Shorter is Better," JAMA Internal Medicine, July 25, 2016.

52



What Factors Promote Antimicrobial Resistance?

• Exposure to sub-optimal levels of antimicrobial

• Exposure to microbes carrying resistance genes

53

Selective pressure for antibiotic concentration lower than the MIC

MIC

Time

Traditional hypothesis on emergence of AMR

Plasm

a concentrations

54



The selection window hypothesis

Mutant prevention concentration (MPC)(to inhibit growth of the least susceptible, single step mutant)

MICSelective concentration (SC)to block wild-type bacteria

Plasm

a concentrations

All bacteria inhibited

Growth of only the most resistant subpopulation

Growth of all bacteria

Mutant Selection window

Adapted from: Canton R, et al. Enferm Infecc Microbiol Clin 2013;31 Supl 4:3-1155

Summary Antimicrobial PK/PD

Through the integration of microbiologic data, pharmacodynamics data and pharmacokinetic

parameters, determination of optimal antimicrobial therapy is possible

DRUG

BUG HOST

56



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