1

Developing Combinations for Pneumonia: Indications,

Regulation, and Opportunities

Michael N. Dudley, PharmD, FIDSA

Senior Vice President and Head of R&DCo-Leader, Infectious Disease Global Innovation Group

The Medicines CompanySan Diego, CA

ASM MicrobeNew Orleans, LA June 2017

2

MN Dudley: Disclosure• Employee, hold stock in the The Medicines Company

• Hold equity with the following: Rempex Pharmaceuticals, Tripex Pharmaceuticals

• Principal investigator for meropenem-vaborbactam program that is supported in part with federal funds from the Department of Health and Human Services; Office of the Assistant Secretary for Preparedness and Response; Biomedical Advanced Research and Development Authority (BARDA), under Contracts Nos. HHSO100201400002 and HHSO100201600026C

• Principal Investigator and Management Board member of the Innovative Medicines Initiative’s (IMI) ND4BB COMBACTE-NET program in the EU

• Special thanks to: Paul Ambrose/ICPD, FNIH, and CTTI

• Several investigational agents and potential uses will be discussed that are not approved by the US FDA

3

Outline

• Why study new drugs in HABP/VABP?

• Challenges in conducting studies of new drugs in HABP/VABP

• Collaborations between regulators, industry and clinical trial specialists are providing helpful guidance for design and conduct of feasible clinical trials

• PK and PK-PD considerations:-Lessons learned

-Special considerations for fixed combination products (beta-lactam/beta-lactamase inhibitors)

4

Opportunities: Societal Estimated Net Present Value (ENPV) for Treatments That Improve Mortality, Morbidity and Avoid Delay in Clinical Response

• Eastern Research Group under contract from FDA and NIAID, 2014

FINAL APRIL 15, 2014

3-39

$0 $40,000 $80,000 $120,000 $160,000 $200,000

ABOM

ABSSSI

CABP

CIAI

CUTI

HABP/VABP

ABOM ABSSSI CABP CIAI CUTI HABP/VABPSocial ENPV $487 $584 $9,375 $1,069 $6,065 $12,166

Figure 6: Sensitivity of Estimated Social ENPVs by Indication for a New Antibacterial Drug (in $ Million) - Error Bars Represent 90% Confidence Bounds

� Percentage change in disease duration for patients that do not respond to commonly used antibacterial drugs,

� Phase 1 clinical trial success probability,

� Pre-clinical R&D success probability, and

� Real annual social rate of discount.

Table 18: Social EPV Sensitivity Results (Figures are in $ Million)

Indication Social EPV Min Mean Max

ABOM $48 $486.6 $5,363 ABSSSI $58 $584.2 $6,133 CABP $706 $9,375.3 $72,494 CIAI $114 $1,069.2 $10,231 CUTI $674 $6,064.6 $54,795

HABP/VABP $1,068 $12,165.6 $161,335

NIAID/FDA Workshop, July 30-31, 2014

This analysis supports early use of active antibiotics in patients that would improve mortality/morbidity and avoiding delays in clinical response (ie, use the active drugs first) have the greatest societal impact

5

Unmet Need: No Drugs for Pulmonary Infections, Especially Nosocomial Pneumonia (HABP/VABP)Number of Antibiotics with initial FDA approval(s) according to indication and year

• Rex JH, Talbot GH, Goldberger MJ, Eisenstein BI, Echols RM, Tomayko F, Dudley MN, Dane A. Progress in the Fight vs. MDR Bacteria 2005-16: Modern Noninferioty Trial Designs Enable Antibiotic Development in Advance of Epidemic Bacterial Resistance. Clin Infect Dis 2017 (online)

• CID 2017:XX (XX XXXX) • 5Noninferiority Trials of Antibacterials

that all future drugs be superior to existing drugs based on clin-ical efficacy measures [3, 26]. Specifically, noninferiority trials address the problem that one size does not fit all: By means of these trials, agents with superiority grounded in other features (eg, a different spectrum of activity, a novel mode of action, a better adverse event profile, and/or more convenient adminis-tration) can be made available for the benefit of specific patients.

A recent drug development vignette highlights the full array of challenges reviewed in this paper. The developers of plazomicin sought initially to implement a pivotal program focused entirely on enrolling patients infected with highly resistant pathogens for which a standard-of-care colistin-based therapy (the only then-current alternative) was thought likely to be either toxic or limited in efficacy. When it became apparent that substantial enrollment in such a program was infeasible, a pivotal trial focused on UDR pathogens was added and the study in the setting of MDR/XDR pathogens made supplemen-tal [32, 33]. This trial program ultimately demonstrated a mor-tality benefit of the new agent over colistin-based therapy [34]. It is of course good news that a new agent has progressed, but it should be noted that (1) this occurred because patients in the colistin-based therapy arm died due to lack of adequate therapy and (2) the emergence of this drug plus other recently licensed agents will progressively make it unethical to use such an infe-rior colistin-based treatment arm as a control in this setting.

The insights discussed in this article into the regulatory sci-ence of noninferiority trial design have profoundly reshaped the antibiotic pipeline (Figure 1). The most recent approval of an oral administration–only antibiotic was in 2003, and the last approval of an antibiotic for milder outpatient skin or upper res-piratory infections was in 2001. Conversely, all initial antibiotic

registrations since 2009 have included an intravenous route of administration and have been for one of the infections recom-mended for routine study (Table 1). Table 1 also highlights the resurgence of antibiotic development since the creation circa 2009–2010 of updated regulatory guidance—although much remains to be done, these are encouraging signs that new agents will be available in the future.

In conclusion, noninferiority trial designs are a necessary and essential part of antibiotic drug development. Without them, ensuring availability of efficacious and safe, novel antibi-otics in advance of epidemic spread of resistant bacterial strains is impossible, to the obvious detriment of individual and public health.

NotesAuthor contributions. All authors contributed to all phases of manu-

script generation, from concept to writing.Disclaimer. The views expressed are those of the authors and not nec-

essarily those of their respective employers.Potential conflicts of interest. J. H. R. is Chief Medical Officer and

Director of F2G, Ltd; Chief Strategy Officer, CARB-X; Non-Executive Director and Consultant, Adenium Biotech ApS; Operating Partner and Consultant, Advent Life Sciences; Expert-in-Residence, Wellcome Trust; serves on the Scientific Advisory Boards of Macrolide Pharmaceuticals; Spero Therapeutics; and Bugworks Research, Inc; is a shareholder in AstraZeneca Pharmaceuticals, F2G, Ltd, Adenium Biotech ApS, Advent Life Sciences, Macrolide Pharmaceuticals, and Bugworks Research, Inc; and has received consulting fees from Phico Therapeutics, ABAC Therapeutics, Polyphor, Ltd, Heptares Therapeutics, Ltd, and Gangagen, Ltd. G. H. T. has received board compensation and/or consultancy fees from Achaogen, Actelion, Adynxx, Anacor, Durata, Cubist, Meiji, Nabriva, and Zavante; and is a shareholder in AN2, Calixa, Durata, Kalyra, Mpex (Tripex), and Nabriva. M. J. G. is previously an employee of AbbVie and now an independent consultant. He has received consulting fees from AbbVie, Arsanis, Astellas, AtoxBio, Axar, Cempra, Cubist, Denovo, Forest/Actavis, GLG, Melinta, NDA Partners, RedHill, Spero, TenNor, Tetralogic,

Figure 1. Initial antibacterial approvals by route and indication, 1995–2016. Initial approvals of antibacterial agents from 1995 to 2016 were retrieved from CDERWatch and Drugs@FDA and are shown by approved route and number of initially approved indications (some agents were approved for >1 indication). As needed due to evolution of indication terminology, indications were grouped. The 2016 approval of bezlotoxumab to reduce recurrence of Clostridium difficile infection is not shown. Abbreviations: CABP, community-acquired bacterial pneumonia; cIAI, complicated intra-abdominal infection; cSSTI, complicated skin and skin structure infection; cUTI, complicated urinary tract infection; Genital, uncomplicated gonorrhea, prostatitis, nongonococcal urethritis, and chlamydia; IV, intravenous; Meningitis, bacterial meningitis; NP, nosocomial pneumonia including hospital- and ventilator-associated pneumonia; Mild RTI, acute otitis media, acute bacterial exacerbation of chronic bronchitis, acute sinusitis, and pharyngitis/tonsillitis; uSSTI, uncomplicated skin and skin structure infection; uUTI, uncomplicated urinary tract infection.

!!!

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Challenges in Conducting Clinical Trials in HABP/VABP

• Feasibility: slow/difficult enrollment, extensive data collection

• Cost of trials

• PK, PK-PD Considerations and Perils in Clinical Trials

7

Per Patient Costs in a HABP/VABP Trial Are Among the Highest: Comparisons With Oncology and Endocrine Clinical Trials(Stergiopoulos S, et. al. DIA 2016, poster T08)

• Key Driver of Cost in HABP/VABP in Per Patient Direct Costs· Recruitment/consenting process· Screen failures: Cost as well as screen failure rate· Trial size: requirement of more sites

Cost Drivers of a Hospital Acquired Bacterial Pneumonia and Ventilator Acquired Bacterial Pneumonia (HABP/VABP) Phase Three Clinical Trials

Hospital Acquired Bacterial Pneumonia (HABP) and Ventilator Acquired Bacterial Pneumonia (VABP; combined- Nosocomial pneumonia, NP or healthcare-associated pneumonia HCAP) are acute infections that occur in hospitalized patients. A hospital stay of 48 hours or more will expose patients to potential infections with a variety of gram-positive and gram-negative bacteria, many of which have become antibiotic resistant.[1]

Studies indicate that the prevalence of NP has been rising.[2] Many of these cases are caused by antibiotic resistant bacteria, increasing the demand for new antibiotics.[3] However, NP clinical trials are very costly to conduct given protocol complexities, multiple pathogens, and difficulty recruiting and retaining patients. NP drug candidates under development are therefore more likely to be discontinued.[4,5]

A new study conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD) and the Clinical Trials Transformation Initiative at Duke University (CTTI) evaluates the drivers of HABP/VABP direct and indirect clinical trial costs and identifies opportunities to lower these costs. It is hoped that the results of this study increase biopharmaceutical company incentives to continue to develop HABP/VABP drugs.

PER-TRIAL DIRECT COST ELEMENTS

INDIRECT COST ELEMENTS

Introduction• Tufts CSDD determined the fully-loaded cost of a HABP/VABP phase

III clinical trial with 1,000 patients and 200 global sites to be, on average, $89,600 per patient.

• Phase III HABP/VABP clinical trials are $9,000 per-patient more expensive than phase III oncology clinical trials, and $34,000 per-patient more expensive than endocrine studies.

• Key variables affecting the cost of a typical phase three HABP/VABP trial can be stratified are the number of patients, the number of sites, procedure costs, screen failure rates, the cost of screen fails, and the cost of patient recruitment.

PER-PATIENT DIRECT COST ELEMENTS

Tufts CSDD, in collaboration with CTTI developed a comprehensive, detailed mapping of direct and indirect cost elements. Primary cost elements include per-patient direct procedure costs, per-trial and per-site costs:

Tufts CSDD gathered benchmark data to create a model calculating a fully-loaded (direct and indirect) cost profile of a typical phase three HABP/VABP clinical trial. Costs for phase III oncology trials and endocrine trials were also calculated for comparison. Data were gathered from the following:• Internal databases provided site and subject (patient) data• Medidata Solutions provided protocol and site cost data• Oracle Clinical provided benchmarking costs for HABP/VABP• IMS Health provided country-site distribution data• PMG, and CenterWatch provided site cost estimates (e.g. IRB fees, case

report form fees; etc.)• FDA, Centerphase Solutions and Mckane et al [3] provided patient

screen-failure rates and randomization rates.• Data involving printing costs, translation costs, and server costs for

electronic data capture (EDC), and clinical trial insurance costs were gathered from companies providing these services and solutions.

Assumptions provided on study duration were derived from industry experts. This study was conducted from November, 2014 to May, 2015.

Variable HABP/VABP Oncology Endocrine

Total Sites (all locations) 200 sites 279 sites 123 sites

Total Subjects (all locations) 1,000 subjects 448 subjects 582 subjects

Total Number of Countries 52 countries 74 countries 47 countries

Randomization Rate

1 patients randomized per

100 screened

25 patients randomized per

100 screened

45 patients randomized per

100 screened

STUDY ASSUMPTIONS

Therapeutic Area Per-Patient Direct Cost($000)

Per-Trial Direct Cost($000)

Indirect Cost($000)

Total Cost Per Patient($000)

Endocrine $9.5 $42.3 $5.8 $57.5

Oncology $18.2 $61.8 $7.5 $87.4

HABP/VABP* $66.1 $20.1 $3.3 $89.6

1. World Health Organization Antimicrobial Resistance: Global Report on Surveillance. 2014. [Accessed May 24, 2016]. Available from: http://apps.who.int/iris/bitstream/10665/112642/1/9789241564748_eng.pdf?ua=1.

2. Jones RN. Microbial Etiologies of Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia. Clin Infect Dis. 2010 Aug 1; 51 Suppl 1: S81-7. DOI: 10.1086/653053.

3. Patel DA, Michel A, Stephens J, Weber B, Petrik C, Charbonneau C. An economic model to compare linezolid and vancomycin for the treatment of confirmed methicillin-resistant Staphylococcus aureus nosocomial pneumonia in Germany. Infection and drug resistance. 2014;7:273-80.

4. Power E. Impact of antibiotic restrictions: the pharmaceutical perspective. Clinical Microbiology and Infection. 2006 8//;12, Supplement 5:25-34.

5. Race against time to develop new antibiotics: Bulletine of the World Health Organization; 2011;89(2):81-160.

6. Mckane A. et al. Determinants of Patient Screen Failure in Phase 1 Clinical Trials. Invest New Drugs. 2013 June: 31(3):774-9.

Personnel Costs

• Sponsor Personnel• Clinical Pharmacology• CRO/Site Contract

Management• Document Manager• Clinical Research Associate• Physician• Statistical Programmer• Study Manager• Pharmaceutical Technician• Product Development

• Site Personnel• Principal Investigator• Co-Investigator• Research Nurse / Study

Coordinator• Technician• Other Administration• Recruitment Specialist• Microbiologist• Regulatory Affairs• Pharmacist / Pharmacy tech

Site and Clinical Supply Costs

•IRB Fees (Local)

•Amendment Fees

•Record Keeping and Storage

•Site Recruitment Costs (marketing)

•PI Training / Travel Costs

•Meeting costs for clinical travel team (venue, food, travel)

•Clinical Supply Costs (for this model is fixed)•Manufacturing•Comparator

•Trial Insurance Costs

Printing / Paper / Data Costs

• Investigator Brochure• Printing• Translation

• Study Protocol• Printing• Translation

• Informed Consent• Printing• Translation

• Case Report Form• Printing• Translation

• Data Costs• Server charges for EDC• IT Charges for EDC• Storage Costs• Data Entry Costs

Upper Management Time

• Vice President

• Executive (Medical) Director

• Associate Director

• Biostatistics Manager

Overhead Costs

• Travel and Meetings

• Depreciation (equipment)

• Depreciation (buildings)

• Other infrastructure costs

• Material and office supplies

• IT costs

Other Costs

• Administration Costs

• Training and Professional Development

• Employee Benefits

Per-Patient Direct Costs Patient Costs

Per-Trial Direct Costs • Personnel Costs

(Pharmaceutical Company and Investigative Site)

• Site and Clinical Supply Costs; Trial Insurance

• Printing / Paper / Data Costs

Per-Trial Indirect Costs•Upper

Management Time•Overhead Costs•Misc. Costs

Figure 1. The Primary Cost Elements

Figure 2. List of Per-Trial and Per Site Cost Elements.

Figure 3. List of Indirect Cost Elements

Figure 4. Study Assumptions. Site and patient (subject) assumptions based on internal Tufts CSDD databases.

Figure 6. Cost Drivers: Changing One DriverUsing current assumptions: cost is $89,600 per patient. Assuming geographic distribution of patients is equal to the geographic distribution of sites (10% of patients in the US). Increasing the number of patients decreases costs as the number of patients outside of the US (in less expensive regions) increases.

Funding for this analysis was made possible by the Food and Drug Administrationthrough grant R18FD005292, views expressed in this manuscript do not necessarilyreflect the official policies of the Department of Health and Human Services; nor doesany mention of trade names, commercial practices, or organization imply endorsementby the United States Government.

We thank the FDA, CenterWatch, Medidata Solutions, Epharma Solutions, IMS, OracleClinical, and PMG for their help in this study.

AVERAGE COST PER PATIENT FOR ENDOCRINE, ONCOLOGY, AND HABP/VABP PHASE III CLINICAL TRIALS

Figure 5. Average cost-per-patient for a Phase III Endocrine, HABP/VABP, and Oncology trial.*HABP/VABP trials may run to a maximum of $165,000 per patient under the same assumptions (1,000 patients; 200 sites; 32 countries). Maximum provided by Oracle Clinical. Per-patient direct costs are high for HABP/VABP due to high screen failure rate.

• Assessment of certain variables for sensitivity assessment is limited (e.g. procedure costs)

• Some cost elements are average costs across all therapeutic areas• Assuming that proportion of sites by country is the same as

proportion of patients by country• Assuming that site-patient percentage is the same for HABP/VABP,

oncology and endocrine trials• Assuming internal work effort is the same for HABP/VABP, oncology

and endocrine trialsIMPACT OF CHANGING KEY COST DRIVER AT A TIME FOR HABP/VABP CLINICAL TRIALS

IMPACT OF CHANGING MULTIPLE COST DRIVERS AT A TIME FOR HABP/VABP CLINICAL TRIALS Figure 7. Cost Drivers: Changing

Multiple DriversUsing current assumptions: cost is $89,600 per patient. Assuming geographic distribution of patients is equal to the geographic distribution of sites (10% of patients in the US).

• Opportunities to lower the high costs of HABP/VABP clinical trials exist.

• The cost of screen fails, as well as screen failure rates are the main drivers of cost for a phase III HABP/VABP trial.

• Future studies are looking to asses best practices for protocol design in order to decrease costs while maintaining scientific rigor.

Poster T 08

S. Stergiopoulos1, P. Tenaerts2, KA Getz1, C. Brown1, J. Awatin1, S. Calvert2, JA DiMasi1

1. Tufts Center for the Study of Drug Development, Tufts University School of Medicine, Boston, Massachusetts2. Clinical Trials Transformation Initiative (CTTI), Duke University, Durham, North Carolina

Methodology

Methodology•Patient Recruitment •Procedures•Patient Retention (i.e. compensation) •Lab Tests•Informed Consent •Query Resolution•Clinical Trial Insurance •Data Entry•Screen Fails

ResultsSummary

Limitations

Conclusions

References

Acknowledgements

$88

$95

$89

$84

$85

$90

$91

$86

$90

$95

$94

$90

$78 $80 $82 $84 $86 $88 $90 $92 $94 $96 $98

Number Sites(+/-50 sites)

Number Patients(+/- 200 patients)

Procedure Cost(+ / - $500/patient)

Screen Failure Rate(+/- 10 screens)

Cost of Screen Fails(+/- $60/patient)

Cost of Recruitment(+/- $50/patient)

Thousands

Low High

$94

$85

$85

$80

$87

$94

$94

$100

$78 $83 $88 $93 $98 $103

Number Sites, Number Patients(+/-50 sites, +/- 200 patients)

Cost of Screen Fails, Recruitment(+/- $60/patient, +/- $50/patient)

Cost of Screen Fails, Procedure Cost(+/- $60/patient , + / - $500/patient)

Cost of Screen Fails, Patient Randomization(+/- $60/patient , + / - 10 screens)

Thousands

Low High

8

Collaborations Between Expert Clinicians, Industry, and Regulators are Helping to Improve Trials in HABP/VABP• Clinical Trials Transformation Initiative (CTTI; Clin Infect Dis 2016 Suppl 2;

https://www.ctti-clinicaltrials.org/projects/streamlining-habpvabp-trials)- Streamlining protocol elements (e.g., improved informed consent procedures (pre-consent in

high risk patients; protocol design; IRBs; outcomes/endpoints)- Operational efficiencies for data collection (AEs; lab data; con meds)- Prospective observational study of risk factors for HABP and VABP (CTTI 001)

• Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium- Assessment of the robustness of all cause mortality endpoint across various HABP/VABP

patient subsets (e.g., ventilated HABP)- Prognostic factors- Alternative endpoints- PROs- Submitted to FDA docket for review in May 2017

9

Recent Experience in Clinical Trials in HABP/VABP of Some Agents Have Included Some Hard PK-PD Lessons

• Low doses/exposures of doripenem

• Low ELF exposures with ceftibiprole

• Differences in tigecycline clearance, MICs in HABP vs. VABP

FDA Workshop, July 2016. Slide/Analysis Courtesy of Dr. Paul Ambrose/ICPD

10

Understanding Efficacy in Clinical Trials: Its all about where you are on the exposure-response curve

Drug exposure response from nonclinical models of infection

FDA Workshop, July 2016. Slide/Analysis Courtesy of Dr. Paul Ambrose/ICPD

Exposures in patients linked with MIC distributions for target attainment estimates from simulations

11

Marginal Dosing of Tigecycline, Higher Clearance in VABP Patients, and Higher MICs in VABP Patients Resulted in Poor Response

Preclinical data: Courtesy of William A. CraigClinical data: Bhavnani SM, Rubino CM, Hammel JP, Forrest A, Dukart G, Dartois N, Cooper A, Korth-Bradley J, Ambrose PG. Pharmacological and patient-specific response determinants in patients with hospital-acquired pneumonia treated with tigecycline. Antimicrob Agents Chemother. 2012; 56:1065-1072Rubino CM, Ma L, Bhavnani SM, Korth-Bradley J, Speth J, Ellis-Grosse E, Rodvold KR, Ambrose PG, Drusano, GL. Evaluation of tigecycline penetration into colon wall tissue and epithelial lining fluid using a population pharmacokinetic model and Monte Carlo simulation. Antimicrob Agents Chemother, 2007 November; 51(11), 4085-4089.

• Poor clinical results in VABP patients (Friere et. al, DMID 2010)

- Population PK studies showed that tigecycline clearance was more rapid in patients with VABP

- Higher MICs in VABP patients

- The net impact is a downward shift to bottom of the dose response curve

FDA Workshop, July 2016. Slide/Analysis Courtesy of Dr. Paul Ambrose/ICPD

12

Combination Antimicrobial Therapy in HABP/VABP: Special Case of Beta-lactam/Beta-lactamase InhibitorsPK• Importance of PK of BOTH BLI and partner beta-lactam:

· PK in ELF· PK in patients (renal impairment)

PK-PD· Identify the PK-PD index for efficacy of a beta-lactamase inhibitor for bacterial

killing AND resistance prevention· Dosage regimens to insure you get those exposures in patients and with dosage

adjustments in renal impairment

13

Meropenem PK-PD in Preclinical Models, PK in ELF and Patients

Preclinicaldata: LouieA,LiuW,FikesS,BrownD,DrusanoGL.ImpactofmeropenemincombinationwithtobramycininamurinemodelofPseudomonas aeruginosapneumonia.AntimicrobAgentsChemother.2013June;57(6),2788-2792.Surveillancedata:EUCAST(2016).MICdistributionsandECOFFs.Availableatwww.eucast.org/mic_distributions_and_ecoffs/.Accessed July2016.Clinicaldata:MattioliF,FucileC,DelBonoV,MariniV,ParisiniA,MolinA,ZuccoliML,MilanoG,DanesiR,MarcheseA,PolilloM,ViscoliC,PelosiP,MartelliA,DiPaoloA.Populationpharmacokineticsandprobabilityoftargetattainmentofmeropenemincriticallyillpatients.Europeanjournalofclinicalpharmacology,2013;1-10.Lodise TP,SorgelF,MelnickD,MasonB,KinzigM,DrusanoGL.Penetrationofmeropenemintoepithelialliningfluidofpatients withventilator-associatedpneumonia.AntimicrobAgentsChemother.2011April;55(4),1606-1610.

FDA Workshop, July 2016. Slide/Analysis Courtesy of Dr. Paul Ambrose/ICPD

14

• KPC-containing strains of Enterobacteriaceae with meropenem-vaborbactam MICs ranging from 0.06 – 64 mg/L

• Selected from clinical isolates with mixtures beta-lactamases and other mutations known to affect sensitivity to meropenem and vaborbactam (e.g., OmpK mutations)

• Test high innocula (hollow fiber) to encourage resistance

• Identify PK-PD index for vaborbactam

PK-PD of Meropenem plus the Beta-Lactamase Inhibitor Vaborbactam in Nonclinical Models(Griffith D et. al. Microbe 2017 Poster Session 341-AAID03 #193; Sunday)

Strain Beta-Lactamases OmpK35 OmpK36Meropenem MIC (µg/mL)

ModelAlone

w/Vaborbactam4 µg/mL 8 µg/mL

E. coli EC1007 KPC-3 ND ND 8 ≤0.06 ≤0.06 HF

E. cloacae ECL1058 KPC-3, SHV-11, TEM-1 FL FL 8 0.125 0.125 HF

E. cloacae ECL1061 KPC-3, Hyper AmpC Expression FS aa#287 FL 16 0.125 0.125 HF

E. cloacae ECL1079 KPC-3 stop aa#60 stop aa#77 >64 32 8 Mouse, HFK. pneumoniae KP1061

KPC-3, SHV-11, TEM-1 FS aa#42 FL 16 ≤0.06 ≤0.06 HF

K. pneumoniae KP1074

KPC-3, SHV-11, TEM-1 FS aa#42 GD >64 1 0.5 HF

K. pneumoniae KP1087

KPC-2, CTX-M-15, SHV-11, TEM-1 FS aa#208 GD 32 0.5 0.25 HF

K. pneumoniae KP1092

KPC-2, SHV-11, SHV-12, TEM-1 FS aa#42 IS at -45 >64 128 32 HF

K. pneumoniae KP1093 KPC-3, SHV-11, TEM FS aa#42 GD >64 2 0.5 Mouse, HF

K. pneumoniae KP1094

KPC-2, TEM-1, LEN-17

stop aa#230 stop aa#92 >64 32 4 Mouse, HF

K. pneumoniae KP1096 KPC-2, TEM, SHV-11 L63V,

E132KIS at

nt#126 >64 64 16 Mouse, HF

K. pneumoniae KP1099

KPC-2, SHV-11, SHV-12, CTX-M-14 FS aa#29 GD >64 4 1 HF

K. pneumoniae KP1100 KPC-3, TEM, SHV FS aa#42 GD >64 16 4 HF

K. pneumoniae KP1194 KPC-2 TEM SHV FS aa#42 IS at -45 >64 64 8 HF

K. pneumoniae KP1223 KPC-2, SHV, TEM FS aa#29 GD >64 64 8 Mouse, HF

K. pneumoniae KP1244

KPC-3, SHV-11, SHV-12 FS aa#42 R191L,

T333N >64 64 16 HF

K. pneumoniae KP1254

KPC-2, SHV, TEM, OXA-10 FS aa#42 IS and

ΔopmK36 >64 >64 64 HF

15

Meropenem-Vaborbactam PK-PD in Hollow Fiber Model(Griffith D et. al. Microbe 2017 Poster Session 341-AAID03 #193; Sunday)

-7-6-5-4-3-2-101234

0 1000 2000 3000 4000 5000 6000 7000

Cha

nge

in L

og C

FU fr

om th

e St

art o

f Tr

eatm

ent

Free 24h VAB AUC/M-V MIC (VAB @ 8 mg/L)

• KPC-producing strains of Enterobacteriaceae with meropenem-vaborbactam MICs ranging from 0.06 – 64 mg/L• 24h free vaborbactam AUC:MIC m-v best describes bacterial killing in hollow fiber model • Log kill and non beta-lactamase mediated resistance targets identified

16

Pharmacokinetics of Meropenem and Vaborbactam in Epithelial Lining Fluid (ELF) in Normal Subjects

17

Meropenem-Vaborbactam Population Pharmacokinetics in Healthy Volunteers and Infected Patients (Trang et. al, Microbe 2017 Poster Session 341-AAID03 #192; Sunday)

VaborbactamMeropenem

18

Summary

• There is an unmet need for new drugs in HABP/VABP, especially with activity against MDR gram-negative pathogens

• Recent guidance and ongoing improvements in trial conduct and design are helping make them more feasible

• Clinical trial misadventures stemming from failure to consider pharmacometric relationships in the planning of trials

• Complexity is increased with combinations of agents, but can be dealt with by careful planning