Translating Patient Diversity into Optimal Drug Therapy A Tour of FDA’s Office of Clinical Pharmacology Joseph A. Grillo, Pharm.D. Associate Director of Labeling and Health Communication Office of Clinical Pharmacology (OCP) Office of Translational Sciences Center for Drug Evaluation and Research U.S. Food and Drug Administration This presentation reflects the views of the author and should not be construed to represent FDA’s views or policies.

Overview History and organizational overview of the Office of Clinical Pharmacology (OCP) Regulatory review resources Transforming public health through research Prescription Drug User Fee Act (PDUFA) VI Model informed drug development (MIDD) Physiologically based pharmacokinetic (PBPK) modeling Integration of precision medicine and genomics OCP labeling and guidance initiatives External engagement and collaborative opportunities with OCP

Evolution of Clinical Pharmacology at FDA Applied regulatory science | Evidence assessment | Dose optimization Therapeutic individualization | Policy | Communication NOW 1980s Early 1990s Mid 1990s Late 1990s 2000s BA/BE Dosage forms Metabolism Early modeling (IVIVC, PK-PD) Organ impairment Sex effects Advanced PM (D/R, E/R, disease modeling, trial simulation) Pediatric pharmacology Pharmacogenomics PBPK Mechanistic safety Systems pharmacology

Clinical Pharmacology in Drug Development and Evaluation EOP1 EOP2 NDA sNDA PRECLINICAL PHASE I PHASE II PHASE III PHASE IV Chemical, MOA, safety characteristics First in human Dose-ranging studies Early PK/PD Dose identification PK/PD in patients E-R/E-S PK/PD & E-R/E-S in target population Labeling Develop BA method PMC/PMR In vivo DDI Extrinsic factors Dose optimization Mitigation strategies in the target population In vitro metabolism, transporter, & DDI Early food-effect Mass balance ACTION In vitro protein binding, cellular/tissue distribution Renal/hepatic, disease, intrinsic factors Food-effect BA/BE Surveillance Relevant animal/POC QTc study Target, mechanistic, &/or physiologic biomarker identification Pharmacogenomics Pharmacostatistical Modeling & Simulation Discovery Learn Confirm

Office of Clinical Pharmacology (OCP) OUR VISION MISSION Improve public health by building and translating knowledge of drug response into patient-centered regulatory decisions of the highest quality Play a pivotal role in advancing development of innovative new medicines by applying state-of-the- art regulatory science and clinical pharmacology principles Promote therapeutic optimization and individualization through best practices in research, policy development, and drug evaluation throughout the product lifecycle OCP is a dynamic, purpose-driven organization whose goals are to: Enhance drug development Promote regulatory science and innovation Inform the optimal use of medications https://www.fda.gov/aboutfda/centersoffices/officeofmedicalproductsandtobacco/cder/ucm106189.htm https://www.fda.gov/aboutfda/centersoffices/officeofmedicalproductsandtobacco/cder/ucm106189.htm

Through the application of state-of-the-art regulatory science and clinical pharmacology principles we: Conduct research, use data-based tools, & formulate best practices Promote therapeutic individualization & personalized medicine Use experimental & analytical approaches Employ mechanistic & model-informed drug development strategies Generate, evaluate, & use knowledge of drug disposition, pharmacology, & disease biology WHAT WE DO Progressively reduce regulatory uncertainty & inform public health decision-making Maximize the value of early & late phase clinical drug development Identify, account for, & ultimately predict patient variability in drug responses Translate knowledge of patient diversity into clinical recommendations for safe & effective drug use Address immediate & emerging issues that impact development, regulatory evaluation, & utilization of therapeutic products Functions Outcomes

OFFICE OF CLINICAL PHARMACOLOGY Issam Zineh – Director Shiew-Mei Huang – Deputy Director Michael Pacanowski Associate Director for Genomics & Targeted Therapy E. Dennis Bashaw Senior Science Advisor Gil Burckart Associate Director for Pediatrics Colleen Kuemmel Staff Fellow Peter Lee Associate Director for Knowledge Management Karen Graves Program Support Specialist Genomics & Targeted Therapy Group Raj Madabushi Team Leader, Guidance & Policy Guidance & Policy Team Joseph Grillo Associate Director for Labeling & Health Communication Labeling & Health Communication Group Jessica Benjamin Chief Program Manager Yow-Ming Wang Director, Therapeutic Biologics Executive Program & Project Management Staff Therapeutic Biologics Program DIVISION OF CLINICAL PHARMACOLOGY I DIVISION OF CLINICAL PHARMACOLOGY IV Mehul Mehta – Director Ramana Uppoor – Deputy Director John Lazor – Director Kellie Reynolds – Deputy Director DIVISION OF CLINICAL PHARMACOLOGY II DIVISION OF CLINICAL PHARMACOLOGY V Chandra Sahajwalla – Director Suresh Doddapaneni – Deputy Director Atiqur Rahman – Director Brian Booth – Deputy Director DIVISION OF CLINICAL PHARMACOLOGY III DIVISION OF PHARMACOMETRICS Shirley Seo – Director Doanh Tran – Deputy Director Yaning Wang – Director Hao Zhu – Deputy Director DIVISION OF APPLIED REGULATORY SCIENCE David Strauss – Director Rodney Rouse – Deputy Director

Novel Product Approvals in 2018 https://www.fda.gov/about-fda/center-drug-evaluation-and-research/reports-budgets-cder

Critical NDA & BLA Review Examples in 2018 LIBTAYO (cemiplimab-rwlc): Utilized pharmacokinetic/pharmacodynamic (PK/PD) relationships to support a flat dosing regimen versus the weight-based regimen studied in clinical trials in patients with squamous cell carcinoma (SCC). TAKHZYRO (lanadelumab): Leveraged E/R information to support approval of new dosing regimen to treat patients with types I and II hereditary angioedema. TPOXX (tecovirimat): Established pediatric dosing recommendations based on PK modeling and simulation for treatment of smallpox infection under FDA’s Animal Rule regulatory pathway. DOSAGE OPTIMIZATION TIBSOVO (ivosidenib): Used physiologically-based PK (PBPK) modeling to support dosage reductions for TIBSOVO when administered with strong cytochrome (CYP) 3A4 inhibitors in treating patients for relapsed or refractory acute myeloid leukemia. YUPELRI (revefenacin): Evaluated metabolite exposures in moderate hepatic impairment patients to support a recommendation not to use YUPELRI to treat chronic obstructive pulmonary disease (COPD) patients with any degree of hepatic impairment. ZEMDRI (plazomicin): Integrated pharmacologic and E/R information from limited clinical data to inform therapeutic drug monitoring recommendations to mitigate acute kidney injury risk in patients with complicated urinary tract infections (cUTI) including pyelonephritis. RISK MITIGATION GALAFOLD (migalastat): Designed a labeling strategy that incorporates in vitro assay data to expand the treatment indication in adults with a confirmed diagnosis of Fabry disease and an amenable galactosidase alpha gene (GLA) variant. SYMDEKO (tezacaftor/ivacaftor): Expanded cystic fibrosis (CF) indication based on in vitro data for patients 12 years or older who have two copies of the F508del mutation of the CF transmembrane conductance regulator (CFTR) gene or have at least one mutations that is responsive to the drug. TIBSOVO (ivosidenib): Informed labeling for selecting adult patients for treatment with TIBSOVO for relapsed or refractory acute myeloid leukemia based on the presence of isocitrate dehydrogenase 1 (IDH1) mutations in the blood or bone marrow. GUIDING PATIENT SELECTION https://www.fda.gov/about-fda/center-drug-evaluation-and-research/reports-budgets-cder

https://www.fda.gov/downloads/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/ManualofPoliciesProcedures/UCM073007.pdf

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Drugs@FDA An Untapped Resource Drug X (drugoxide) Capsules Company: X , Inc. Application No: ###### Approval Date ##/##/#### Approval Letter(s) (PDF) Printed Labeling (PDF) Summary Review (PDF) Officer/Employee List (PDF) Office Director Memo (PDF) Cross Discipline Team Leader Review (PDF) Medical Review(s) (PDF) Chemistry Review(s) (PDF) Pharmacology Review(s) (PDF) Statistical Review(s) (PDF) Microbiology Review(s) (PDF) Clinical Pharmacology Biopharmaceutics Review(s) (PDF) Risk Assessment and Risk Mitigation Review(s) (PDF) Proprietary Name Review(s) (PDF) Other Review(s) (PDF) Administrative Document(s) & Correspondence (PDF) Drugs@FDA An Untapped Resource Searchable database of FDA-approved drug products, OTC human drugs and biological therapeutic products Updated daily Includes most drug products approved since 1939 Provides patient information, labels, approval letters, reviews, and other information for the majority of drug products approved since 1998

Research Within OCP OCP staff routinely conduct regulatory-based research as part of their professional development Competitive Internal Grants Research Grant Critical Path Grants Regulatory Science Research and Review Enhancement Grant Office of Women’s Health Medical Countermeasures Scientific Interest Groups Division of Applied Regulatory Science (DARS) Designs and conducts computational and laboratory research that can inform regulatory decision making and improve how drugs are developed and reviewed

OCP Unit Scope & Research Focus DCPI DCPII DCPIII DCPIV DCPV CV Renal Neurology Psychiatry Biomarkers for PAH and MDD Bioequivalence criteria for depot injection drugs in schizophrenia Optimization of trial designs in schizophrenia, rare diseases in neurology space and pediatric programs Allergy Analgesia/Anesthesia Diabetes/Endocrine/ Metabolism Pulmonary Rheumatology Derm/Dental GI/Inborn errors Bone/Repro/Uro Special monographs DDIs & BMI/BW on contraceptives BTM for BMD prediction Psoriasis biomarkers Antivirals Anti-infectives Solid organ transplant Ophthalmology Animal rule Anti-infective PK/PD & breakpoints DDIs in labeling Transporter mediated DDIs Animal doses to humans Oncology Hematology Medical Imaging Dose optimization PPI-oncology DDIs CIPN predictors Biologics DDIs & immunogenicity Therapeutic protein interaction, immunogenicity, E-R, biosimilarity and interchangeability, pediatrics Rare autoimmune disease dose selection E-R in pain/addiction CV= cardiovascular, PAH= pulmonary arterial hypertension, MDD= major depressive disorder, E-R= exposure-response, GI=gastrointestinal, DDI=drug-drug interaction, BTM= bone turnover markers, BMD= bone mineral density, PK/PD pharmacokinetics/pharmacodynamics, PPI= Proton-pump inhibitor, CIPN= chemotherapy-induced peripheral neuropathy

OCP Unit Scope & Research Focus TBP DPM DARS LHC GTTG All Therapeutic Areas All Therapeutic Areas All Therapeutic Areas All Therapeutic Areas Scope Biologic Products Scope Scope Scope Scope E-R relationships Disease models Safety visualization tool Dose optimization Mechanistic safety Assays & biomarkers Chemical & biomedical informatics Impact of labeling enhancements Parity between labeling & DI resources HCP literacy Impact of CP related labeling decisions Biosimilar & interchangeable products Immunogenicity Bioanalytical Methods Glycosylation or PEGylation and PK variability Genetic epidemiology Biomarker utilization Knowledge management Bioinformatics Research Research Research Research Research

Transforming Public Health Through Research https://www.fda.gov/about-fda/center-drug-evaluation-and-research/reports-budgets-cder

Integrating Scientific Innovation & Regulatory Review https://www.fda.gov/about-fda/center-drug-evaluation-and-research/reports-budgets-cder

PDUFA VI: Regulatory Decision Tools Complex Innovative Trial Designs Model-Informed Drug Development [Including PBPK] Biomarker Qualification Real World Evidence Benefit/Risk Assessment Patient Voice PDUFA: Prescription Drug User Fee Act

Model-Informed Drug Development PK/PD Exposure-Response In Silico Clinical Trial Simulations Human PK Dose Prediction Study Design Optimization Predict/Characterize: ADME Intrinsic /Extrinsic Factors Early Risk/Benefit Dosage Selection Labeling Population Bridging Development and application of exposure-based, biological, and statistical models derived from preclinical and clinical data sources to address drug development or regulatory issues* PK PopPK PBPK MIDD Disease Models Clinical Trial Models QSAR QSPR Systems Biology QSP CiPA QSAR: Quantitative structure–activity relationship QSPR: Quantitative structure–property relationship * From PDUFA 6; Excludes statistical designs involving complex adaptations, Bayesian methods, or other features requiring computer simulations to determine the operating characteristics of a confirmatory clinical trial.

MIDD: PBPK Modeling Note: A total of 254 submissions were reviewed by OCP including 94 NDAs, from 2008-2017. Each submission might have more than one area of application. For example, one submission may include one or more PBPK models to be used to support enzyme-, transporter- mediated DDI, as well as food effect. Grimstein, et al. J Pharm Sci. 2019;108(1):21-25.

Ibrutinib Applicant’s proposed model predicted untested lower potency inhibitors on "drug as substrate" DDI effects FDA initiated analyses Identified potential difference between reversible inhibitors & time dependent inhibitor effects Applicant simulations and FDA analysis informed prescription drug labeling (PDL) and provided decision support for potential dose staggering and dose reduction mitigation strategies http://www.accessdata.fda.gov/drugsatfda_docs/nda/2013/205552Orig1s000ClinPharmR.pdf

Precision Medicine An innovative approach to disease prevention and treatment that takes into account individual differences in people’s genes, environments, and lifestyles Precision medicines or targeted therapies*: Drugs or biologics intended for use with a genomic, proteomic, or other biomarker Identifies patients within a clinically-defined disease who are eligible for treatment based differences in efficacy or safety Aids in determining the appropriate dose Allows for monitoring of responses to individualize therapy Biomarkers may have diagnostic, prognostic, predictive, or other value and often mechanistically related to the drug * Unofficial definition

Uses of Genomics in Drug Development PREEMPTIVE Validate targets for drug development Predict drug toxicities Define target population PROSPECTIVE Predict drug exposure Minimize noise Identify patients at risk for disease or event Select patients likely to respond to drug RETROSPECTIVE Explain variable responses to drug Identify (non-)responders or patients with adverse reactions Identify risk for serious drug interactions

Novel Drugs Approved with Genomic and Other Biomarker Information in Labeling Actionable biomarker: specific prescribing recommendation that is included in one of the following sections of labeling: 1) Boxed Warning, 2) Indications and Usage, 3) Dosage and Administration, 4) Contraindications, or 4) Warnings and Precautions. Biomarkers may be any genomic biomarker or other selected protein biomarker that are used for patient selection.

Clinical Pharmacology Labeling Footprint 25 Highlights D&A BW, CI, W&P, AR, PCI, and others Drug Interactions Specific Populations Clinical Pharmacology Highly Actionable, Brief, Limited Context Less Actionable, Detailed, Additional Context D&A: Dosage and Administration BW: Boxed Warning CI: Contraindications W&P: Warnings and Precautions AR: Adverse Reactions PCI: Patient Counseling Information 25

CDER Labeling Initiative Prescription Drug Labeling Improvement & Enhancement Initiative (PDLIEI) established 2013 Enhance the safe and effective use of prescription drugs by facilitating optimal communication through PDL Increase percentage of PDLs that complies with PLR content and format requirements Develop and evaluate approaches to enhance clarity, utility, and comprehension of PDL across CDER Foster consistency in PDL across CDER by establishing guidances and best practices https://www.fda.gov/drugs/guidancecomplianceregulatoryinformation/lawsactsandrules/ucm084159.htm

HCP Perception Drug Interaction Information in PDL Current Presentation Ideal Presentation Confusing structure Too much information Wrong/out-of-date information No conveyance of risk No real guidance Easy to access and navigate Minimizes pharmacology jargon Clinically intuitive structure Imparts sense of severity or risk Provides risk management instructions Omits unnecessary information Up to date HCP= Healthcare Provider; PDL = Prescription Drug Labeling (also called Prescribing Information or the “PI”) OCP Advisory Committee for Pharmaceutical Science and Clinical Pharmacology September 25, 2013

Tabular Presentation for Complex or Highly Technical Information Disclaimer: Any tables and presented today are meant to be illustrative only; these examples are not intended to limit the use of other possible formats and approaches to convey critical information

Focus on Essential Information Consistency Through Tabular Formats Preferred Example: 12.3 Pharmacokinetics Drug Interaction Studies Strong CYP3A Inhibitors: Coadministration with a strong CYP3A inhibitor (ketoconazole) increased drugoxide Cmax by 1.3-fold and AUC by 2-fold. Non-Preferred Example: 12.3 Pharmacokinetics Drug Interaction Studies Coadministration of a single 40 mg dose of drugoxide with the strong CYP3A inhibitor ketoconazole (200 mg twice daily for 14 days) increased the Cmax and AUC of drugoxide by 1.3 and 2-fold, respectively, compared to when drugoxide was given alone in 14 healthy volunteers. Tmax was unchanged. A reduced starting dosage is recommended.

Complex Therapeutic Individualization Strategies Table X: Recommended Dosage Adjustments in Patients Taking Strong CYP2D6 Inhibitors, CYP3A Inhibitors, and/or CYP3A Inducersa and/or in Patients who are CYP2D6 Poor Metabolizers Current Dosage (mg) Dosing Frequency (hours) Perpetrators Modified Dosage Modified Frequency 2D6 Poor Metabolizer Concurrent/ strong CYP2D6 INH CYP3A INH CYP3A IND 200 mg 6 Yes No Avoid Use NA 400 mg 600 mg 12 a = CYP3A inducers taken for greater than 2 weeks; INH = inhibitor; IND = inducer; NA = not applicable

Guidance Development Initiative Guidance document Represent FDA's current thinking on a particular subject Does not create or confer any rights for or on any person Does not bind FDA or the public Draft guidances are published to collect public comments prior to finalization Comments made to a docket # found in the Federal Register (FR) notice Identify Issue Final Guidance Published FDA Working Group Guidance Development WG Reviews Comments & Revises Draft Guidance & FR Notice Stakeholder Comments To Docket https://www.fda.gov/regulatoryinformation/guidances/#about

Published or Planned OCP-Led Guidances GUIDANCES PUBLISHED IN 2018 Bioanalytical Method Validation (Final) Developing Targeted Therapies in Low-Frequency Molecular Subsets of a Disease (Final) Maximal Usage Trials for Topical Active Ingredients Being Considered for Inclusion in an Over-the- Counter Monograph: Study Elements and Considerations (Draft) Physiologically Based Pharmacokinetic Analyses- Format and Content (Final) GUIDANCES PUBLISHED OR PLANNED IN 2019 Bioavailability Studies Submitted in NDAs or INDs – General Considerations (Draft) Assessing the Effects of Food on Drugs in INDs and NDAs – Clinical Pharmacology Considerations (Draft) Maximal Usage Trials for Topical Active Ingredients Being Considered for Inclusion in an Over-the-Counter Monograph: Study Elements and Considerations (Final) General Clinical Pharmacology Considerations for Neonatal Studies for Drugs and Biological Products (Planned) Pharmacokinetics in Patients with Impaired Renal Function-Study Design, Data Analysis and Impact on Dosing and Labeling (Planned) Pharmacogenomic Data Submission (Planned) Population Pharmacokinetics (Planned) General Clinical Pharmacology Considerations for Pediatric Studies for Drugs and Biological Products (Planned) https://www.fda.gov/drugs/guidance-compliance-regulatory-information/guidances-drugs https://www.fda.gov/media/124386/download

Public Outreach and Engagement Leveraging Quantitative Methods and Modeling to Modernize Generic Drug Development and Review Drug Interactions with Hormonal Contraceptives: Public Health and Drug Development Implications Mechanistic Absorption Modeling and Simulations in Oral Bioequivalent Product Development Workshop Pediatric Trial Design and Modeling Workshop Webinar: Section 12 Labeling Guidance Pharmaceutical Science and Clinical Pharmacology Advisory Committee Meeting Extrapolation of Efficacy in Pediatrics Workshop Primary Pediatric Hypertension Workshop: Epidemiology and Treatment Gaps Brookings Meeting: Improving Productivity in Pharmaceutical Research and Development: The Role of Clinical Pharmacology and Experimental Medicine Email: OCP@fda.hhs.gov Subscribe to Clinical Pharmacology Corner (via Google Chrome) at https://updates.fda.gov/subscriptionmanagement

OCP & DARS Annual Reports Available Online https://www.fda.gov/about-fda/center-drug-evaluation-and-research/reports-budgets-cder

Collaboration Opportunities Academic Institutions Collaborative Agreements (e.g., MOU, CRADA) CDER Network of Experts (NoE) Program Academic Faculty Faculty Sabbatical/Scientific Visit Program Advisory Committees (AC)/Special Government Employee (SGE) Professional & Graduate Students Doctor of Pharmacy APPE Rotations Clinical Pharmacology Drug Labeling Student Summer Internships (Salaried) Professional and Graduate Students ORISE/Commissioner Fellows At the AACP Annual Meeting: FDA will be at Booth 212 Sunday, July 14, 2019 from 3:30 pm to 6:30 pm Monday, July 15, 2019 from 9:00 am to 1:30 pm OCP will have a networking session Monday, July 15, 2019, from 9:00 am to 10:00 am in Monroe Boardroom 1 MOU: https://go.usa.gov/xQxVa; NoE: https://go.usa.gov/xQxyu; AC: https://go.usa.gov/xQxVk; APPE: https://go.usa.gov/xQxV5; ORISE: https://go.usa.gov/xQxVN

Conclusion Take the first step today! Clinical pharmacology is well poised to continue to advance drug development and regulatory evaluation OCP recognizes it is a member of a community and values and fosters quality interactions There are opportunities to actively (e.g., MOU) or passively (e.g., Drugs@FDA information) interact and collaborate with OCP Take the first step today!

ACKNOWLEDGEMENTS: Kimberly Bergman, Eric Brodsky, Janelle Burnham, Shiew Mei Huang, Rajanikanth Madabushi, Michael Pacanowski, Sherbet Samuels, David Strauss, Mongthuong Tran, Ping Zhao (Gates Foundation), Issam Zineh.