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Trends in Early Development


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PAREXEL Early Phase Clinical Research Services experts discuss developing trends in drug development including adaptive trials design, real-world data and biomarkers.

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Trends in Early Development

  1. 1. © 2018 PAREXEL INTERNATIONAL CORP. TRENDS IN EARLY DEVELOPMENT Dr. John Lambert Corporate Vice President and Chief Medical Officer, Early Phase Medical Sciences, PAREXEL International April 17, 2018 PAREXEL KOREA SYMPOSIUM 2018
  2. 2. © 2018 PAREXEL INTERNATIONAL CORP. / 2 AGENDA • Introduction • Innovative Trial Design • Use of Genomic and other Biomarkers in Clincal Trials – Oncology • Modelling and Simulation – Role and importance TRENDS IN EARLY DEVELOPMENT Source: Butler, Declan. Nature; (Jun 12, 2008): 840-842. FROM BENCH TO BEDSIDE
  4. 4. © 2018 PAREXEL INTERNATIONAL CORP. / 4 CLINICAL RESEARCH DATA - SOURCES Registries EHRs Claims data RCT • FDA - RWD/ RWE supports regulatory decision-making about drug safety; less frequently to establish drug effectiveness ; useful for the clinical devices • EMA – Use if RCT is not feasible (time, ethics, rarity); hard endpoints (to offset bias); conditions with known & predictable progression Source:
  5. 5. © 2018 PAREXEL INTERNATIONAL CORP. / 5 REAL WORLD DATA (RWD) AND REAL WORLD EVIDENCE (RWE) RWD: Data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources • Insurance claims/billing data • Electronic health records • National product/disease registry data • Patient-generated data including in home-use settings • Data from other sources inform on health status (e.g. mobile devices Uses • Creating formularies • Developing clinical practice guidelines and clinical decision support tools • Developing a product’s benefit- risk profile • Monitor post-market safety and adverse events • Generate additional hypotheses for continued clinical development *RWE *Clinical evidence from RWD re the use/ potential benefits or risks of a drug
  6. 6. © 2018 PAREXEL INTERNATIONAL CORP. / 6 Drug 1 Indication 1 • Single treatment • Single indication Drug 1 Indication 1 Indication 2 ….. Indication n • Single treatment • Multiple indications • Genomic information • Severity • Lines of therapy • Background Characteristics Drug 1 Drug 2 Indication 1 …. Drug n • Multiple treatments • Fixed # treatment arms or add/delete treatment arms • Single indication Drug 1 Indication 1 Drug 2 Indication 2 …. ….. Drug n Indication n • Multiple treatments • Fixed # treatment arms or add/delete treatment arms • Multiple indications • Fixed # indications or add/delete indications INNOVATION - CLINICAL TRIAL DESIGN OPTIONS Traditional Design Umbrella Design Basket Design Platform Design
  7. 7. © 2018 PAREXEL INTERNATIONAL CORP. / 7 WHAT IS AN ADAPTIVE TRIAL? Prospectively planned opportunity to revisit initial assumptions based on interim data – e.g. adapt design and/or sample size based on observed treatment effect differences or drop a dose arm that is ineffective Most Suited For Drugs If - 1. Rapid Biomarker/PD Readout 2. Multiple Therapeutic Indications 3. Established Dose Effect/Toxicity Relationships 4. Ethical Issues Of Traditional Designs TRADITIONAL DESIGN (CARGO) ADAPTIVE DESIGN (PASSENGER)
  8. 8. © 2018 PAREXEL INTERNATIONAL CORP. / 8 CURRENT USE OF ADAPTIVE TRIALS STAGE PHASE MARKET ADOPTION LEARN I and seamless I/II Already significant in the use of flexible combination protocols II seamless II/III • Probably more adoption in Phase II • Estimates of % adoption – ISR (2010): 20% – ISR (2015): 30% – Tufts (2013): 20% – ISR (2014): 22% • DIA adaptive design working group – 20% adoption – 40% sponsors examine adaptive as optionCONFIRM III POST-MARKETING IV Minimal current adoption, but significant growth opportunity
  9. 9. © 2018 PAREXEL INTERNATIONAL CORP. / 9 FIRST IN HUMAN COMBINED COMPLEX PROTOCOLS (SMALL MOLECULE - FLEXIBLE DESIGN) Single Dose 1 Single Dose 2 Single Dose 3 Single Dose 4 Multiple Dose 1 Multiple Dose 2 Single Dose n Min. Intoler. Dose Max. Toler. Dose Food Effect PK? yes Multiple Dose Elderly Safe Starting Dose (Human Equivalent Dose) NOAEL/PAD/MABEL DDI, Human Disease Model, Ethnicity ,others Multiple Dose 3
  10. 10. © 2018 PAREXEL INTERNATIONAL CORP. / 10 PAREXEL’S VISION AND APPROACH STATISTICAL DESIGN AND ANALYSIS STUDY EXECUTIONADAPTIVE EXECUTION ENVIRONMENT • Sample size adjustment based on interim effect size • Seamless Phase II/III designs All Functions understand and execute the needs of adaptive study designs • Project leadership • Clinical monitoring • Data management PAREXEL provides key technologies to support adaptive trials, integrating EDC, ePRO, IVR, supplies simulation and forecasting • Bayesian adaptive dose finding design • Two stage designs with adaptive sample size sequential methods
  12. 12. © 2018 PAREXEL INTERNATIONAL CORP. / 12 THREE PILLAR FRAMEWORK Source: Morgan P. Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival., Drug Discov Today. 2011 Dec. - PK analysis - Free drug exposure > pharmacological potency - In vivo PK/PD with PET receptor occupancy or radio ligands - Indirect - In vivo PK/PD with expression of Biomarkers - Indirect Framework to assess probability of successful translation PHASE II SURVIVAL Pillar 1 Exposure at the target site of action - PK analysis - Free drug exposure > pharmacological potency Pillar 2 Binding to the target site - In vivo PK/PD with PET receptor occupancy or radio ligands - Indirect Pillar 3 Expression of pharmacology - In vivo PK/PD with expression of Biomarkers - Indirect (e.g. human disease models) Ask the right questions at the right timeand quantitatively address them
  13. 13. © 2018 PAREXEL INTERNATIONAL CORP. / 13 THREE PILLARS OF SURVIVAL 44 Pfizer Phase II programs between 2005-09 Source: Morgan P. Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival., Drug Discov Today. 2011 Dec.
  14. 14. © 2018 PAREXEL INTERNATIONAL CORP. / 14 BIOMARKERS IN PHASE I STUDIES: Mechanistic • Protein expression • Phosphorylation of an enzyme • Occupation of a receptor = target engagement • Ex vivo functional assay (LPS on PMCs) Functional • Cardiac output • Forced expiratory volume in 1 sec (FEV1) • Heat pain thresholds (pain) • Cognitive performance (Cogstat™) Efficacy measures • Blood Pressure • Cholesterol • Glucose • Tumor imaging Toxicity • Liver function tests, liver enzymes • Proteinuria (and other excreted markers) • Qtc (cardiac repolarization parameter) A biomarker is a characteristic that is objectively measured as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention (NIH Biomarker Definition Working Group)
  15. 15. © 2018 PAREXEL INTERNATIONAL CORP. / 15 A NEW TREATMENT PARADIGM The molecular profile of an individual patient and their disease influences the effect of a medicine; biomarker diagnostics help to target the right medicine to the right patient Source: Adapted from Bayer Healthcare, “Personalized Medicine” (accessed May 2015)
  16. 16. © 2018 PAREXEL INTERNATIONAL CORP. / 16 BIOMARKERS & GENOMICS ENABLE DELIVERY OF PRECISION MEDICINE 1. Accessed 04 May 2017 2. Personalized Medicine Coalition. The Case for Personalized Medicine (eds. 1–4). 2008–2014; Personalized Medicine Coalition. Applications: Therapies. Accessed October 31, 2016 at 3. The support of human genetic evidence for approved drug indications. Nelson MR et al. Nature Genetics 2015; 47: 856-60 4.,%20Biomedtracker,%20Amplion%202016.pdf Nearly 1 in 4 of new drugs approved by the U.S. Food and Drug Administration (FDA) between 2014-16 were personalized or precision medicines1 Over the next five years, the proportion of personalized medicines in clinical development is expected to increase to nearly 70 percent2 In 2015, a Nature Genetics publication estimated that selecting genetically supported targets could double the success rate in clinical development3 63 28 55 83 8.4 76 46 76 94 25.9 0 20 40 60 80 100 Phase I to Phase II Phase II to Phase II Phase III to NDA/BLA NDA/BLA to Approval Phase I to Approval Without Bx With Bx Probability of Success With or Without Selection Biomarkers 3x
  17. 17. © 2018 PAREXEL INTERNATIONAL CORP. / 17 PHARMACOGENOMICS Source: Pharmacotherapy 2011; 31 (8): 729-735 Drug response in diverse populations
  18. 18. © 2018 PAREXEL INTERNATIONAL CORP. / 18 • Key cell types: Cancer, stromal and immune present in each patient's tumor ; over 100,000 tumor exomes sequenced • Should be possible to design a therapeutic strategy that improves outcomes in an individual patient • Functional Genomics laboratory tools/in vivo models used to assess: 1. Mechanisms of tumorigenesis 2. Mediators of drug resistance 3. Principles of cell signaling 4. Oncogenes and tumor suppressor 5. Somatic mutation affects on protein function PRECISION FUNCTIONAL GENOMICS IN CANCER CARE
  20. 20. © 2018 PAREXEL INTERNATIONAL CORP. / 20 PK/ PD MODELING AND SIMULATION • The ultimate goal is to utilize internal and external data in a quantitative manner to improve drug development strategy and decision-making • Providing the right information at the right time in the right format. Early buy-in from clinical and commercial to develop quantitative metrics by which a meaningful ‘go/no go’ decision • Reduce cost and time (e.g. use modeling instead of additional studies or treatment arms) • To facilitate dialogue with Regulatory agencies (Exposure Response or PK/PD modeling is more of an expectation these days) • Modelling of 1. Exposure (PK) to PD responses 2. Animal PK to human starting doses 3. Exposure to efficacy response 4. Exposure to toxicity/safety issues
  22. 22. © 2018 PAREXEL INTERNATIONAL CORP. / 22 WHAT IS MODELLING? • Fit model to all subjects individually and then calculate statistics (e.g. mean, SD etc.) • Combine all the data in one mathematical model (structural model) • Differences between individuals are described with random effects. • Covariates are implemented Traditional Approach (sequential process) Population Approach (fit simultaneously)
  23. 23. © 2018 PAREXEL INTERNATIONAL CORP. / 23 PK MODELING ACTIVITIES AND CAPABILITIES Non Compartmental analysis Allometry Pediatric PK Population PK Conc- ECG QT Analysis DDI models PK/PD Modeling Binary Analysis Complex Pop PK Survival Analysis Physiol/ Based/PK Meta Analysis Disease IVIVC CTS SP Population Pharmacokinetics Modeling using Sparse PK sampling and Population PK - becoming routine request by regulatory agencies Pediatric study plan (PSP or PIP) required by regulatory agency - Population PK modeling and simulation key component
  24. 24. © 2018 PAREXEL INTERNATIONAL CORP. / 24 CASE STUDIES: DE-RISKING QT EFFECTS Situation Potential QT prolongation liability evidence Action Early Phase studies were designed to support the development of Concentration-QT models. Based on the model and available PK data from historical studies, dose / effect simulations for multiple dosing regimens, administration routes and populations were analyzed to determine the effect of the drug on QT interval. Drug concentration (ng/mL) Modeling TQT study Simulating Dosing Regimens in the Drug Label Low dose High dose Result The magnitude of QT effects were predicted, impacting risk assessments for future clinical plans and allowing subsequent dosing regimens to be assessed against QT prolongation criteria.
  25. 25. © 2018 PAREXEL INTERNATIONAL CORP. / 25 REQUIREMENTS FOR PK/POPULATION PK MODELING Service Needs PAREXEL Experienced PK Modelers/ Scientists/Analysts Yes Biostatisticians Yes Therapeutic Experts Yes Clinical Pharmacologists Yes Clinical Study Capability - PAREXEL Phase I units (4) - Phase II and III Services Yes Regulatory Experts Yes