SHORTENING TIMELINES AND IMPROVING EFFICIENCY IN DRUG DEVELOPMENT -Seamless drug development paradigms

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SHORTENING TIMELINES AND IMPROVING EFFICIENCY IN DRUG DEVELOPMENT -Seamless drug development paradigms Claudia Filozof, MD PhD Executive Medical Director Covance

Challenges in Clinical Development in NASH No regulatory Guidelines towards approval Limitations of preclinical models to replicate the disease in humans Long asymptomatic natural history: Time to hard endpoints is long No validated non-invasive biomarkers as surrogate endpoints Disease progression is bidirectional Limitations of liver biopsy as a surrogate marker Sampling variability Intra and Inter-subjects variability in interpretation

Clinically Meaningful Benefit Based on how a patient feels: symptoms quality of life Based on how a patient functions: functional status (impairment or improvement in ability to lead a normal active life) Based on patient morbidity and mortality: survival liver-related outcomes rates of hospitalization (resource utilization)

Surrogate Endpoints: Regulatory Perspective Generally Accepted Substantial body of literature available Quality of data is strong Surrogate should reflect: Mortality? Other clinical outcomes Surrogate should have: Content and face validity Sensitivity to change Reasonably Likely Less amount of data available Quality of data not as strong Surrogate should have: Reasonable likelihood of reflecting change in health status based on its relationship to biology of disease Sensitivity to change

Rationale for the use of Adaptive Design in NASH High unmet need for an approved therapy Number of patients with biopsy-confirmed NASH and/or willing to have multiple liver biopsies is very limited Disease progression and regression are not well understood It may take several years to progress to cirrhosis and generate clinical outcomes Currently accelerated/conditional approval involves a 2-step approach

Adaptive Design in NASH: Potential Advantages Provides an opportunity for prospective planning of modifications of one or more aspects of a study Adding or dropping treatment arms Re-estimating sample size Changes in the allocated proportion of subjects in one or more arms Allows evaluation of data collected from different stages for a combined analysis May help minimize the overall number of patients required during the entire drug development process Allows the same subjects to move from one phase to another, reducing the need to find additional subjects willing to undergo multiple biopsies May reduce the clinical development process/ overall time to reach marketing approval

Proof of Concept/Dose Ranging Adaptive Trial Design Population: Biopsy-confirmed NASH patients Randomize Additional Patients Population: Patients at high risk of NASH N=XX Dose 3 Utility function: overall analysis R N=XX Dose 2 N=XX Dose 1 Weeks Placebo = XX -4-2 0 12 24 36 48 60 72 Screening period Run-in Changes Interim Analysis in liver at fat Weeks and/or other 12 16 non 24 invasive Safety biomarkers stop criteria Futility/efficacy criteria based on non-invasive biomarkers Adaptations Weeks 48 52 72 Biopsy driven endpoints Utility function Filozof et al. Hepatology Communications 2017. In press

Phase 3/4 Adaptive Design Population: Biopsy confirmed NASH NAS 4 Fibrosis stage F2/F3 Phase 3 Randomize Additional Patients Phase 4 Stage 1 Phase 4 Stage 2 R Weeks N=XX N=XX Dose X Placebo -6 0 12 24 36 48 60 Event 72 Screening Period Efficacy Based on Histology Event Rate Driven: Long Term Lifestyle may Lead to Accelerated/ Confirmation 6+ year Composite Advice Conditional Approval Endpoint 1. Resolution of NASH without worsening of fibrosis 2. Reduction in fibrosis without worsening of NASH Filozof et al. Hepatology Communications 2017. In press Safety Evaluation Overall alpha: <0.05 Progression to cirrhosis (histology) Overall mortality and liver Clinical outcomes

Seamless Phase 2/3/4 Adaptive Study Design Drop off study arm(s)/ Randomize Additional Patients POC Phase 2 Phase 3 Phase 4 Dose 3 Utility function: overall analysis -------///////////- R Dose 2 Dose 1 OUTCOMES Weeks Placebo ------///////////- -6 0 16/24 48/52 96/104 Screening Period Lifestyle Advice First IA Week: Safety and futility criteria based on non-invasive biomarkers Second IA: Biopsy-driven endpoints ACCELERATED APPROVAL Event Driven app 6+ years Filozof et al. Hepatology Communications 2017. In press

Seamless Phase 2/3/4 Adaptive Study Design Sample size is often selected to power the study for detecting a meaningful treatment effect at the end of the phase 3. Limited power for critical decision making (e.g., for dose selection or dropping arms). A precision analysis is recommended to assure that the selected dose has achieved statistical significance The dose with highest confidence level for achieving statistical significance will be selected The doses with confidence levels for achieving statistical significance less than 75% will be dropped. A trend test (e.g. Cochran Amitage test) may be considered To protect the trial integrity due to the un-blinding of the interim data, a very small alpha (e.g., 0.0001) is recommended.

Adaptive Design in NASH: Potential Limitations Prevent potential operational biases that may arise during the evaluation of the interim data: Identification, minimization and control of sources of bias/variation; Overall type I error control rate at a pre-specified alpha level Maintain the quality, validity and integrity of data: outline roles and responsibilities of a data safety monitoring committee. Need for multiple liver biopsies and long term follow-up of phase 2/3/4 seamless trials may limit the number of patients who are willing to participate. The need for type 1 error control with a very small alpha increases the total number of patients to allow reasonable power.

Conclusions High unmet need of an approved therapy Seamless adaptive clinical designs may have several advantages: Reduce the overall number of patients and timelines without compromising the quality of the evidence needed to establish the efficacy and safety of therapeutic agents Flexibility for pre-planned adaptations The use of a utility function may allow all endpoints to be linked for the overall analysis But some limitations: Operational complexity Need to control of potential operational bias Need of multiple liver biopsy and long-term follow-up

Thank you