Leveraging Data Sharing

Klaus Romero MD MS FCPDirector of Clinical Pharmacology

Critical Path Institute

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C-Path & FDA MOUOctober 14, 2005

“purpose… to establish an overarching framework for collaboration… to foster development of new evaluation tools to inform medical product development”

C-Path Consortium Model

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FDAEMA

Patients

NIH

Academia

AA

BC

D

E

Precompetitive Neutral ground

Multiple Companies

Formal Legal

Agreement

Critical Path Institute (C-Path) has developed a consortium structure that provides a unique neutral, precompetitive environment to increase collaborative efforts for drug development

C-Path Collaborators

Creating Consensus

Six global consortia collaborating with 1,000+ scientists and 41 companies

Informal discussion with FDA/EMA.

Sponsor submits a letter of intent requesting formal qualification. FDA/EMA Review Team formed.

Sponsor submits briefing document.

F2F meeting between sponsor and FDA/EMA Review Team. Review Team may request additional information.

Sponsor submits full data package. Review process within FDA/EMA begins.

Consultation and

Advise Process

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Regulatory decision qualifying or endorsing the submitted tools

Success!!!

Regulatory Review Process: What’s success?

What Was Learned?ADAS-Cog Variability

Sponsor 1 Sponsor 2 Sponsor 3 Sponsor 4 Sponsor 5 Sponsor 6 Sponsor 7

Item 1 Word Recall Word Recall Word Recall Word Recall Word Recall Word Recall Word Recall

Item 2 Commands Name Obj/fing. Name Obj/fing. Commands Name Obj/fing. Name Obj/fing. Name Obj/fing.

Item 3 Constr. Praxis Delayed recall Commands Constr. Praxis Commands Commands Commands

Item 4 Delayed recall Commands Constr. Praxis Delayed recall Delayed recall Constr. Praxis Constr. Praxis

Item 5Naming Obj/fing. Constr. Praxis Idea Praxis Name Obj/fing. Constr. Praxis Idea. Praxis Idea. Praxis

Item 6 Idea. Praxis Idea Praxis Orientation Idea. Praxis Idea. Praxis Orientation Orientation

Item 7 Orientation Orientation Word Recog Orientation Orientation Word Recog Word Recog

Item 8 Word Recog. Word Recog. Remem. Instr. Word Recog Word Recog Remem. Instr.Spoken Lang Abil.

Item 9 Remem Instr. Remem Instr.Spoken Lang. Abil. Remem. Instr. Remem. Instr.

Spoken Lang. Abil. Comprehension

Item 10 ComprehensionSpoken Lang. Abil.

Word Finding Dif.

Spoken Lang Abil.

Spoken Lang Abil. Word Finding Dif. Word Finding Dif.

Item 11Word Finding Dif.

Word Finding Dif. Comprehension

Diff. Spont. Speech

Word Finding Dif. Comprehension Remem. Instr.

Item 12Spoken Lang. Abil. Comprehension Concentration Comprehension Comprehension Concentration

Item 13 Number cancel. Concentration Concentration Concentration

Benefits of Data Standards

• SDTM clinical data standard used / preferredwithin FDA – standards required in PDUFA V

• Enable data sharing between organizations

• Enable aggregation and querying of data

• When implemented from the start, can lower costs of acquiring and analyzing data

CDISC Standards

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CDISC and C-Path

C-Path Mission:

To improve human health and well-being by developing new technologies and methods to accelerate the development and review of medical products

CDISC Mission:

To develop and support global, platform independent ‐data standards that enable information system interoperability to improve medical research and related areas of healthcare

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C-Path and CDISC Collaborations

C-Path – FDA Qualification

Collaborations

CAMD – Alzheimer’sCAMD – Parkinson’sPKD – Polycystic Kidney DiseasePSTC – Safety TestingCPTR – Tuberculosis

CDISC – Data Standards

C-Path Data Repository

C-Path and CDISC announce formal release of data standard for Alzheimer’s Disease

~6000 Patients

• Seven companies remapped and pooled data from 21 trials for ~6000 patients: value = $400 Million

• Database open to >200 qualified research teams in 35 countries

C-Path’s Data Repository for Alzheimer’s Disease

CODR – integrated CDISC data model

C-Path Online Data Repository (CODR)

CODR is a relational database with a data model designed around the CDISC SDTM clinical data standard

CDISC domains and variables are integrated into the database architecture

Common framework for easy generation of new data repositories based on applicable CDISC domains

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CAMD Process Overview

WG1Data

WG 2Modeling

and Simulation

WG 3Biomarkers &

Imaging

Models Biomarkers

Regulatory Review,Qualification, Acceptance

WG 4Health Authorities

Submission

Consensus

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Quantitative Disease-Drug-Trial Models

DiseaseModel

Drug Model

TrialModel

Biology Natural Progression Placebo Biomarker-Outcome

Pharmacology Effectiveness Safety

Early-Late Preclinical-Healthy-Patient

Patient Population Drop-out Compliance

FDA Data

DiverseExpertise

Physiology

Disease-drug-trial models are mathematical representations of the time course of biomarker-clinical outcomes, placebo effects, drug’s pharmacologic effects and trial execution characteristics for both the desired and undesired responses, and across experiments.

Janet Woodcock

Clinical Trial Simulations Based on the Model helpinform the Development process for New Drugs

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If symptomatic only: If symptomatic + Disease modifying

78-week Parallel Study Design versus 91 Week Delayed Start Design by Varying Disease Modifying Effects

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When Given a Regulatory Decision, Sponsors will be able to more Confidently use the Tool and the Review Process for New Drugs will be Streamlined

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CAMD Regulatory Path for AD Disease-Drug-Trial Model

MAY 2012

Team responding to Agency questions

C-Path Project Pipeline

FDA EMA

PMDACAMDDisease or Target Drug Development Tool

Feasibility1 Scoping2 Research3 Submitted4 Qualified5

Alzheimer's disease (AD)

Imaging Biomarkers

CSF Biomarkers

Disease model of mild and moderate AD

Disease model of Mild Cognitive Impairment

Parkinson's disease (PD)

PD imaging biomarkers

C-Path and CDISC announce formal release of data standard for Alzheimer’s Disease

C-Path Project Pipeline

FDA EMA

PMDACPTRDisease or Target Drug Development Tool

Feasibility1 Scoping2 Research3 Submitted4 Qualified5

Tuberculosis

Liquid cultures

TB quantitative disease progression model

Hollow Fiber System

Clinical Trial Inventory

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TB M&S inventory

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Approaches from other areas

Predator-Prey models in HCV may provide useful insights for TB modeling and simulation.

Guedj J. et al. Understanding HCV dynamics with direct-acting antiviral agents due to interplay between intracellular replication and cellular infection dynamics. J Theor Bio 2010;267:330-40

What about HCV?

C-Path firsts

Are industry and regulators interested?

Which DDTs are a priority?

What is the current status of data standardization?

Which are the relevant potential data sources?

How can we collaborate?