Shortening the Timeline for Developing New Treatments How the Rare Disease Cures Accelerator – Data and Analytics Platform (RDCA-DAP) Can Help For audio access call: 800-289-0462 passcode: 189526#
Agenda Opening Q&A Alexa Moore, NORD All Panelists Speakers Pamela Gavin, NORD Michelle Campbell, FDA/CDER Jane Larkindale, C-Path Robert Alexander, Takeda
Shortening the Timeline for Developing New Treatments – How the Rare Disease Cures Accelerator – Data and Analytics Platform (RDCA-DAP) Can Help Robert Alexander, MD Jane Larkindale, DPhil Michelle Campbell, PhD Pamela Gavin, MBA Vice President and Head, Global Executive Director, Rare Disease Chief Strategy Officer, Sr. Clinical Analyst, Stakeholder Clinical Science Neuroscience Cures Accelerator-Data and Analytics Engagement and Clinical Outcomes, National Organization for Rare Therapeutic Area Unit, Takeda Platform and Duchenne Regulatory Disorders Office of Neuroscience, FDA/CDER Pharmaceuticals International Co. Science Consortium, C-Path
Pamela Gavin, MBA Chief Strategy Officer, NORD
Orphan Drug Act (1983)
Orphan Drug Act Successes 48 Novel Drugs Approved by CDER in 2019 Orphan Non-orphan Nearly 44% were orphan products Number of approved orphan indications per year
Rare Disease Landscape Many rare diseases aren’t being studied.
Rare Challenges Expense/Limited Limited Small patient Standardization of Data ownership funding for the understanding of populations data and measures and sharing study of rare progression of spread over Challenges the Restricted diseases many rare diseases diverse ability to combine ownership geographic area Impacts scientific Over time and for and compare Multiple studies, discovery, the different people Challenges clinical Can shape quality, same condition development of trial design and Impacts drug utility, and expertise recruitment Split already small development interpretation of communities across interest, duration Harder to detect data multiple efforts of development, and understand (increasing burden design of clinical effects on participants) trials
RDCA-DAP Partners
Rare Disease Cures Accelerator Data and Analytics Platform The RDCA-DAP is a neutral, independent integrated database and analytics hub designed to be used in building novel tools to accelerate drug development across rare diseases. Allows access to the Better understanding Encourages Promotes data by researchers of a rare disease and standardization of sharing of (as permitted by its progression data collection patient level data contributor)
RDCA-DAP Benefits 360 ° view of disease characterization and natural history Accelerate understanding of conditions and commercial/research interest; inform the design of trials Encourage greater representativeness in study samples - steps toward more equitable and inclusive study designs Opportunity for cross-disease discovery Efficient, effective use of resources
Rare Disease Cures Accelerator- Data and Analytics Platform Michelle Campbell, PhD Sr. Clinical Analyst, Stakeholder Engagement and Clinical Outcomes Office of Neuroscience FDA/CDER
Context and Motivation • Regulators are working with rare disease patients, investigators, and companies, mostly one at a time, and most struggling with the same challenges: • Vast knowledge gaps about the natural course of the disease and small dispersed patient populations that make it hard to do the randomized clinical trials that save lives. • There is a need for a better solution.
Key activities presenting areas of challenge Discovery / Translational / Preclinical Clinical Development Characterization Getting Patient Clinical Study of New of Disease Perspectives on Treatments their Disease and • What is known about the • Is the investigational drug available in a disease? form that can be administered? Treatment • Are there well-defined lab tests — • Pre-clinical safety testing done to inform • What disease impacts to diagnose the disease? assessment of safety in humans? matter most to patients? • What is the natural history of the • A study design specified? • What is the landscape of disease? • A study protocol? currently available • What causes the disease treatments? • IRB review and approval? (pathogenesis)? • IND submitted for FDA review? • Plan for patient enrollment? • Patient access to the trial site? • Plan for study data collection?
Congress provided FDA an Opportunity in its Fiscal Year 2019 Appropriation Within the increases provided for a New Platform for Drug Development in FY 2019, Congress appropriated funding for Investment and Innovation for Rare Diseases CDER is investing funds in Innovation for Rare Diseases to launch work on “Rare Disease Cures Accelerator.”
Need for a “Rare Disease Cures Accelerator” • Adopting a cooperative research • Some key components include: approach to accelerate the move ◦ Centralized standardized infrastructure from bench to bedside for rare to support and accelerate rare disease disease cures. characterization • A “Rare Disease Cures Accelerator” ◦ Standard core sets of COAs measuring would provide the infrastructure impacts that matter most to patients, for a cooperative scientific ideally applicable to more than one approach to clinical trials readiness rare disease in rare diseases. ◦ Global rare disease clinical trials network
Centralized standardized infrastructure to support and accelerate rare disease characterization • There is a compelling need for: • A standardized rare disease natural ◦ Efficient comprehensive history study data platform is needed characterization of the natural to provide a sustainable approach history of a given rare disease ◦ This platform would provide a targeted for clinical development disease-neutral background data ◦ Characterization conducted framework for the conduct of rigorously with attention to standardized natural history established data quality standards, studies. in order to be most useful to ◦ Disease-specific needs would be clinical trial design and regulatory layered onto this framework to review provide a rapid means for standardized, yet customized, development of natural history studies for any given disease.
Rare Disease Cures Accelerator- Data and Analytics Platform The Rare Disease Cures Accelerator- Data and Analytics Platform (RDCA-DAP) is intended to serve as a neutral, independent data collaboration and analytics hub to promote the sharing of critically important data across rare diseases in order to accelerate the understanding of disease progression.
RDCA-DAP Critical Path Institute and NORD partnering on initiative
RDCA-DAP: Long-term goal for impact on drug development • Centralized and standardized • Analytics and simulation tools to help infrastructure to support and accelerate optimize your trial protocol for your rare disease characterization, allowing therapy development of more efficient and effective clinical • Ability to look at dynamics of change in trial protocols outcome measures and biomarkers in individual disease states and in related • Standardized data that can be extracted diseases and understand sources of in CDISC format for regulatory variation in rate of change. submissions • Ability to potentially find and match • Aggregated data will allow for a better historical or contemporary control understanding of the variance in disease patients to enrich your placebo arm and progression across broad range of reduce numbers of patients. patients aiding in development of optimized clinical trial protocols (endpoints, inclusion criteria, length and size of trial)
How do we add data to the RDCA-DAP, and what do we get out of it? Jane Larkindale, DPhil Executive Director, RDCA-DAP
Interacting with RDCA-DAP Where does data What do you do How can I see and come from? with the data? use the data? Clinical Trial Interface level I: RDCA-DAP DATA COLLABORATION CENTER Data Dashboard Registry Data C-Path Online Data Repository Natural History Data User Friendly, Interface level II: Genomic Secure Data Data interrogator Cloud Imaging and data Interface Data extraction Incoming Surveillance Integrated Data Data Data Data for Curation Interface level III: Standardization Vault Storage Analysis Preclinical Advanced Data analytics Other Novel Data
RDCA-DAP – Where does the data come from? • RDCA-DAP does not collect new data from patients or in new studies • RDCA-DAP seeks to get copies of data from existing sources: Clinical trial data [Baseline, Placebo arm and Drug arm all have value!] ◦ Natural history data ◦ Registries (patient-entered, clinical, etc.) ◦ Other sources ◦ • You cannot identify any individual in RDCA- DAP’s data • Data from multiple sources is integrated
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