Clinical Trial Designs for Personalized Therapy
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Friday, September 21
7:30-8:15 am Morning Coffee or Sponsored Breakfast Presentation (Opportunity Available)
Contact Ilana Quigley at firstname.lastname@example.org or 781-972-5457
8:30-8:35 Chairperson’s Opening Remarks
8:35-9:00 Accelerating and Personalizing Clinical Trials with Biomarkers and Adaptive Design, the I-SPY 2 Example
Sonia Pearson-White, Ph.D., Scientific Program Manager, Oncology, The Biomarkers Consortium, Foundation for the National Institutes of Health
I-SPY 2 is a unique clinical trial managed as a public/private partnership by the Foundation for the NIH (FNIH) Biomarkers Consortium. I-SPY 2 employs an innovative adaptive trial design in high risk breast cancers in the neoadjuvant setting, and will advance the understanding of which drugs work best with tumor types with different biomarker profiles, and the drive toward personalized medicine. The trial includes 20 major cancer research centers across the United States, and is part of an accelerated approval strategy under development at the FDA.
9:00-9:25 Predictive Markers and Innovative Oncology Clinical Trials in Early Development: Opportunities and Challenges
James Song, Ph.D., Senior Statistical Scientist, Global Biostatistics, Genentech
There has been a paradigm shift in oncology research. Molecules are now targeted therapies with wider therapeutic index and derived from molecular biology discoveries. Furthermore, integration of molecular diagnostics with targeted therapies for integrated cancer care will be the key in the future. Thus the importance of identifying predictive markers early has been well recognized. In this presentation we will review opportunities and some of the key challenges in identifying and evaluating predictive markers in Phase I and Phase II oncology trials. Innovative designs, in particular adaptive designs, could play a significant role in such development programs. We will review a few examples of such designs from oncology trials.
9:25-9:50 Clinical Validation of Predictive Biomarkers and Next-Generation Personalized Medicine Treatment Strategies Incorporating Genetic Dynamics
Robert A. Beckman, M.D., External Faculty, Center for Evolution and Cancer, Helen Diller Family Cancer Center, University of California at San Francisco; Executive Director, Clinical Development Oncology, Daiichi Sankyo Pharma Development
The future of oncology drug development lies in personalized therapy using predictive biomarkers. However, examples of the failure of predictive biomarkers also exist. In these cases the use of biomarkers increased the costs, complexity and duration of clinical trials, and narrowed the treated population unnecessarily. Here, we present methods to adaptively integrate predictive biomarkers into clinical programs in a data-driven manner, wherein these biomarkers are emphasized in exact proportion to the evidence supporting their clinical predictive value. Next-generation personalized treatment strategies, which emphasize tumor heterogeneity, evolutionary dynamics and possible future tumor states, will also be presented.
9:50-10:15 Clinical Trial Designs for Testing Biomarker-Based Personalized Therapies
Mei-Chiung Shih, Ph.D., Senior Biostatistician, VA Palo Alto Cooperative Studies Program Coordinating Center; Assistant Professor, Health Research and Policy, Stanford University
Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization and futility stopping proposed in the recent literature.
10:15-11:15 Coffee Break in the Exhibit Hall with Poster Viewing
11:15-11:20 Chairperson’s Opening Remarks
11:20-11:45 Challenge in the Design of Clinical Studies in Rare Diseases and Personalized Medicine
Federico Goodsaid, Ph.D., Vice President, Strategic Regulatory Intelligence, Vertex Pharmaceuticals
The number of patients available for clinical studies in therapeutic product development for rare diseases is small. This problem is also shared across any personalized healthcare product development targeting patient populations defined by rare mutations. Strong therapeutic effects may provide conventional study design alternatives, but more modest therapeutic effects may not be successfully tested with these study designs. Alternative designs to address this problem will be discussed, together with examples showing the advantages and disadvantages of these designs.
11:45-12:10 Doing Things a Little Bit Differently: The Good, the Bad and the Surprising
Daniel P. Rossignol, Ph.D., Executive Director, Taisho Pharmaceutical Research & Development
Getting a drug safely and quickly to an approved NDA is not easy. Getting a first-in-class drug quickly and safely through clinical trials is almost impossible. As an example of the lessons learned I will discuss the development of eritoran, a drug targeted for treatment of severe sepsis. Biomarkers developed from preclinical research drove Phase I studies of eritoran to test dosing, safety and PK, and at the same time allowed us to determine the PD activity of drug both ex vivo and in vivo. Analysis of risk/benefit and development of a dosing regimen were performed using clear, mechanism-driven analyses of drug dose-response. These studies also generated surprising results (e.g., Just how many compartments are there in blood?). Thus, while generation of surprising results can clarify a development pathway and even save a drug from the “ineffective” heap, effective incorporation of these results into the development plan can slow down the program. Thus scientifically-thorough development of a first in class drug should have additional time built into the timelines to allow for resolution of unexpected issues.
12:10-12:35 Decentralizing Trial Endpoints — Can We Bring Assays to Patients, Instead of Patients to Assays?
Aaron Nelson, M.D., Ph.D., Senior investigator II, Translational Sciences, Novartis Institutes for Biomedical Research
Novel technologies are increasingly available for remote physiological and biochemical measurements. The emergence of such technology is driven by healthcare and “quantified self” markets, and made possible by advances in microelectronics and biosensors. Remote patient monitoring technologies permit “decentralization” of trial endpoints, reducing reliance on central sites and increasing “real world” data. Such approaches may ultimately confer logistical and scientific benefits to sponsors, and increase convenience and benefit for subjects.
12:35 Close of Conference
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