Joan Buenconsejo, FDA, and Brenda Crowe, Eli Lilly and Company
This three-day workshop is one of a series of annual meetings that has been sponsored by the ASA Biopharmaceutical Section in cooperation with the U.S. Food and Drug Administration’s (FDA) Statistical Association since 1996. Held each September in Washington, DC, short courses are scheduled on the first day, followed by two days of sessions on the science and statistics associated with the development of new medical products (e.g., pharmaceuticals, biologics, and devices). The workshop has been popular since its inception because it provides a unique opportunity to bring together statisticians from industry, academia, and the FDA for an open dialogue about issues of mutual interest.
Following is an overview of the workshop topics. Visit the workshop website for the complete online program and registration details.
Short Courses (September 19)
Statistical Issues in Drug Development
Group Sequential and Adaptive Clinical Trial Design
Study Design for Biomarker Development and Validation
Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies
Key Multiplicity Problems in Clinical Trials
Bayesian Adaptive Methods for Clinical Trials
Session Topics (September 20–21)
Key multiplicity issues in clinical drug development
Personalized medicine: separating the hope from the hype
Current issues in the design and analysis of noninferiority trials
Early-phase study designs in oncology
Statistical issues in medical device trials
Decisionmaking and safety in clinical trials – graphs make a difference
Suicidal ideation and behavior in clinical trials: points of interest and statistical challenges for industry and regulators
Biomarker implements for advancing stratified medicine: statistical considerations for R&D and regulatory approval
Confounding issues: how to interpret and how to avoid
New paradigms for statistical support in R&D
Primary endpoint in oncology trials – OS or PFS
Issues and correlates of protection in vaccine development
The new topology of safety: program safety analysis plan and safety reporting rules
Addressing bias in the evaluation of diagnostics
Finding meaningful links between CMC quality attributes and clinical outcomes in QBD framework
Cognitive and surrogate biomarkers endpoints in clinical trials of early Alzheimer’s disease
Bayesian analysis in the context of small clinical trials
Statistical challenges encountered in assessing immunogenicity data from vaccine trials
Propensity score analysis and observational studies
Making QBD work (small molecules focus)
Exposure-response modeling to facilitate future study designs of drug development programs
Regulatory impact and issues of joint modeling of longitudinal and time-to-event
Challenges of using meta-analyses in drug safety and other evaluations
Challenges and opportunities for designing and analyzing cancer vaccine/immunotherapy clinical trials
Making QBD work (large molecules focus)
Recent developments in adaptive design methodology
Sensitivity analyses of incomplete longitudinal clinical trial data
Challenges in subgroup analyses in multi-regional clinical development
Statistical considerations for assessing biosimilarity and interchangeability of follow-on biologics
Problems associated with unbalanced center enrollment
Implementation and conduct of adaptive trials
Discussion of the 2010 National Research Council’s recommendations for the prevention and treatment of missing data in clinical trials
Statistical methods in nonclinical data analysis
Benefit-risk: case studies and panel discussion
Multi-regional trials with different endpoint requirements by region
Evolving role of data monitoring committees in the 21st century
Patient-centered outcomes research and health economics outcomes research
Members of the organizing committee look forward to seeing you in September. Conference attendance will be limited to 750 participants, so be sure to register early.
The Prevention and Treatment of Missing Data in Clinical Trials
November 1–2, 2011
Renaissance Woodbridge Hotel, Iseline, New JerseyThe U.S. Food and Drug Administration (FDA) recently commissioned the National Research Council of the National Academy of Sciences to prepare “a report with recommendations that would be useful for FDA’s development of a guidance for clinical trials on appropriate study designs and follow-up methods to reduce missing data and appropriate statistical methods to address missing data for analysis of results.” After creating the Panel on Handling of Missing Data in Clinical Trials, the National Research Council issued the report The Prevention and Treatment of Missing Data in Clinical Trials in December of 2010.
This two-day short course, developed by five of the panel members, will provide in-depth coverage of the content of the report. The presentations will be infused by newly developed case studies, which will demonstrate the latest thinking on the design and analysis of randomized studies threatened by biases caused by missing data. Tom Permutt and Bob O’Neil from the FDA will round out the list of presenters to provide a regulatory perspective.
The course is targeted toward data analysts, statisticians, and other quantitative scientists involved in the design, analysis, and reporting of results of clinical trials of devices or treatments subject to regulatory review.
Visit the course website to register or view travel/hotel information and a preliminary agenda. Contact Ashley Gilliam (agilliam@jhsph.edu) with administrative questions and Daniel Scharfstein (dscharf@jhsph.edu) for specific questions about the course.
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