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Preparing for a career in regulatory biostatistics What does it take ?
Robert T. O’Neill Ph.D.
Director, Office of Biostatistics Office of Translational Sciences, CDER For presentation at the 17th annual International Chinese Statistical Association Applied Statistics Symposium ; June 4-7th, 2008
Outline of Issues
What is regulatory statistics
Where do you learn
Opportunities
Training the next generation
The science of regulatory statistics
The field of regulatory statistics evolved from the need to apply statistical principles and practices to implement regulations developed to promote and protect the public health by facilitating the development of effective and safe medical products. The modern era began about 1970 Many statisticians have begun careers in FDA and moved to industry or academic positions where they built upon their regulatory statistics background There are about 105 biostatisticians in CDER, and about that many more in all of FDA, established programs in CBER, CDRH, CFSAN and CVM and NCTR
http://www.fda.gov/cder/Offices/Biostatistics/
What is the role of biostatistician in a regulatory agency and how did it evolve
The need for biostatisticians was created by the regulations and standards for efficacy and safety What shaped this role Culmination of accumulating experience The development and evolution of the discipline of regulatory statistics International roles, influences and events
Major Events Impacting Determination of Evidence
The 1962 Kefauver-Harris Amendments: the foundation for experimental evidence as the basis for drug approvals
The 1970 definition of ‘Adequate and well controlled investigations’: the foundation for statistical principles: the concept of hypothesis testing and estimation, randomization, blinding
The 1986 NDA Rewrite: the foundation for documentation of evidence, including statistical evidence and introduction of the integrated efficacy and safety section -
Major Events Impacting Determination of Evidence (cont.)
The 1988 Guideline for the Format and Content of the Clinical and Statistical Sections of an application
1992 ; Subpart H - Accelerated Approval of New Drugs for Serious or Life-threatening Illnesses - surrogate endpoints (AIDS crisis)
The 1997 Food and Drug Modernization Act (FDAMA); a modification of the substantial evidence criteria
The 1998 ICH Statistical Principles for Clinical Trials: the foundation for global understanding , harmonization and implementation of statistical principles
Roles in the career of a regulatory biostatistician
Statistical review team member
Entry level and senior reviewer Expert statistician
Applied researcher Leadership, manager , policy development
Office Director, Deputy
Division Director, Deputy Associate Director Other organizational roles
Bioinformatics, training, compliance, epidemiology
What does a regulatory statistician do ?
Evaluate , critique large numbers of clinical studies, with access to patient level data - data base management skills
Make recommendations inference and evidence Prepare and deliver public advisory committee presentations that are video taped, webcast Write reports that may be available publically through FOI Develop and Negotiate statistical and clinical guidances
Domestic and international (ICH)
Dispute resolutions Administrative hearings (rarely) Influence, educate colleagues Interactions with multiples audiences, including industry statisticians, consultants, and academics
An advisory committee biostatistician - a special government employee (SGE)
Usually an academic with minimum conflicts of interest Difficult job Requires unique skill mix Goes beyond understanding the science and the statistics Multi-disciplinary committee Voting is often the decision making choice
Training and Experience as a critical part of the career path in regulatory biostatistics
A reviewer of clinical and pre-clinical data within the context of scientific and regulatory standards of evidence A policy maker A decision maker A negotiator An educator A speaker A writer
Subject matter expertise
Impact of regulations and health care on mission of FDA Drug development
Pre-Clinical and clinical study design and analysis methodology Exploration / Confirmation
New proposals: adaptive, enrichment Surveillance and life cycle risk assessment
Epidemiology, observational study methods, causal inference, propensity score methods, multiple events Data mining strategies Meta-analytic methods - individual and study level covariates - not traditional literature based meta-analysis Data base management, programming, scientific computation Modern process control and quality by design methods for manufacturing- non invasive testing, development of standards and setting specifications (wastage and safety)
Statistical areas
Clinical trials – all aspects (read ICH E9)
Experimental designs for clinical trials
Repeated measures,Time to event, K period designs, Adaptive methods Methods development, application
All areas dealing with FDA guidances Pre-clinical animal study designs Chemistry , manufacturing, contols, specification setting and monitoring Simulation practices - modern protocol planning and scenario planning - not of a just a single study but a series of studies or a development program
Statistical areas
Epidemiology
Observational data methods Cohort and case control studies Large data base and outcomes based study methods Meta-analytic methods or combining Multiplicity - outcomes, subgroups - very important for inferential claims Prediction, prognosis, differential benefit and harm - important for understanding the difference between individual and group prediction and ‘personalized medicine’ Sampling, surveys Exploratory – bayesian , frequentist and likelihood strategies
Some Training that FDA provides to our staff
Statistical courses/ seminars/ workshop
Subject matter courses/ seminars/
Genomics, nanotechnology, drug safety evaluation,
Speaking, enunciation, toastmasters, negotiating
Designing Quality into Clinical Trials
Biostatistics and Statistics Broadening the field of application
Quality by design - modern quality control - in process control and specification setting and monitoring - designing quality into the design space
The manufacturing process - heparin
The clinical trial Sampling - clinical trial auditing and inspections - consumer surveys and OTC label comprehension studies Micro-array , SNP, genomics marker identification and validation studies Study design and analysis to support choice of and validation of patient reported outcomes in clinical trials Scientific computing, large scale data base analysis and data mining, record linkage studies, health records analysis
FDA Statisticians Collaborate with and are professionally involved in external activities
Professional society involvement
Organizing meetings externally - with Phrma, ASA, DIA, SCT, ISCA, IBS
Training the next generation Education and training vs experience in the career path
Experience , case studies, breadth of involvement Interest in continual learning vs. comfort zone
Academic contributions need to be aligned with needs of society and reality of modern health care FDA providing case study material to the academic sector
Fellowships
We are looking for a few good statisticians