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Preparing for a career in regulatory biostatistics - What does it take ?

Learn about the role of a biostatistician in a regulatory agency and the skills required for a successful career in the field. Explore the evolution of regulatory statistics and the major events that have shaped the discipline. Discover the various roles and responsibilities of a regulatory biostatistician, from statistical review team member to leadership positions. Gain insights into training, experience, and subject matter expertise necessary for a career in regulatory biostatistics.

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Preparing for a career in regulatory biostatistics - What does it take ?

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  1. 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

  2. Outline of Issues • What is regulatory statistics • Where do you learn • Opportunities • Training the next generation

  3. 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

  4. http://www.fda.gov/cder/Offices/Biostatistics/

  5. 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

  6. 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 -

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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)

  13. 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

  14. 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

  15. 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

  16. Designing Quality into Clinical Trials

  17. Biostatistics and StatisticsBroadening 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

  18. FDA Statisticians Collaborate with and are professionally involved in external activities • Professional society involvement • Organizing meetings externally - with Phrma, ASA, DIA, SCT, ISCA, IBS

  19. Training the next generationEducation 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

  20. We are looking for a few good statisticians

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