Evaluating Probability of Success for
Internal Decision Making in Drug
Development
Narinder Nangia, Ph.D.
Martin King, Ph.D.
Jane Qian, Ph.D.
Speakers
Narinder Nangia, Ph.D. has over 15 years experience as a statistician in the
pharmaceutical industry, in both learning and confirming stages of drug
development across several therapeutic areas including Pain, Inflammation, CNS
and Oncology. For the last few years, he has been advocating the use of Bayesian
approaches for decision-making in early drug development.
Martin King, Ph.D. has over 10 years experience as a statistician in the
pharmaceutical industry, including both early- and late-stage clinical development
(Phase 2-4) in the Antiviral, Oncology, and Dyslipidemia areas. He has presented
on the probability of phase 3 success to statistical and non-statistical audiences.
Jane Qian, Ph.D. has over 13 years experience as a statistician in the
pharmaceutical industry, including both early- and late-stage clinical development
(Phase 1-4) in Cardiovascular and Metabolic, Oncology, Arthritis and Pain, Antiinfective and Antiviral, CNS and Women's health areas. She has been advocating
the use of predictive probabilities for early drug development in Oncology.
Evaluating probability of success in drug development
JSM, 4 August 2008
© 2008 Abbott
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Course Prerequisite
This course is designed for statisticians working in the pharmaceutical or
biotechnology industries. Some familiarity with clinical trials and the drug
development process is desirable.
Participants should have a basic familiarity with hypothesis testing and
statistical inference (any first-semester graduate course) and with Bayesian
statistics (e.g., Berry DA. Nat Rev Drug Discov. 2006;5:27-36)
Evaluating probability of success in drug development
JSM, 4 August 2008
© 2008 Abbott
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Clinical Trial Simulation – An Example
Priors and Simulated Posteriors
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Case: EWR (Control) = 21% (N = 1200), EWR (Test) = 26% (N = 200),
SS = 1125/arm, NCTS = 100
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Control
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Evaluating probability of success in drug development
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