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June 28, 2007
Adaptive Clinical Trials: Improving the Efficacy of Dose Finding Trials
- Dr. Jose Pinheiro, Director Biostatistics, Senior Modeler, Pharmacology Modeling and Simulation, Novartis PharmaceuticalLearn More

Adaptive Dose-Ranging Studies: an Evaluation with Recommendations from the PhRMA Working Group

Based on recent failures of some clinical trials, the FDA and pharmaceutical industry are trying to establish and promote adaptive clinical trials designs. The idea of this new initiative is based on the ability to use collected data to make modifications and decisions to that trial. That should help to optimize collected data and improve the chances of positive results or stop the study if it appears unsuccessful.

The pharma industry considers adaptive designs in dose ranging. New models help to improve the efficacy of a clinical trial by refocusing patient’s attention to the dosage or eliminating the dosage that causes numerous side effects.

Poor dose selection resulting from incorrect or incomplete knowledge of dose response relationship is one of the root causes of high attrition rates currently observed in Phase III trials. Adaptive dose-ranging studies are innovative designs aimed at striking a balance between needed dose response information and increased costs and timelines. PhRMA has formed a working group (WG) to evaluate and propose recommendations on the practical use of these in clinical
development. As part of the work of this WG, different adaptive and non-adaptive dose-ranging methodologies were evaluated under a variety of practical trial scenarios, through a comprehensive simulation study.

Join Dr. Jose Pinheiro as he shares Novartis’ experiences in designing adaptive dose trials as well as the PhRMA working group on Adaptive Dose ranging Studies’ recommendations on how to improve the efficacy of dose finding trials.

VPs, Directors, Heads, and Managers of:
  • Quantitative Clinical Pharmacology
  • Strategic Modeling and Simulation
  • Statistical Science
  • Biostatistics
  • Pharmacology Modeling and Simulation

Dr. Jose Pinheiro, Director Biostatistics, Senior Modeler, Pharmacology Modeling and Simulation, Novartis Pharmaceutical

José Pinheiro received his Ph.D. in Statistics from the Department of Statistics at the University of Wisconsin -- Madison in 1994, with a dissertation on theory, methods and software for linear and nonlinear mixed-effects models. Afterwards, he worked for two years in the Department of Biostatistics at the same university, being involved in the design and analysis of clinical trials, as well as in research in the area of group sequential designs, in collaboration with Prof. David DeMets. In 1996 he joined the Statistics Research department at Bell Labs, as a Member of Technical Staff. During his five years at Bell Labs, he developed methods and algorithms for telecom applications which resulted in several company patents, while continuing his research in methods and software for mixed-effects models.

José moved to Novartis Pharmaceuticals in 2001, joining the Methodology group in the Biostatistics & Statistical Reporting department, and currently heads the group in the U.S. At Novartis, he has been involved in methodological development and consulting activities in various areas of biostatistics applied to drug development, including dose-finding trials, proof-of-concept studies, pharmacokinetics and pharmacodynamics models, randomization schemes, and longitudinal data analysis. For his contributions to the company, he received a Novartis Leading Scientist Award in 2006.

José is co-leader of the PhRMA working group on Adaptive Dose-Ranging Designs and a member of the PhRMA WG on Novel Adaptive Designs. He is a member of the Biostatistics and Data Management Technical Group at PhRMA, and the secretary of ENAR. José is a co-developer, with Prof. Douglas Bates, of the NLME software in S-PLUS and R for fitting and analyzing linear and non-linear mixed-effects models. They have also co-authored the book "Mixed-Effects Models in S and S-PLUS", published by Springer-Verlag in 2000, a standard reference in the area.

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