Guideline E4 from the International Conference on Harmonisation (ICH) describes the importance of fully characterizing the dose-response of novel therapies submitted for regulatory approval. Knowledge of the dose-response curve determines the suitable dosing range where patients can expect to receive clinical benefit, without experiencing excessive adverse experiences. This understanding of dose-response can lead to further study and marketing of a limited set of doses expected to be safe and effective for a majority of patients, while providing some evidence for successfully tailoring doses according to the response of an individual patient. In this tutorial, we review design and analysis considerations for the study of dose-response, including identifying the maximum tolerated dose (MTD) through several variations of the continual reassessment method; determining the dose range, spacing and number of doses for further study; characterizing the dose range through Frequentist or Bayesian application of Emax models; and exploring additional candidate dose-response models and the possible averaging of those models through MCP-Mod methodologies. Some examples will be shared using SAS with clinical trial data from diverse therapeutic areas.
Richard C. Zink is Principal Research Statistician Developer in the JMP Life Sciences division at SAS Institute, following eight years in the pharmaceutical industry. He is Statistics Section Editor for Therapeutic Innovation & Regulatory Science, and Publications Officer for the Biopharmaceutical Section of the American Statistical Association. Richard holds a Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill, where he serves as an adjunct faculty member. He is author of Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS and co-editor of Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods.
Dr. Sandeep Menon is currently the Vice President and Head of Statistical Research and Consulting Center at Pfizer Inc. and also holds Adjunct faculty positions at Boston University and Tufts University School of Medicine. His group located at different Pfizer sites globally provides scientific and statistical leadership and provides consultation to the Global Head of Statistics, senior Pfizer management in Discovery, Clinical Development, Legal, Commercial and Marketing. His responsibilities also include providing a strong presence for Pfizer in regulatory and professional circles to influence content of regulatory guidelines and their interpretation in practice. Previously he held positions of increased responsibility and leadership where he was in charge of all the biostatistics activities for the entire portfolio in his unit, spanning from discovery (target) through proof-of-concept studies for supporting immunology and autoimmune disease, inflammation and remodeling, rare diseases, cardiovascular and metabolism, and center of therapeutic innovation. He was responsible for overseeing biostatistical aspects of more than 40 clinical trials, over 25 compounds, and 20 indications. He is a core member of the Pfizer Global Clinical Triad (Biostatistics, Clinical and Clinical Pharmacology) Leadership team. He has been in the industry for over a decade and prior to joining Pfizer he worked at Biogen Idec and Aptiv Solutions.
Sandeep is passionate about teaching and has been teaching part-time over a decade. He has taught introductory, intermediate and advanced courses in biostatistics including adaptive designs in clinical trials. He has taught short courses internationally and is a regular invited speaker and panelist in academic, FDA/Industry forums and Business management schools.
His research interests are in adaptive designs and personalized medicine. He has several publications in top tier journals and recently co-authored and co-edited books titled “Clinical and Statistical Considerations in Personalized Medicine” and “Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods”. He is an active member of the Biopharmaceutical Section of the American Statistical Association (ASA), serving as associate editor of ASA journal - Statistics in Biopharmaceutical Research (SBR), and as a core member of the ASA Samuel S. Wilks Memorial Medal Committee. He is the co-chair of sub-team under the cross Industry DIA-sponsored Adaptive Design Scientific Working Group (ADSWG) on the “Role of Adaptive Designs in Personalized Medicine”, member of biomarker identification sub team formed under the currently existing multiplicity working group sponsored by the Society for Clinical trials and an invited program committee member at Biopharmaceutical Applied Statistics Symposium (BASS). He is in the Editorial Board for Journal of Medical Statistics and Informatics and in the advisory board for the MS in Biostatistics program at Boston University.
Sandeep received his Medical degree from the University of Bangalore (formerly Karnataka University), India and later completed his Masters and PhD in Biostatistics at Boston University and was a research fellow at Harvard Clinical Research Institute. He has received several awards for academic and research excellence.