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Meet the Speakers:
Innovations in Bayesian Trials

This dynamic program will cover a range of topics presented by Bayesian experts in academia, regulatory and industry.

Click here to register and learn more!

Simon Wandel, PhD
Novartis Pharma AG, Basel

Simon Wandel holds a master in Statistics and a PhD in Medical Statistics/Epidemiology from University of Bern. In 2010, he joined Novartis as statistician. In 2013, he co-founded a start-up specialized for Bayesian statistics (Cogitars GmbH), before rejoining Novartis as Expert Statistical Methodologist in 2014. He is currently working as a Director Biostatistics in Novartis’ Cardio-Renal-Metabolic Development Unit. He has a particular interest and substantial experience in application of Bayesian statistics for clinical trials.

 

Beat Neuenschwander, PhD
Novartis Pharma AG, Basel

Beat Neuenschwander got his PhD in Statistics in 1991 from the University of Bern, Switzerland. He then worked as a statistical consultant and analyst for the Institute of Social and Preventive Medicine, University of Berne, and the Swiss Federal Office of Public Health. In 2001, Beat joined Novartis Pharmaceuticals where he has been working in modeling & simulation and statistical methodology. Beat has been applying Bayesian statistics for 25 years, with a focus on the design of Phase I and Phase II trials, evidence synthesis, predictive inference, subgroup analysis, and the derivation of prior distributions from co-data.

 

Greg Campbell
PhD, President, GCStat Consulting

greg campbellIn the United States Bayesian statistics has been used in regulatory submissions to the Food and Drug Administration (FDA) for confirmatory clinical trials medical devices for more than fifteen years. The Bayesian history and accomplishments for medical devices will be reviewed. Attention is then turned to the status and opportunities of Bayesian statistics for pharmaceutical drugs and biologicals. There are harbingers of change in the wind and these will be reviewed. Finally the challenges and the future of Bayesian statistics in the regulatory environment will be tackled.

 

Yuan Ji
Professor of Biostatistics, Department of Public Health Sciences, The University of Chicago

Yuan

Dr. Yuan Ji is Professor of Biostatistics at The University of Chicago. He is an NIH-funded PI focusing on innovative computational and statistical methods for translational cancer research. Dr. Ji is author of over 140 publications in peer-reviewed journals, conference papers, book chapters, and abstracts, including Nature, Nature Methods, JCO, JNCI, JASA, and Biometrics, across medical and statistical journals. He is the inventor of many innovative Bayesian adaptive designs such as the mTPI and i3+3 designs, which have been widely applied in dose-finding clinical trials worldwide, including trials published on Lancet Oncology, JAMA oncology and JCO. He is an elected fellow of the American Statistical Association.

Nicky Best
Head, Advanced Biostatistics and Data Analytics Centre of Excellence, GSK

Nicky Best is Head of Advanced Biostatistics and Data Analytics at GlaxoSmithKline (GSK), where she leads a team of UK- and US-based statisticians who help drive methodological innovation to enhance the efficiency of clinical trial design, analysis and decision-making strategies. In 2015, Nicky was awarded the RSS/PSI award for Statistical Excellence in the Pharmaceutical Industry for her role in implementing prior elicitation and statistical assurance to improve decision making in clinical development. In 2018 she received the RSS Bradford Hill Medal for her work on Bayesian methods in clinical trials, cost-effectiveness, epidemiology and drug development. She currently co-chairs the EFSPI/PSI Historical Data SIG.
Before joining the pharmaceutical industry, Nicky was an academic statistician at the Medical Research Council Biostatistics Unit in Cambridge UK and Imperial College London, where she was professor of Statistics and Epidemiology. Her academic research focused on development and application of Bayesian methods in health and social science, and she is co-developer of the BUGS Bayesian software package.

 

Jason Connor
President & Lead Statistical Scientist, ConfluenceStat

Jason Connor is the founder of ConfluenceStat LLC. He has 15 years designing Bayesian adaptive trials and platform trials. He current sits on the Data Monitor Committees for multiple international platform trials in ALS, glioblastoma, prostate cancer, and COVID-19. 

Peter Mueller
Professor, Department of Mathematics and the Department of Statistics & Data Science, The University of Texas at Austin

pm19-1Peter Mueller is Professor in the  Department of Mathematics and the Department of Statistics & Data Science at the University of Texas at Austin. He has published widely on computational methods in Bayesian statistics, nonparametric Bayesian statistics and decision problems, with an emphasis on applications in biostatistics and bioinformatics. He has served as president of the International Society for Bayesian Analysis, and as chair for the Section on Bayesian Statistics of the American Statistical Association. Besides many graduate level courses he has taught short courses on Bayesian biostatistics, Bayesian clinical trial design, nonparametric Bayesian inference, medical decision making and more.

 
 

Ming-Hui Chen
Professor and Head of the Department of Statistics, The University of Connecticut

Chen160823c002-webDr. Ming-Hui Chen is currently Professor and Head of the Department of Statistics at the University of Connecticut (UConn). He was elected to Fellow of the International Society for Bayesian Analysis in 2016, Fellow of the Institute of Mathematical Statistics in 2007, and Fellow of the American Statistical Association in 2005. He has published over 400 peer-reviewed articles in mainstream statistics, biostatistics, and medical journals. He has also published five books, including two advanced graduate-level books on Bayesian survival analysis and Monte Carlo methods in Bayesian computation. He served as President of the International Chinese Statistical Association (ICSA) (2013) and President of the New England Statistical Society (2018-2020). In 2020, he received the ICSA distinguished achievement award. Currently, he serves as a Co Editor-in-Chief of Statistics and Its Interface and an Associate Editor of JASA, JCGS, and LIDA.

 

Ram Tiwari
Head of Statistical Methodology, Bristol Myers Squibb



Ram_Headshot
Ram C. Tiwari, Ph.D. recently (from February 1) joined Bristol Myers Squibb as the Head of Statistical Methodology. His prior career includes: Director for Division of Biostatistics, CDRH/FDA, 2016-2020; Associate Director for Statistical Science and Policy in the Immediate Office, Office of Biostatistics, CDER, 2018-2014; Program Director and Mathematical Statistician in the Division of Cancer Control and Population Sciences at National Cancer Institute, NIH, 2000-2008; Professor and Chair at the Department of Mathematics, University of North Carolina at Charlotte, 1986-2000; and faculty positions at UC Santa Barbara, and IIT Bombay.

Dr. Tiwari received his MS and PhD degrees from Florida State University in Mathematical Statistics. He is a Fellow of the American Statistical Association and a past President of the International Indian Statistical Association. Dr. Tiwari has published over 200 papers, using both Bayesian and Frequentist methods, covering a wide range of statistical topics with applications in clinical trials. He recently co-authored a book entitled “Signal detection for Medical Scientists: Likelihood Ratio Test-based Methodology” to be published by Taylor & Francis.