The 3rd Stat4Onc Annual Symposium
Efficient development strategy for the immune-oncology space
Speaker Biography and Abstract
Markus P. Vallaster, MD, PhD, PhD
Clinical Program Leader, Oncology
Markus joined Boehringer Ingelheim as Clinical Program Leader, Oncology in September 2018 and currently serves as the medical lead for an MDM2-p53 antagonist that induces apoptosis in TP53 wildtype tumors. A variety of combination partners for this compound are under investigation to more efficiently attack tumor cells and alter the tumor microenvironment.
Before his time at BI, Markus worked in clinical development at a small Biotechnology company in Cambridge, Massachusetts, focusing on T cell based therapies and immuno-oncology. Markus spent several years in academia where he studied epigenetic changes in an animal model over time and generations applying genome-wide sequencing approaches to assess the contributions of small RNAs, histone modifications, and DNA methylation patterns to the overall regulatory network in a cell.
Markus is a physician-scientist who received his medical training at Ludwig-Maximilian-University in Germany. Markus holds a PhD in stem cell research from Ludwig-Maximilian-University and a PhD in epigenetics from University of Massachusetts Medical School, USA.
The times they are a-changin’ – new immuno-oncology approaches to old cancers
The immune system plays a major role in the development, as well as elimination of cancer cells in the body. Over the last decade, novel and more refined analytical methods have expanded our understanding of how certain sub-types of immune cells within the tumor microenvironment (TME) can either promote or inhibit tumor growth. We realized that the interchange between immune system and cancer cells is not static, but rather complex and dynamic. Intrinsic and extrinsic factors can modulate this intricate balance between immune-activating and immune-suppressive factors in the TME. Immune checkpoint inhibitors such as anti-CTLA4 and anti-PD1 antibodies have shown remarkable efficacy in a subset of cancer patients to re-invigorate tumor-infiltrating lymphocytes (TILs) and eliminate tumor cells. However, the reasons as to why the majority of cancer patients does not benefit from these treatments remain elusive. Our ability to develop tools that allow us to characterize and monitor the TME of cancer patients in more detail will determine the success of immuno-oncology (I/O) approaches. Here, we will discuss some of the opportunities and challenges that we face in our endeavor to bring new I/O treatments to patients.
Cong Chen, PhD
Early Oncology Development Statistics
Merck & Co., Inc
Dr. Cong Chen is Executive Director of Early Oncology Development Statistics at Merck & Co., Inc. He joined Merck in 1999 after graduating from Iowa State University with a Ph.D. in Statistics. He also holds a MS degree in Mathematics from Indiana University at Bloomington and a BS degree in Probability and Statistics from Beijing University, PR China.
As head of the group, he oversees the statistical support of oncology early clinical development at Merck. Prior to taking the role in March 2016, he led the statistical support for the development of pembrolizumab (KEYTRUDA), a paradigm changing anti-PD-1 immunotherapy, and played a pivotal role in accelerating its regulatory approvals.
He is a Fellow of American Statistical Association, an Associate Editor of Statistics in Biopharmaceutical Research, a member of Cancer Clinical Research Editorial Board and a co-leader of the DIA Small Population Work Stream. He has published over 70 papers and 9 book chapters on design and analysis of clinical trials, and was twice invited to give an oral presentation at the AACR Annual Meeting in recent years on oncology drug development.
Optimal basket designs for efficacy screening with cherry-picking
In oncology drug development post dose-finding, a new drug is routinely tested in a basket trial with multiple tumor types for efficacy screening. Due to the small sample sizes, assessment of anti-tumor activities is heuristic and often involves unsupervised cherry-picking.
In this talk, I will present a variety of optimal basket designs including optimal one-stage designs with minimal sample size, an extension of Simon’s optimal designs for single-arm trials to multi-arm basket trials, optimal two-stage basket designs under fixed total sample size. Time permitting, I will also discuss about the optimal number of tumor types for a basket trial under fixed sample size. A supervised cherry-picking method (pruning and pooling) is applied to all the designs that control Type I error at the desired level and calculate Type II error under a non-informative prior assumption about drug activity.
Zhenming Shun, Ph.D.
Zhenming Shun currently is VP, Head of Biostatistics and Data Management at Daiichi-Sankyo. Before the current job, Zhenming was an Associate VP, Global Head of Biostatistics Oncology at Sanofi. Zhenming has more than 20 years of experience in drug development. Zhenming received his PhD in statistics from U of Chicago and MS in mathematics form Peking University. His research interests include adaptive design in clinical trials and generalized mixed effects models.