Description: The development of novel therapies for rare diseases involves many challenges due to small and heterogeneous patient populations, limited knowledge of natural history data, ethical constraints, etc. This tutorial will focus on statistical methods for early phase clinical trials. It will start with some background on the drug development issues for rare diseases. After that, we will consider adaptive phase 1 trial designs that facilitate learning of the underlying dose–toxicity relationship while protecting study participants from exposure to overly toxic doses. We will discuss data analysis issues following these designs and the approaches for making decisions on the maximum tolerated dose (MTD). We will also cover adaptive phase 1/2 trial designs that incorporate toxicity and early efficacy (response) in dose-finding objectives and discuss the added value of such designs. Some additional important topics on early development clinical trials will be highlighted.
Lecturer: Alex Sverdlov
Alex Sverdlov is a Neuroscience Disease Area Statistical Lead at Novartis. He earned his BSc in Applied Mathematics from V.N. Karazin Kharkiv National University, Ukraine, MSc in Statistics from University of Maryland, Baltimore County, and PhD in Information Technology with Concentration in Statistical Science from George Mason University. With 17 years of career in the biopharmaceutical industry, Alex has been actively involved in methodological research and applications of innovative statistical approaches in drug development. His most recent work involves design and analysis of clinical trials of novel treatment modalities such as digital therapeutics and gene therapies. Alex has co-authored over forty refereed articles, edited three monographs, and co-authored a book “Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach” (CRC Press/Chapman & Hall, 2019).
