Estimating minimum effective doses and their response rates in combination trial using iPIPE

Fri, May 14, 2025, 09:00 – 10:00AM (PDT), 11:00 – 12:00 noon (EST)

Abstract: 

In this talk, we address the problem of identifying minimum effective doses (MED) of drug combination or composite therapy in early phase proof-of-concept trials. Drug combination is a common therapeutic strategy in cancer. Combination of multiple (>2) molecules is becoming more plausible due to advances in target identification. For other diseases and treatment modalities, treatments are often composite of multiple factors. We will describe a novel adaptive design (called adaptive PIPE) for the identification of MED in the context of a behavioral intervention trial where our goal is to reduce cardiometabolic risk of the trial participants. PIPE is computationally fast and is scalable to trials with high-order combinations. PIPE is motivated by a Bayesian decision-theoretic framework thus facilitating false discovery control. We will show the improvement due to adaptations in terms of false discovery rate, true positive rate, and treatment allocation of trial participants. If time permits, we will discuss iPIPE, an extension of PIPE for estimating response rates of combinations.

Speaker:

Ying Kuen (Ken) Cheung, PhD, is Professor of Biostatistics at Columbia University. He has general interests in the development and evaluation of evidence-based treatments, interventions and policies at all phases of translational research. He is an expert in experimental designs, adaptive designs in clinical trials of treatments for cancer, stroke, neurological disorders, cardiovascular diseases, and mental health, SMART designs, N-of-1 personalized trials, and the analysis of high dimensional behavioral data. An overarching goal of his research and professional activities is to advance precision medicine using data science and biostatistical methods. He is a recipient of IBM Faculty Award on Big Data and Analytics. He is a Fellow of the American Statistical Association, and a Fellow of the New York Academy of Medicine.

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