Enabling Phase III Go/No-Go Decision Using Phase I/II Study Data

• Activity Number: 652
• Type: Topic Contributed
• Date/Time: Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Jiang Qian*+ and Ya-Hui Hsu
• Companies: Abbott Laboratories and Abbott Laboratories
• Keywords: Joint modelling ; Bayesian approach ; response rate ; time-to-event data ; posterior probability ; predictive probability

Abstract

Phase 1 and 2 are crucial phases in the drug development process, as decisions to go/no go into Phase 3 development will be primarily based on phase 1/2 study data and/or other external information. This session will introduce statistical models that enable quantification of the uncertainty associated with the results coming from early phase 1/2 studies. The response and time-to-event data will be modeled jointly to elucidate the relationship between short term endpoint (response rate) and long term endpoint (time-to-event). The models will use formal or informal Bayesian approaches to exploit the totality of accumulated data/knowledge in a coherent way for internal Go/No Go Phase 3 decision-making. Posterior and predictive probabilities for parameters of interest computed in a Bayesian paradigm are easy to interpret and provide much more relevant and useful information than hypothesis testing. Example(s) from real life oncology clinical trial will be used to illustrate statistical method to jointly model response and time-to-event data, and subsequently to evaluate the probability of success for drug candidates in Phase 3 development.