Improving Oncology Clinical Program by Use of Innovative Designs and Comparing via Simulations

• Activity Number: 13
• Type: Topic Contributed
• Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Joel Miller*+ and Tom Parke and Donald Berry and Olga V Marchenko and Inna Perevozskaya and Yanping Wang
• Companies: Eli Lilly and Company/ImClone and Tessella Inc. and MD Anderson Cancer Center and Quintiles, Inc. and Pfizer Inc. and Eli Lilly and Company
• Keywords: oncology ; adaptive ; development ; simulation ; clinical ; program

Abstract

The design of an oncology clinical program is much more challenging than the design of a separate study. The standard approach has been proven to be not very successful during the last decade; the failure rate of Phase 3 studies in oncology is more than 66%. Improving the development strategy by taking into account data from early development and applying innovative statistical methods is one of the major objectives for biostatisticians designing and supporting oncology clinical programs. This presentation is built on the work of the DIA oncology workstream on adaptive program. With representatives from a number of companies and universities, this group compared a standard oncology program with one using predictive biomarkers, prognostic biomarkers, and adaptive designs. Simulation-based Bayesian decision theory was used to tackle this problem.