Bayesian Dose Escalation Using PK as a Covariate

• Activity Number: 503
• Type: Topic Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Arun Krishna* and Venkat Sethuraman+ and Lu-May Chiang
• Companies: Novartis Oncology and Novartis Oncology and Novartis Pharmaceuticals Corporation
• Keywords: Linear pharmacokinetics ; MTD ; bayesian

Abstract

Extensive research has been done in seeking the optimal dose using the dose-concentration relationship in healthy volunteers using Bayesian techniques. The Drawback of few this method specific to Cancer trials is either its lack of incorporating the risk of an adverse event into the modeling procedure on the assumption of linear pharmacokinetics, or, methods solely based on adverse events to establish MTD. This talk is on the application of pharmacokinetic end points as a covariate within a Bayesian decision procedure for Phase I dose escalation cancer trials.The motivation is to identify a optimal dose in Cancer patients that is likely to have a significant therapeutic value while ensuring its safety.Specifically in situations where both 'Therapeutic Value' as well as 'safety' are primarily exposure driven.Therefore in certain instances relating toxcity primaryly to drug concentration.