The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
At a recent PhUSE SDE, Cytel’s Chitra Tirodkar presented how East PROC MCPMod could be used to help solve the problem of uncertain true dose-response relationship in a bronchodilator study. In this blog we summarize some of the issues, and make Chitra's slides available for download.
The method for dose-response modeling that is widely called MCPMod allows a sponsor to measure the likelihood that particular dose-response curves are the right mathematical model for a given set of data. Since several different dose-response curves might be able to fit the data, how can you determine which is the best curve for your purposes?
When approaching a Phase 3 clinical trial, the need to ‘de-risk’ the massive investment often leads sponsors on a quest for the perfect risk mitigating adaptation. While a strategically planned clinical trial design can be an important step in giving a new medicine its best possible chance of success, there are a number of other ways that a trial sponsor can minimize study risk.
MCP-Mod methodology for dose-ranging clinical trials has been gaining popularity since the 2013 publication of the qualification opinion by the European Medicines Agency Committee for Medical Products for Human Use. Since its development at Novartis, MCP-Mod promises to devise proof-of-concept and dose-ranging trials which generate superior statistical evidence for dose-selection, while providing safety and efficacy data that can prove critical data for Phase III clinical trial design.
Although the general framework of the MCP-Mod method are becoming more familiar, its added complexity raises the question of whether it is a necessary supplement (or even substitute) for traditional dose-ranging trials. Here are a few shortfalls of the traditional approach that MCP-Mod is equipped to handle.