The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.
Our client had the following key questions which they wanted our pharmacometrics group to address for an upcoming phase 2 trial of their ulcerative colitis compound .
1) Can knowledge from pre-clinical and Phase 1 data inform on the optimal range of doses for an upcoming Phase 2 dose-ranging study?
2) How may the dose response observed in PD markers in Phase 1 healthy volunteers translate to the patient population?
Unlike statistics which has been around in some form for hundreds of years, pharmacometrics is, by comparison, a relatively new discipline and only entered the clinical development world in the last 30 years. Situated at the intersection of mathematical modeling, simulation, and big data, pharmacometrics leverages the best practices of translational research to generate clinical development strategy.
Exposure-response data gained from clinical studies can provide a basis for model-based analysis and simulation, helping to predict the expected relationships between exposure and response. Using this approach, it may be possible to optimize dosage regimens and to individualize treatment in specific patient subsets for which there are limited data. In this blog, we examine a case study of an exposure response modeling project conducted by our Quantitative Pharmacology and Pharmacometrics team.