Applying MAM PBPK Modeling to Predict Positive Negative Food Effects скачать в хорошем качестве

Applying MAM PBPK Modeling to Predict Positive Negative Food Effects

It is widely recognized that food can affect the absorption of orally administered drugs. In the course of pharmaceutical development, food is evaluated clinically as part of the early single or multiple ascending dose studies; additional evaluations often take place when there are formulation changes. The outcome of these studies informs dosing instructions both during the conduct of clinical trials as well as on the product label. Physiologically based absorption/biopharmaceutics modeling offers the possibility to simulate a compound’s pharmacokinetics under fasted or fed states, incorporating knowledge of formulation properties. This webinar will discuss predictive case studies on food effect predictions and a proposed, multi-step workflow for BCS I and II compounds that was developed based on the collective experience of four pharmaceutical companies. The case studies demonstrate how appropriately established and validated models can lead to successful prediction of food effect. The examples integrate solubility and/or dissolution data and rely on a “middle out” validation of the model on prandial state for initial model setup. Subsequent model validation in both fasted and fed state is recommended, if possible, prior to application of the models for late stage and the to-be-marketed formulations. When the models are established following the proposed workflow, we believe they can be used to simulated outcomes for new doses and formulation/API changes, in lieu of repeating a clinical food effect study. Speakers: Neil Parrott Modeling & Simulation Scientist Roche Pharmaceuticals Tycho Heimbach, Ph.D. Director, Global Team Lead PBPK Novartis Institutes for BioMedical Research