Predicting pharmacokinetics of drugs using physiologically based modeling--application to food effects.

Our knowledge of the major mechanisms underlying the effect of food on drug absorption allows reliable qualitative prediction based on biopharmaceutical properties, which can be assessed during the pre-clinical phase of drug discovery. Furthermore, several recent examples have shown that physiologically based absorption models incorporating biorelevant drug solubility measurements can provide quite accurate quantitative prediction of food effect. However, many molecules currently in development have distinctly sub-optimal biopharmaceutical properties, making the quantitative prediction of food effect for different formulations from in vitro data very challenging. If such drugs reach clinical development and show undesirable variability when dosed with food, improved formulation can help to reduce the food effect and carefully designed in vivo studies in dogs can be a useful guide to clinical formulation development. Even so, such in vivo studies provide limited throughput for screening, and food effects seen in dog cannot always be directly translated to human. This paper describes how physiologically based absorption modeling can play a role in the prediction of food effect by integrating the data generated during pre-clinical and clinical research and development. Such data include physicochemical and in vitro drug properties, biorelevant solubility and dissolution, and in vivo pre-clinical and clinical pharmacokinetic data. Some background to current physiological absorption models of human and dog is given, and refinements to models of in vivo drug solubility and dissolution are described. These are illustrated with examples using GastroPlus to simulate the food effect in dog and human for different formulations of two marketed drugs.