Physiologically based modelling and prediction of drug interactions.

Quantitative Prediction of Drug–Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug-drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to ...

Physiologically Based Pharmacokinetic Modeling Framework for Quantitative Prediction of an Herb–Drug Interaction

Herb-drug interaction predictions remain challenging. Physiologically based pharmacokinetic (PBPK) modeling was used to improve prediction accuracy of potential herb-drug interactions using the semipurified milk thistle preparation, silibinin, as an exemplar herbal product. Interactions between silibinin constituents and the probe substrates warfarin (CYP2C9) and midazolam (CYP3A) were simulate...

TITLE: Prediction of Drug-Drug Interactions with Crizotinib as the CYP3A Substrate Using a Physiologically-Based Pharmacokinetic Model AUTHORS:

TITLE : Prediction of Drug - Drug Interactions with Crizotinib as the CYP 3 A Substrate Using a Physiologically - Based Pharmacokinetic Model

Towards A Computational Prediction of Nanoparticle Pharmacokinetics and Distribution

A number of nanotechnology-enabled drug delivery platforms are in varying stages of drug development. While, physiologically-based pharmacokinetic (PBPK) modelling has become a well-established tool for conventional medicines from preclinical to post-licensing environments, its application for nanomedicines is in its infancy. Part of the reason for this is that the fundamental mechanisms that u...