Physiologically-based Pharmacokinetic (PBPK) Modelling of Transporter Mediated Drug Absorption, Clearance and Drug-drug Interactions

Abstract

Abstarct: Membrane transporters play an important role in intestinal absorption, distribution and clearance of drugs. Additionally transporters along with enzymes regulate tissue exposures (e.g. liver, kidney and brain), which are important for safety and efficacy considerations. Early identification of transporters involved guides generation of in vitro and in vivo data needed to gain mechanistic understanding on the role of transporters in organ clearance, tissue exposures and enables development of physiological-based pharmacokinetic (PBPK) models. A lot of progress has been made in developing several in vitro assay systems and mechanistic in silico models to determine kinetic parameters for transporters, which are incorporated into PBPK models. Although, intrinsic clearance and inhibition data from in vitro systems generally tend to underpredict in vivo clearance and magnitude of drug-drug interactions (DDIs), empirical scaling factors derived from a sizable dataset are often used to offset underpredictions. PBPK models are increasing used to predict the impact of transporters on intestinal absorption, clearance, victim and perpetrator DDIs prior to first in human clinical trials. The models are often refined when clinical data is available and are used to predict pharmacokinetics in untested scenarios such as the impact of polymorphisms, ontogeny, ethnicity, disease states and DDIs with other perpetrator drugs. The aim of this review is to provide an overview of (i) regulatory requirements around transporters, (ii) in vitro systems and their limitations in predicting transporter mediated drug disposition and DDIs, (iii) PBPK modelling tactics and case studies used for internal decision making and/or for regulatory submissions.

Drug Disposition Protein Quantification in Matched Human Jejunum and Liver From Donors With Obesity

“…Indeed, correcting for SI and VIL1 resulted in higher interindividual variability ( Figure ), suggesting that more sophisticated algorithms for cell type composition are required 58 . As differences in protein levels can greatly influence mathematical prediction models for drug disposition or toxicity, they should be taken into account when personalizing systems pharmacology 1 . However, care should be taken in using the concentrations provided for multimeric assemblies (e.g., ABCG2 (BCRP) is active as a dimer).…”

“…Such translation has been successfully performed with scaling factors based on specific protein concentrations in the in vitro model and target tissue 2,3 . To build and refine predictive models, they must take into account interindividual variability 1 . Information regarding the protein composition of tissues involved in drug disposition across different populations is therefore imperative.…”

“…Mathematical models, such as physiologically‐based pharmacokinetic models, are frequently applied to predict drug disposition, efficacy, and toxicity in humans. These models rely on accurate translation of experimental in vitro data to in vivo 1 . Such translation has been successfully performed with scaling factors based on specific protein concentrations in the in vitro model and target tissue 2,3 .…”

“…These models rely on accurate translation of experimental in vitro data to in vivo . 1 Such translation has been successfully performed with scaling factors based on specific protein concentrations in the in vitro model and target tissue. 2 , 3 To build and refine predictive models, they must take into account interindividual variability.…”

“… 2 , 3 To build and refine predictive models, they must take into account interindividual variability. 1 Information regarding the protein composition of tissues involved in drug disposition across different populations is therefore imperative.…”