Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation.

Daniel Scotcher,Maria Posada,Aleksandra Galetin,Amin Rostami-Hodjegan,Christopher Jones

doi:10.1208/s12248-016-9959-1

Daniel Scotcher, Maria Posada + Show 3 more

Open Access

https://doi.org/10.1208/s12248-016-9959-1

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Abstract

It is envisaged that application of mechanistic models will improve prediction of changes in renal disposition due to drug-drug interactions, genetic polymorphism in enzymes and transporters and/or renal impairment. However, developing and validating mechanistic kidney models is challenging due to the number of processes that may occur (filtration, secretion, reabsorption and metabolism) in this complex organ. Prediction of human renal drug disposition from preclinical species may be hampered by species differences in the expression and activity of drug metabolising enzymes and transporters. A proposed solution is bottom-up prediction of pharmacokinetic parameters based on in vitro-in vivo extrapolation (IVIVE), mediated by recent advances in in vitro experimental techniques and application of relevant scaling factors. This review is a follow-up to the Part I of the report from the 2015 AAPS Annual Meeting and Exhibition (Orlando, FL; 25th-29th October 2015) which focuses on IVIVE and mechanistic prediction of renal drug disposition. It describes the various mechanistic kidney models that may be used to investigate renal drug disposition. Particular attention is given to efforts that have attempted to incorporate elements of IVIVE. In addition, the use of mechanistic models in prediction of renal drug-drug interactions and potential for application in determining suitable adjustment of dose in kidney disease are discussed. The need for suitable clinical pharmacokinetics data for the purposes of delineating mechanistic aspects of kidney models in various scenarios is highlighted.

Highlights

Renal metabolism and excretion can be important determinants of the local and systemic exposures of drugs and their metabolites
Few studies have compared different structures or refined versions of mechanistic kidney models in specific scenarios [19,37], and further studies of this nature are recommended
Statistical analyses of data from clinical pharmacokinetics studies using patients with and without chronic kidney disease can be used to determine whether any relationships between pharmacokinetic parameters (e.g. CLR, CL, area under the curve (AUC), V) and markers of renal function (e.g. creatinine clearance (CLCR) or estimated glomerular filtration rate) exist [59]

Summary

INTRODUCTION

The overall aim of this part of the review is to examine the progress required to achieve quantitative predictions of renal drug disposition using PBPK-IVIVE with specific focus on the efforts to develop and validate mechanistic kidney models. This will include the prediction of renal drug metabolism and renal excretion as clearance routes. It is important to note that modelling of renal drug disposition in paediatrics requires special consideration to account for the maturation of renal function and ontogeny of protein expression For those interested in this topic, modelling efforts and reviews have previously been reported [7,8,9]. Enzyme abundances were found to be between 7- and 11-fold and 19- and 43-fold higher in recombinant expression

Literature values and applications

CONCLUSION AND FUTURE DIRECTIONS