How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective

Usage of In Vitro Metabolism Data for Drug-Drug Interaction in Physiologically Based Pharmacokinetic Analysis Submissions to the US Food and Drug Administration

The key parameters necessary to predict drug-drug interactions (DDIs) are intrinsic clearance (CL_int ) and fractional contribution of the metabolizing enzyme toward total metabolism (f_m ). Herein, we summarize the accumulated knowledge from 53 approved new drug applications submitted to the Office of Clinical Pharmacology, US Food and Drug Administration, from 2016 to 2018 that contained physiologically based pharmacokinetic (PBPK) models to understand how in vitro data are used in PBPK models to assess drug metabolism and predict DDIs. For evaluation of CL_int and f_m , 29 and 20 new drug applications were included for evaluation, respectively. For CL_int , 86.2% of the PBPK models used modified values based on in vivo data with modifications ranging from -82.5% to 2752.5%. For f_m , 45.0% of the models used modified values with modifications ranging from -28% to 178.6%. When values for CL_int were used from in vitro testing without modification, the model resulted in up to a 14.3-fold overprediction of the area under the concentration-time curve of the substrate. When values for f_m from in vitro testing were used directly, the model resulted in up to a 2.9-fold underprediction of its DDI magnitude with an inducer, and up to a 1.7-fold overprediction of its DDI magnitude with an inhibitor. Our analyses suggested that the in vitro system usually provides a reasonable estimation of f_m when the drug metabolism by a given CYP pathway is more than 70% of the total clearance. In vitro experiments provide important information about basic PK properties of new drugs and can serve as a starting point for building a PBPK model. However, key PBPK parameters such as CL_int and f_m still need to be optimized based on in vivo data.

Metabolic stability and its role in the discovery of new chemical entities

Determination of metabolic profiles of new chemical entities is a key step in the process of drug discovery, since it influences pharmacokinetic characteristics of therapeutic compounds. One of the main challenges of medicinal chemistry is not only to design compounds demonstrating beneficial activity, but also molecules exhibiting favourable pharmacokinetic parameters. Chemical compounds can be divided into those which are metabolized relatively fast and those which undergo slow biotransformation. Rapid biotransformation reduces exposure to the maternal compound and may lead to the generation of active, non-active or toxic metabolites. In contrast, high metabolic stability may promote interactions between drugs and lead to parent compound toxicity. In the present paper, issues of compound metabolic stability will be discussed, with special emphasis on its significance, in vitro metabolic stability testing, dilemmas regarding in vitro-in vivo extrapolation of the results and some aspects relating to different preclinical species used in in vitro metabolic stability assessment of compounds.

Physiologically Based Pharmacokinetic and Pharmacodynamic Analysis Enabled by Microfluidically Linked Organs-on-Chips

Physiologically based pharmacokinetic (PBPK) modeling and simulation approaches are beginning to be integrated into drug development and approval processes because they enable key pharmacokinetic (PK) parameters to be predicted from in vitro data. However, these approaches are hampered by many limitations, including an inability to incorporate organ-specific differentials in drug clearance, distribution, and absorption that result from differences in cell uptake, transport, and metabolism. Moreover, such approaches are generally unable to provide insight into pharmacodynamic (PD) parameters. Recent development of microfluidic Organ-on-a-Chip (Organ Chip) cell culture devices that recapitulate tissue-tissue interfaces, vascular perfusion, and organ-level functionality offer the ability to overcome these limitations when multiple Organ Chips are linked via their endothelium-lined vascular channels. Here, we discuss successes and challenges in the use of existing culture models and vascularized Organ Chips for PBPK and PD modeling of human drug responses, as well as in vitro to in vivo extrapolation (IVIVE) of these results, and how these approaches might advance drug development and regulatory review processes in the future.