Utility of physiologically based pharmacokinetic models to drug development and rational drug discovery candidate selection

Abstract

The present paper proposes a modeling and simulation strategy for the prediction of pharmacokinetics (PK) of drug candidates by using currently available in silico and in vitro based prediction tools for absorption, distribution, metabolism and excretion (ADME). These methods can be used to estimate specific ADME parameters (such as rate and extent of absorption into portal vein, volume of distribution, metabolic clearance in the liver). They can also be part of a physiologically based pharmacokinetic (PBPK) model to simulate concentration–time profiles in tissues and plasma resulting from the overall PK after intravenous or oral administration. Since the ADME prediction tools are built only on commonly generated in silico and in vitro data, they can be applied already in early drug discovery, prior to any in vivo study. With the suggested methodology, the following advantages of the mechanistic PBPK modeling framework can now be utilized to explore potential clinical candidates already in drug discovery: (i) prediction of plasma (blood) and tissue PK of drug candidates prior to in vivo experiments, (ii) supporting a better mechanistic understanding of PK properties, as well as helping the development of more rationale PK-PD relationships from tissue kinetic data predicted, and hence facilitating a more rational decision during clinical candidate selection, and (iii) the extrapolation across species, routes of administration and dose levels.

Introduction

In drug discovery and development, it is of particular interest to estimate the pharmacokinetic (PK) behavior of drug candidates as early as possible based upon in silico and/or in vitro data to select the most promising compounds for further development. The characterization of a drug's PKs, which is the integral of the time coincident processes of absorption, distribution, metabolism and excretion (ADME), can be elucidated by studying each of the ADME processes individually, or by evaluating the overall PK of a study compound by assembling these processes in one global model. Physiologically based prediction methods have been developed for both evaluation types. The conceptual structure of a generic physiologically based pharmacokinetic (PBPK) model of disposition and absorption is depicted in Fig. 1. PBPK models have been developed and used in the last 30 years for the prediction of PK and PK/PD behavior of drugs and chemicals. Furthermore, the physiologically based nature of the PBPK modeling approach allows us to address mechanistic questions with regard to the PK as well as the concentration-effect relationships. PBPK models are capable of predicting quantitatively disposition in different animal species, including humans. Due to these advantages, PBPK models are routinely applied in chemical risk assessment and, therefore, can be considered as an established methodology in this field (Andersen, 1995, Clewell, 1995). However, the application of PBPK modeling in support of drug discovery and development in the pharmaceutical industry remained very limited, apart from a few examples (for examples see Kawai et al., 1994; Charnick et al., 1995). One of the main reasons for the limited applicability of PBPK models in drug discovery and early development was the need for resources demanding input parameters to characterize ADME, which could not be generated within the business process due to time constraints. Recent developments of in silico/in vitro based prediction tools, in particular for absorption, distribution and hepatic clearance, allowed PBPK modeling to become a real alternative for application already in early stages of drug discovery and development. These early applications of mechanism-based PBPK modeling have the potential to facilitate a more rational decision during the clinical candidate selection process, due to a better mechanistic understanding of the ADME processes. The present work summarizes the current status of ADME prediction tools, with the main focus on absorption, distribution and hepatic metabolic clearance. These prediction tools are combined in a PBPK model to obtain predictions of concentration–time profiles and thereby representing the first attempt to predict oral PKs solely based upon in silico and in vitro data. The oral PBPK model suggested is a further extension of the PBPK model of disposition recently published (Poulin and Theil, 2002b) by adding the absorption input function to the combined models of distribution and liver metabolism (Fig. 1). Finally, a modeling and simulation strategy is presented, using the discussed ADME prediction tools separately, as well as combined in a generic PBPK model for rat and humans, which illustrates the use of the method within the drug discovery and development process. One model compound (propranolol) is shown, where the application of the suggested modeling strategy has been illustrated.