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

Toxicol Lett. 2003 Feb 18;138(1-2):29-49. doi: 10.1016/s0378-4274(02)00374-0.


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.

Publication types

  • Review

MeSH terms

  • Animals
  • Drug Evaluation / methods*
  • Drug Evaluation, Preclinical / methods*
  • Drugs, Investigational / classification
  • Drugs, Investigational / pharmacokinetics*
  • Drugs, Investigational / toxicity*
  • Humans
  • Models, Biological*
  • Quantitative Structure-Activity Relationship
  • Rats
  • Solubility
  • Species Specificity


  • Drugs, Investigational