The pharmacokinetic/pharmacodynamic pipeline: translating anticancer drug pharmacology to the clinic

AAPS J. 2011 Mar;13(1):111-20. doi: 10.1208/s12248-011-9253-1. Epub 2011 Jan 19.

Abstract

Progress in an understanding of the genetic basis of cancer coupled to molecular pharmacology of potential new anticancer drugs calls for new approaches that are able to address key issues in the drug development process, including pharmacokinetic (PK) and pharmacodynamic (PD) relationships. The incorporation of predictive preclinical PK/PD models into rationally designed early-stage clinical trials offers a promising way to relieve a significant bottleneck in the drug discovery pipeline. The aim of the current review is to discuss some considerations for how quantitative PK and PD analyses for anticancer drugs may be conducted and integrated into a global translational effort, and the importance of examining drug disposition and dynamics in target tissues to support the development of preclinical PK/PD models that can be subsequently extrapolated to predict pharmacologic characteristics in patients. In this article, we describe three different physiologically based (PB) PK modeling approaches, i.e., the whole-body PBPK model, the hybrid PBPK model, and the two-pore model for macromolecules, as well as their applications. General conclusions are that greater effort should be made to generate more clinical data that could validate scaled preclinical PB-PK/PD tumor-based models and, thus, stimulate a framework for preclinical to clinical translation. Finally, given the innovative techniques to measure tissue drug concentrations and associated biomarkers of drug responses, development of predictive PK/PD models will become a standard approach for drug discovery and development.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Antineoplastic Agents / pharmacokinetics*
  • Antineoplastic Agents / therapeutic use*
  • Biomarkers
  • Drug Design
  • Humans
  • Models, Statistical
  • Neoplasms / drug therapy
  • Neoplasms / metabolism
  • Systems Biology
  • Translational Research, Biomedical*

Substances

  • Antineoplastic Agents
  • Biomarkers