Predicting Drug Concentration-Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically-Based Pharmacokinetic Model

CPT Pharmacometrics Syst Pharmacol. 2017 Nov;6(11):765-777. doi: 10.1002/psp4.12250. Epub 2017 Oct 13.

Abstract

Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System-specific and drug-specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration-time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue. These drugs, all small molecules, were selected to cover a wide range of physicochemical properties. The concentration-time profiles for these drugs were adequately predicted across the CNS compartments (symmetric mean absolute percentage error for the model prediction was <91%). In conclusion, the developed PBPK model can be used to predict temporal concentration profiles of drugs in multiple relevant CNS compartments, which we consider valuable information for efficient CNS drug development.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Brain Chemistry
  • Central Nervous System / chemistry*
  • Cerebrospinal Fluid / chemistry
  • Models, Biological*
  • Plasma / chemistry
  • Rats
  • Small Molecule Libraries / pharmacokinetics*
  • Tissue Distribution

Substances

  • Small Molecule Libraries