Open AccessPredicting Drug Concentration‐Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically‐Based Pharmacokinetic Model
Author(s) -
Yamamoto Yumi,
Välitalo Pyry A.,
Huntjens Dymphy R.,
Proost Johannes H.,
Vermeulen An,
Krauwinkel Walter,
Beukers Margot W.,
van den Berg DirkJan,
Hartman Robin,
Wong Yin Cheong,
Danhof Meindert,
van Hasselt John G. C.,
de Lange Elizabeth C. M.
Publication year - 2017
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12250
Subject(s) - physiologically based pharmacokinetic modelling , pharmacokinetics , drug , in silico , central nervous system , pharmacology , microdialysis , cerebrospinal fluid , drug development , compartment (ship) , chemistry , medicine , biology , neuroscience , pathology , biochemistry , oceanography , gene , geology
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.