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In order to optimize central nervous system (CNS) drug development, accurate prediction of the drug’s human steady‐state unbound brain interstitial fluid‐to‐plasma concentration ratio (K p,uu,brain ) is critical, especially for drugs that are effluxed by the multiple drug resistance transporters (e.g., P‐glycoprotein, P‐gp). Due to lack of good  in vitro  human blood‐brain barrier models, we and others have advocated the use of a proteomics‐informed relative expressive factor (REF) approach to predict K p,uu,brain . Therefore, we tested the success of this approach in humans, with a focus on P‐gp substrates, using brain positron emission tomography imaging data for verification. To do so, the efflux ratio (ER) of verapamil, N‐desmethyl loperamide, and metoclopramide was determined in human P‐gp‐transfected MDCKII cells using the Transwell assay. Then, using the ER estimate, K p,uu,brain  of the drug was predicted using REF (ER approach). Alternatively,  in vitro  passive and P‐gp–mediated intrinsic clearances (CLs) of these drugs, estimated using a five‐compartmental model, were extrapolated to  in vivo  using REF (active CL) and brain microvascular endothelial cells protein content (passive CL). The ER approach successfully predicted K p,uu,brain  of all three drugs within twofold of observed data and within 95% confidence interval of the observed data for verapamil and N‐desmethyl loperamide. Using the  in vitro –to– in vivo  extrapolated clearance approach, K p,uu,brain  was reasonably well predicted but not the brain unbound interstitial fluid drug concentration‐time profile. Therefore, we propose that the ER approach be used to predict K p,uu,brain  of CNS candidate drugs to enhance their success in development.

clinical pharmacology and therapeutics

Successful Prediction of Human Steady‐State Unbound Brain‐to‐Plasma Concentration Ratio of P‐gp Substrates Using the Proteomics‐Informed Relative Expression Factor Approach