4.7 Article

Physiologically Based Pharmacokinetic (PBPK) Modeling for Predicting Brain Levels of Drug in Rat

期刊

PHARMACEUTICS
卷 13, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/pharmaceutics13091402

关键词

blood-brain barrier (BBB); physiologically based pharmacokinetics (PBPK); quantitative structure-property relationships (QSPRs); distribution volume in brain (Vu; brain); plasma-brain partition coefficient (Kpuu; brain

资金

  1. European Union, through FEDER (Fondo Europeo de Desarrollo Regional), under the project: Modelos in vitro de evaluacion biofarmaceutica [SAF2016-78756]
  2. Ministry of Science, Innovation and Universities of Spain [FPU17/00530]
  3. Miguel Hernandez University [0762/19]
  4. Agencia Estatal Investigacion

向作者/读者索取更多资源

This study developed a new in vitro system combined with a PBPK model to predict brain concentration levels of different drugs in rats. Through internal validation, it was concluded that the model, incorporating MDCK data, provided the best predictions for passive diffusion and carrier-mediated transported drugs.
One of the main obstacles in neurological disease treatment is the presence of the blood-brain barrier. New predictive high-throughput screening tools are essential to avoid costly failures in the advanced phases of development and to contribute to the 3 Rs policy. The objective of this work was to jointly develop a new in vitro system coupled with a physiological-based pharmacokinetic (PBPK) model able to predict brain concentration levels of different drugs in rats. Data from in vitro tests with three different cells lines (MDCK, MDCK-MDR1 and hCMEC/D3) were used together with PK parameters and three scaling factors for adjusting the model predictions to the brain and plasma profiles of six model drugs. Later, preliminary quantitative structure-property relationships (QSPRs) were constructed between the scaling factors and the lipophilicity of drugs. The predictability of the model was evaluated by internal validation. It was concluded that the PBPK model, incorporating the barrier resistance to transport, the disposition within the brain and the drug-brain binding combined with MDCK data, provided the best predictions for passive diffusion and carrier-mediated transported drugs, while in the other cell lines, active transport influence can bias predictions.

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