Gülave Berfin, Lesmana Ariel, de Lange Elizabeth Cm, van Hasselt J G Coen
Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, Leiden, 2333 CC, The Netherlands.
J Pharmacokinet Pharmacodyn. 2025 Jan 7;52(1):11. doi: 10.1007/s10928-024-09957-0.
P-glycoprotein (P-gp) is a key efflux transporter and may be involved in drug-drug interactions (DDIs) at the blood-brain barrier (BBB), which could lead to changes in central nervous system (CNS) drug exposure. Morphine is a P-gp substrate and therefore a potential victim drug for P-gp mediated DDIs. It is however unclear if P-gp inhibitors can induce clinically relevant changes in morphine CNS exposure. Here, we used a physiologically-based pharmacokinetic (PBPK) model-based approach to evaluate the potential impact of DDIs on BBB transport of morphine by clinically relevant P-gp inhibitor drugs.The LeiCNS-PK3.0 PBPK model was used to simulate morphine distribution at the brain extracellular fluid (brain) for different clinical intravenous dosing regimens of morphine, alone or in combination with a P-gp inhibitor. We included 34 commonly used P-gp inhibitor drugs, with inhibitory constants and expected clinical P-gp inhibitor concentrations derived from literature. The DDI impact was evaluated by the change in brain exposure for morphine alone or in combination with different inhibitors. Our analysis demonstrated that P-gp inhibitors had a negligible effect on morphine brain exposure in the majority of simulated population, caused by low P-gp inhibition. Sensitivity analyses showed neither major effects of increasing the inhibitory concentration nor changing the inhibitory constant on morphine brain exposure. In conclusion, P-gp mediated DDIs on morphine BBB transport for the evaluated P-gp inhibitors are unlikely to induce meaningful changes in clinically relevant morphine CNS exposure. The developed CNS PBPK modeling approach provides a general approach for evaluating BBB transporter DDIs in humans.
P-糖蛋白(P-gp)是一种关键的外排转运蛋白,可能参与血脑屏障(BBB)处的药物相互作用(DDIs),这可能导致中枢神经系统(CNS)药物暴露的变化。吗啡是一种P-gp底物,因此是P-gp介导的药物相互作用的潜在受影响药物。然而,尚不清楚P-gp抑制剂是否能在临床上引起吗啡中枢神经系统暴露的相关变化。在此,我们使用基于生理药代动力学(PBPK)模型的方法,来评估临床相关的P-gp抑制剂药物对吗啡血脑屏障转运的药物相互作用的潜在影响。LeiCNS-PK3.0 PBPK模型用于模拟吗啡在不同临床静脉给药方案下,单独或与P-gp抑制剂联合使用时在脑细胞外液(脑)中的分布。我们纳入了34种常用的P-gp抑制剂药物,其抑制常数和预期的临床P-gp抑制剂浓度来自文献。通过单独使用吗啡或与不同抑制剂联合使用时脑暴露的变化来评估药物相互作用影响。我们的分析表明,在大多数模拟人群中,P-gp抑制剂对吗啡脑暴露的影响可忽略不计,这是由于P-gp抑制作用较低。敏感性分析表明,增加抑制浓度或改变抑制常数对吗啡脑暴露均无重大影响。总之,对于所评估的P-gp抑制剂,P-gp介导的对吗啡血脑屏障转运的药物相互作用不太可能在临床上引起相关吗啡中枢神经系统暴露的有意义变化。所开发的中枢神经系统PBPK建模方法为评估人类血脑屏障转运体药物相互作用提供了一种通用方法。