Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Gorlaeus laboratorium, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
Department of Pharmacy and Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, USA.
Pharm Res. 2023 Nov;40(11):2555-2566. doi: 10.1007/s11095-023-03554-5. Epub 2023 Jul 13.
The unbound brain extracelullar fluid (brain) to plasma steady state partition coefficient, K, values provide steady-state information on the extent of blood-brain barrier (BBB) transport equilibration, but not on pharmacokinetic (PK) profiles seen by the brain targets. Mouse models are frequently used to study brain PK, but this information cannot directly be used to inform on human brain PK, given the different CNS physiology of mouse and human. Physiologically based PK (PBPK) models are useful to translate PK information across species.
Use the LeiCNS-PK3.0 PBPK model, to predict brain extracellular fluid PK in mice.
Information on mouse brain physiology was collected from literature. All available connected data on unbound plasma, brain PK of 10 drugs (cyclophosphamide, quinidine, erlotonib, phenobarbital, colchicine, ribociclib, topotecan, cefradroxil, prexasertib, and methotrexate) from different mouse strains were used. Dosing regimen dependent plasma PK was modelled, and Kpuu,BBB values were estimated, and provided as input into the LeiCNS-PK3.0 model to result in prediction of PK profiles in brain.
Overall, the model gave an adequate prediction of the brain PK profile for 7 out of the 10 drugs. For 7 drugs, the predicted versus observed brain data was within two-fold error limit and the other 2 drugs were within five-fold error limit.
The current version of the mouse LeiCNS-PK3.0 model seems to reasonably predict available information on brain from healthy mice for most drugs. This brings the translation between mouse and human brain PK one step further.
未结合的脑细胞外液（脑）与血浆的稳态分配系数 K 值提供了血脑屏障（BBB）转运平衡程度的稳态信息，但不能提供脑靶器官的药代动力学（PK）特征。小鼠模型常用于研究脑 PK，但鉴于小鼠和人类中枢神经系统的生理学不同，不能直接将这些信息用于推断人类脑 PK。基于生理学的 PK（PBPK）模型有助于在物种间转换 PK 信息。
使用 LeiCNS-PK3.0 PBPK 模型预测小鼠脑细胞外液 PK。
从文献中收集有关小鼠脑生理学的信息。使用来自不同小鼠品系的 10 种药物（环磷酰胺、奎尼丁、厄洛替尼、苯巴比妥、秋水仙碱、瑞博西利、拓扑替康、头孢拉定、普雷萨替尼和甲氨蝶呤）的未结合血浆和脑 PK 的所有可用相关数据。对剂量依赖性血浆 PK 进行建模，并估计 Kpuu、BBB 值，并将其作为输入提供给 LeiCNS-PK3.0 模型，以预测脑内 PK 特征。
总体而言，该模型对 10 种药物中的 7 种药物的脑 PK 特征进行了适当的预测。对于 7 种药物，预测的脑数据与观察到的数据之间的误差在两倍以内，另外 2 种药物的误差在五倍以内。
当前版本的小鼠 LeiCNS-PK3.0 模型似乎可以合理地预测健康小鼠的大多数药物的脑内信息。这使得小鼠和人类脑 PK 之间的转化又向前迈进了一步。
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