In this manuscript, we have presented the development of a novel platform physiologically-based pharmacokinetic (PBPK) model to characterize brain disposition of mAbs in the mouse, rat, monkey and human. The model accounts for known anatomy and physiology of the brain, including the presence of distinct blood–brain barrier and blood–cerebrospinal fluid (CSF) barrier. CSF and interstitial fluid turnover, and FcRn mediated transport of mAbs are accounted for. The model was first used to characterize published and in-house pharmacokinetic (PK) data on the disposition of mAbs in rat brain, including the data on PK of mAb in different regions of brain determined using microdialysis. Majority of model parameters were fixed based on literature reported values, and only 3 parameters were estimated using rat data. The rat PBPK model was translated to mouse, monkey, and human, simply by changing the values of physiological parameters corresponding to each species. The translated PBPK models were validated by a priori predicting brain PK of mAbs in all three species, and comparing predicted exposures with observed data. The platform PBPK model was able to a priori predict all the validation PK profiles reasonably well (within threefold), without estimating any parameters. As such, the platform PBPK model presented here provides an unprecedented quantitative tool for prediction of mAb PK at the site-of-action in the brain, and preclinical-to-clinical translation of mAbs being developed against central nervous system (CNS) disorders. The proposed model can be further expanded to account for target engagement, disease pathophysiology, and novel mechanisms, to support discovery and development of novel CNS targeting mAbs.

中文翻译：

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用于大脑中抗体配置的转化平台 PBPK 模型。

在这份手稿中，我们介绍了一种新的基于生理学的药代动力学 (PBPK) 模型的开发，以表征小鼠、大鼠、猴子和人类中 mAb 的大脑分布。该模型解释了大脑的已知解剖学和生理学，包括存在明显的血脑屏障和血脑脊液 (CSF) 屏障。CSF 和间质液周转，以及 FcRn 介导的 mAb 转运都被考虑在内。该模型首先用于表征有关 mAb 在大鼠大脑中的分布的已发表和内部药代动力学 (PK) 数据，包括使用微透析确定的 mAb 在大脑不同区域的 PK 数据。大多数模型参数是根据文献报告值固定的，只有 3 个参数是使用大鼠数据估计的。将大鼠 PBPK 模型转化为小鼠，猴子和人类，只需改变每个物种对应的生理参数值。翻译的 PBPK 模型通过先验预测所有三个物种中 mAb 的脑 PK 并将预测的暴露与观察到的数据进行比较来验证。平台 PBPK 模型能够合理地（在三倍以内）先验地预测所有验证 PK 配置文件，而无需估计任何参数。因此，此处介绍的平台 PBPK 模型提供了一种前所未有的定量工具，用于预测大脑中作用部位的 mAb PK，以及针对中枢神经系统 (CNS) 疾病开发的 mAb 的临床前到临床转化。提出的模型可以进一步扩展以解释目标参与、疾病病理生理学和新机制，