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使用生理药代动力学(PBPK)模型和模拟预测儿科人群中单克隆抗体的药代动力学

Prediction of Monoclonal Antibody Pharmacokinetics in Pediatric Populations Using PBPK Modeling and Simulation.

作者信息

Zunino Chiara, Gualano Virginie, Zhou Haiying, Lukacova Viera, Le Merdy Maxime

机构信息

Phinc Development, 36 Rue Victor Basch, 91300 Massy, France.

Simulations Plus, Inc., P.O. Box 12317, Research Triangle Park, NC 27709, USA.

出版信息

Pharmaceutics. 2025 Jul 5;17(7):884. doi: 10.3390/pharmaceutics17070884.

Abstract

: Accurately determining pediatric dosing is essential prior to initiating clinical trials or administering medications in routine clinical settings. In children, ethical considerations demand careful evaluation of both safety and effectiveness. Typically, dosing recommendations for therapeutic proteins, such as monoclonal antibodies (mAbs), are derived from adult dosages using body weight as a scaling factor. However, this method overlooks key physiological and biochemical distinctions between pediatric and adult patients. Therefore, this could lead to the underexposure of mAbs, limiting their efficacy in this population. Additional methods are necessary to predict pediatric doses mechanistically. For small molecules, physiologically based pharmacokinetic (PBPK) models have been extensively used to predict pediatric doses based on physiological age-related changes and enzymes/transporters ontogeny. This study aims to evaluate the ability of PBPK models to predict mAbs' pediatric exposure. : Three mAbs were used for model development and validation: bevacizumab, infliximab, and atezolizumab. The PBPK models were built using GastroPlus Biologics module. For each mAb, the PBPK model was developed based on observed data in healthy and/or patient adults. Then, the physiological parameters were scaled to describe the pediatric physiology to predict exposure to the pediatric populations. Predicted plasma concentration-time courses were overlaid with reported observed data to assess the ability of the PBPK model to predict pediatric exposure. : Results showed that PBPK models accurately predicted pediatric pharmacokinetics for mAbs. : This research marks a significant step in validating mechanistic extrapolation methods for biologics exposure prediction in children using PBPK models.

摘要

在启动临床试验或在常规临床环境中给药之前,准确确定儿科剂量至关重要。对于儿童,伦理考量要求对安全性和有效性进行仔细评估。通常,治疗性蛋白质(如单克隆抗体[mAbs])的给药建议是通过将成人剂量乘以体重作为比例因子得出的。然而,这种方法忽略了儿科和成人患者之间关键的生理和生化差异。因此,这可能导致单克隆抗体暴露不足,限制其在该人群中的疗效。需要其他方法来机械地预测儿科剂量。对于小分子,基于生理的药代动力学(PBPK)模型已被广泛用于根据与生理年龄相关的变化以及酶/转运体的个体发育来预测儿科剂量。本研究旨在评估PBPK模型预测单克隆抗体儿科暴露的能力。

使用了三种单克隆抗体进行模型开发和验证

贝伐单抗、英夫利昔单抗和阿特珠单抗。PBPK模型使用GastroPlus Biologics模块构建。对于每种单克隆抗体,基于健康和/或成年患者的观察数据开发PBPK模型。然后,对生理参数进行缩放以描述儿科生理学,以预测儿科人群的暴露情况。将预测的血浆浓度-时间过程与报告的观察数据进行叠加,以评估PBPK模型预测儿科暴露的能力。

结果表明,PBPK模型准确预测了单克隆抗体的儿科药代动力学。

这项研究标志着在验证使用PBPK模型预测儿童生物制品暴露的机械外推方法方面迈出了重要一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1aaa/12298552/36f0e4123506/pharmaceutics-17-00884-g001.jpg

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