生理药动学模型应用于治疗性抗体研究进展

Research Progress of the Application of Physiologically-based Pharmacokinetic Model in Therapeutic Antibodies

关键词:  治疗性抗体  生理药动学模型  药动学  新生儿Fc受体  靶点介导的药物处置

Key words:  therapeutic antibodies  physiologically-based pharmacokinetic model  pharmacokinetics  neonatal Fc receptor  target-mediated drug disposition

摘要:

目的 探讨生理药动学（physiologically-based pharmacokinetic，PBPK）模型在治疗性抗体中研究现状和应用前景。方法 结合近几年国内外相关文献，了解治疗性抗体药动学（pharmacokinetics，PK）的特点及影响因素，并对目前用于治疗性抗体的PBPK模型进行总结。分析不同情况下PBPK模型的建立和参数优化，以及需要考虑的重要生理过程[如新生儿Fc受体（neonatal Fc receptor，FcRn）介导的再循环、靶点介导的药物处置（target-mediated drug disposition，TMDD）等]。结果 治疗性抗体由于其特殊的结构和生物活性，与小分子药物相比，在体内吸收、分布、代谢和排泄等过程存在显著性差异，且在分子靶向治疗领域有明显的临床优势。而科学合理地使用PBPK模型，则有助于预测治疗性抗体在动物或者人体的PK变化，对开发其临床安全有效的治疗方案至关重要。结论 PBPK模型在治疗性抗体中的应用前景较广，需结合实际情况选择合适的模型结构，并通过模型验证和参数优化，不断提高PBPK模型的预测性能。

Abstract:

OBJECTIVE To explore the research status and application prospects of physiologically-based pharmacokinetic (PBPK) models in therapeutic antibodies. METHODS Referring to the relevant literature at home and abroad in recent years, this paper outlined the pharmacokinetics(PK) of antibodies and the influencing factors of PK, summarized the currently available PBPK models for therapeutic antibodies, and analyzed the establishment and parameter optimization of PBPK models under different scenarios, as well as important physiological processes to be considered, such as neonatal Fc receptor(FcRn) mediated recycling and target-mediated drug disposition(TMDD). RESULTS Due to their special structures and biological activities, therapeutic antibodies had significant differences in absorption, distribution, metabolism and excretion in vivo compared with small molecule drugs, and had apparent clinical advantages in the field of molecular targeted therapy. Scientifically and rationally applying the PBPK models might help predict the PK of therapeutic antibodies in animals or humans, which was essential for developing safe and effective therapeutic regimens. CONCLUSION PBPK modeling has a broad application prospect in therapeutic antibodies. It is necessary to utilize appropriate model structures based on actual conditions and constantly improve the prediction performance of PBPK models through model verification and parameter optimization.