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预测儿童的正确剂量:基于计算的儿科生理药代动力学模型工具的作用。

Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools.

机构信息

College of Pharmacy, Hebei Medical University, Shijiazhuang, China.

出版信息

CPT Pharmacometrics Syst Pharmacol. 2023 Jan;12(1):13-26. doi: 10.1002/psp4.12883. Epub 2022 Nov 20.

Abstract

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

摘要

利用基于生理学的药代动力学(PBPK)模型可以预测特殊人群的药物药代动力学(PKs)和安全性。使用 PBPK 模型可以为儿科临床试验提供安全性保障,并加速新药研发进程,尤其是对于儿童这一临床试验相对困难的人群。本综述总结了过去 6 年来儿科 PBPK(P-PBPK)建模软件在剂量预测方面的作用,并简要介绍了一般 P-PBPK 建模的过程。我们总结了该软件的理论和应用,并讨论了该领域的应用趋势和未来展望。该建模软件的广泛应用无疑将使预测年轻患者的剂量预测变得更加容易。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e1b/9835135/1ca766153354/PSP4-12-13-g001.jpg

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