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利用蒙特卡罗模拟和药代动力学-药效学目标的考虑因素支持抗菌药物剂量选择。

Use of Monte Carlo simulation and considerations for PK-PD targets to support antibacterial dose selection.

机构信息

The Institute for Clinical Pharmacodynamics, Inc, Schenectady, NY, United States.

The Medicines Company, San Diego, CA, United States.

出版信息

Curr Opin Pharmacol. 2017 Oct;36:107-113. doi: 10.1016/j.coph.2017.09.009. Epub 2017 Nov 10.

Abstract

Monte Carlo simulation is used to generate data for pharmacokinetic-pharmacodynamic (PK-PD) target attainment analyses to assess antibacterial dosing regimens in early and late stage drug development. Careful consideration of the quality of data for pharmacokinetics, non-clinical PK-PD targets for efficacy, the choice of the bacterial reduction endpoint upon which the PK-PD target is based, variability in the PK-PD target, and effect site exposures ensures optimal dose selection. Relationships between drug exposure and efficacy and/or safety endpoints based on clinical data can also be applied to simulated data to support dose selection. These in silico analyses, conducted throughout drug development, provide the greatest opportunity to de-risk the development of antibacterial agents.

摘要

蒙特卡罗模拟用于生成药代动力学-药效学(PK-PD)目标达成分析的数据,以评估药物开发早期和晚期的抗菌药物给药方案。在进行 PK-PD 目标的药代动力学数据、非临床 PK-PD 疗效靶标、基于 PK-PD 目标的细菌减少终点选择、PK-PD 目标变异性以及效应部位暴露的质量方面,需要仔细考虑,以确保最佳的剂量选择。基于临床数据的药物暴露与疗效和/或安全性终点之间的关系也可以应用于模拟数据,以支持剂量选择。这些在药物开发过程中进行的计算分析为降低抗菌药物开发风险提供了最大的机会。

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