Use of Monte Carlo simulation and considerations for PK-PD targets to support antibacterial dose selection
Use of Monte Carlo simulation and considerations for PK-PD targets to support antibacterial dose selection
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DOI：
10.1016/j.coph.2017.09.009
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发表时间：
2017-10-01
影响因子：
4
通讯作者：
Bhavnani, Sujata M.
中科院分区：
文献类型：
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作者：
Trang, Michael;Dudley, Michael N.;Bhavnani, Sujata M.
蒙特卡罗模拟被用来产生药代动力学药效学(PK-PD)目标达标率分析的数据，以评估药物开发早期和晚期的抗菌剂量方案。仔细考虑药代动力学的数据质量、疗效的非临床PK-PD目标、PK-PD目标所基于的细菌减少终点的选择、PK-PD目标的可变性以及作用部位的暴露确保最佳剂量选择。基于临床数据的药物暴露与疗效和/或安全终点之间的关系也可应用于模拟数据以支持剂量选择。这些在整个药物开发过程中进行的计算机分析，为降低抗菌剂开发的风险提供了最大的机会。
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.