Pharmacometric and statistical considerations for dose optimization.

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Palang Chotsiri, Prasert Yodsawat, Richard M Hoglund, Julie A Simpson, Joel Tarning
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Abstract

The probability of target attainment (PTA) is a common metric in drug dose optimization, but it requires a specific known target concentration threshold. Such target thresholds are not always available for some treatments, and patient and disease groups, particularly when treating children. This study performed pharmacokinetic and pharmacokinetic-pharmacodynamic (PKPD) simulations to explore different statistical approaches for determining the optimal dose for unknown PK and PKPD targets. To determine an optimal dose, PK and PKPD outcomes in typical patients with a standard adult dosing regimen were simulated and set as the reference profile, and compared to simulated outcomes for different dosing regimens in the population of interest. Statistical distances between the empirical cumulative distribution functions of the outcomes from all possible dosing regimens were calculated and compared to the reference profile. An optimal dose for known PK and PKPD target outcomes was selected to maintain the outcome above the assigned target, while optimal dosing in a population of interest with an unknown target was selected to generate equivalent PK and PKPD outcomes as the typical population. All of the dose optimization methods with commonly used PK and PKPD models and covariates were implemented as an open source freely available Shiny web-application. The developed pharmacometric method for dose optimization in populations with known and unknown target levels were robust and reproducible, and the implementation of a freely accessible Shiny web-application ensures widespread use and could be a useful tool for dose optimization in populations of interest.

剂量优化的药物计量学和统计学考虑因素。
达标概率(PTA)是药物剂量优化的常用指标,但它需要特定的已知目标浓度阈值。对于某些治疗方法、患者和疾病群体,尤其是在治疗儿童时,并不总是有这样的目标阈值。本研究进行了药代动力学和药代动力学-药效学(PKPD)模拟,以探索确定未知 PK 和 PKPD 目标最佳剂量的不同统计方法。为了确定最佳剂量,我们模拟了典型患者使用标准成人给药方案的 PK 和 PKPD 结果,并将其设定为参考曲线,然后与相关人群中不同给药方案的模拟结果进行比较。计算所有可能给药方案结果的经验累积分布函数之间的统计距离,并与参考曲线进行比较。针对已知的 PK 和 PKPD 目标结果选择最佳剂量,以将结果维持在指定目标之上,而针对未知目标的相关人群选择最佳剂量,以产生与典型人群相同的 PK 和 PKPD 结果。所有剂量优化方法与常用的 PK 和 PKPD 模型以及协变量都以开源免费的 Shiny 网络应用程序的形式实现。所开发的用于已知和未知目标水平人群剂量优化的药物计量学方法具有稳健性和可重复性,而免费提供的 Shiny 网络应用程序的实施确保了该方法的广泛使用,并可成为在相关人群中进行剂量优化的有用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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