在药代动力学模型中整合早期反应生物标志物:克罗恩病患者英夫利昔单抗初始个体化剂量的新方法

IF 3.1 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Abigail Samuels, Kei Irie, Tomoyuki Mizuno, Jack Reifenberg, Nieko Punt, Alexander A. Vinks, Phillip Minar
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引用次数: 0

摘要

使用模型信息精确给药来个性化英夫利昔单抗已被证明可以改善维持期间浓度目标的获取和临床结果。当前英夫利昔单抗药代动力学模型的迭代包括药物清除的时变协变量,然而,不考虑协变量的预期改善可能导致滥用更高的英夫利昔单抗剂量和不精确的药物暴露。目的是确定与英夫利昔单抗清除率相关的四种生物标志物的变化(Xiong等模型),并确定这些动态变化的整合是否会改善诱导和早期维持期间的模型性能。我们分析了两组接受英夫利昔单抗治疗克罗恩病的儿童。采用Emax方法评估协变量的时变变化。使用中位数百分比误差(偏倚)和中位数绝对百分比误差(精度)评估模型性能(观察到的与预测的英夫利昔单抗浓度)。合并队列包括239名克罗恩病患者。我们发现,从基线到剂量4,体重、白蛋白、红细胞沉降率和中性粒细胞CD64的最大变化分别为4.7%、+11.7%、- 62.4%和- 26.5%。我们还发现,单独使用基线协变量预测未来谷浓度的效果不如Emax时变方法,但在偏倚(剂量2、3和4)和精度(剂量2和4)方面有显著改善。将药物清除的四种时变生物标志物与药代动力学建模相结合,提高了预测的准确性和精度。这种新策略可能是改善药物暴露,最大限度地减少滥用剂量策略和降低医疗成本的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrating early response biomarkers in pharmacokinetic models: A novel method to individualize the initial infliximab dose in patients with Crohn's disease

Integrating early response biomarkers in pharmacokinetic models: A novel method to individualize the initial infliximab dose in patients with Crohn's disease

The use of model-informed precision dosing to personalize infliximab has been shown to improve both the acquisition of concentration targets and clinical outcomes during maintenance. Current iterations of infliximab pharmacokinetic models include time-varying covariates of drug clearance, however, not accounting for the expected improvements in the covariates can lead to indiscriminate use of higher infliximab doses and imprecise drug exposure. The aim was to identify changes in the four biomarkers associated with infliximab clearance (Xiong et al. model) and determine if integration of these dynamic changes would improve model performance during induction and early maintenance. We analyzed two cohorts of children receiving infliximab for Crohn's Disease. The Emax method was used to assess time-varying changes in covariates. Model performance (observed vs. predicted infliximab concentrations) was evaluated using median percentage error (bias) and median absolute percentage error (precision). The combined cohorts included 239 Crohn's disease patients. We found from baseline to dose 4, the maximum changes in weight, albumin, erythrocyte sedimentation rate, and neutrophil CD64 were 4.7%, +11.7%, −62.4%, and −26.5%, respectively. We also found the use of baseline covariates alone to forecast future trough concentration was inferior to the Emax time-varying method with a significant improvement observed in bias (doses 2, 3, and 4) and precision (doses 2 and 4). The integration of the four time-varying biomarkers of drug clearance with pharmacokinetic modeling improved the accuracy and precision of the predictions. This novel strategy may be key to improving drug exposure, minimizing indiscriminate dosing strategies, and reducing healthcare costs.

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来源期刊
Cts-Clinical and Translational Science
Cts-Clinical and Translational Science 医学-医学:研究与实验
CiteScore
6.70
自引率
2.60%
发文量
234
审稿时长
6-12 weeks
期刊介绍: Clinical and Translational Science (CTS), an official journal of the American Society for Clinical Pharmacology and Therapeutics, highlights original translational medicine research that helps bridge laboratory discoveries with the diagnosis and treatment of human disease. Translational medicine is a multi-faceted discipline with a focus on translational therapeutics. In a broad sense, translational medicine bridges across the discovery, development, regulation, and utilization spectrum. Research may appear as Full Articles, Brief Reports, Commentaries, Phase Forwards (clinical trials), Reviews, or Tutorials. CTS also includes invited didactic content that covers the connections between clinical pharmacology and translational medicine. Best-in-class methodologies and best practices are also welcomed as Tutorials. These additional features provide context for research articles and facilitate understanding for a wide array of individuals interested in clinical and translational science. CTS welcomes high quality, scientifically sound, original manuscripts focused on clinical pharmacology and translational science, including animal, in vitro, in silico, and clinical studies supporting the breadth of drug discovery, development, regulation and clinical use of both traditional drugs and innovative modalities.
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