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浓度依赖性血液结合:以他克莫司为例,通过基于生理学的药代动力学模型评估其影响。

Concentration-dependent blood binding: assessing implications through physiologically based Pharmacokinetic modeling of tacrolimus as a case example.

作者信息

El-Khateeb Eman, Karsanji Deeyen, Darwich Adam S, Rostami-Hodjegan Amin

机构信息

Centre for Applied Pharmacokinetic Research (CAPKR), University of Manchester, Manchester, UK.

Certara Predictive Technologies (CPT), Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK.

出版信息

J Pharmacokinet Pharmacodyn. 2025 Sep 4;52(5):50. doi: 10.1007/s10928-025-09992-5.

Abstract

Concentration-dependent binding to red blood cells is a characteristic of several drugs, complicating the understanding of how pathophysiological factors influence drug behavior. This study utilized user-friendly, physiologically-based pharmacokinetic (PBPK) models to compare concentration-dependent and independent blood-to-plasma drug concentration ratios (B/P), using tacrolimus as a case study. Two models were developed and validated for tacrolimus using clinical data from healthy volunteers; Model 1 accounted for saturable blood binding, and Model 2 used a constant B/P level. The differences between the two models based on the two binding assumptions were also studied across clinically relevant hematocrit (HCT) and dose levels. For intravenous (IV) infusions, varying HCT from 15 to 45% resulted in a predicted difference in the area under the concentration-time curve (AUC) of 6-9% for total drug concentration in blood and 37-39% for unbound drug concentration in plasma. Increasing IV doses increased the predicted differences in blood AUC. For oral dosing to steady state, predicted differences in trough concentrations ranged between 50% and 130%, peak concentrations (78-284%), and AUC (up to 125%) according to HCT, dose, and biological medium, e.g., trough differences ranged from 50% (blood, 5 mg) to 130% (plasma, 10 mg). A hypothetical scenario of tacrolimus dose levels increasing above clinically relevant doses revealed a reducing difference in outcomes between the two binding assumptions. Although PBPK models ignoring concentration-dependent binding may adequately fit observed data, they can necessitate compensatory adjustments in disposition parameters, limiting their ability to predict clinical scenarios beyond the model's original development settings.

摘要

几种药物具有与红细胞浓度依赖性结合的特性,这使得理解病理生理因素如何影响药物行为变得复杂。本研究以他克莫司为例,利用用户友好的基于生理的药代动力学(PBPK)模型比较浓度依赖性和非依赖性血药与血浆药物浓度比(B/P)。使用健康志愿者的临床数据开发并验证了两种他克莫司模型;模型1考虑了饱和血药结合,模型2使用恒定的B/P水平。还在临床相关的血细胞比容(HCT)和剂量水平下研究了基于两种结合假设的两种模型之间的差异。对于静脉输注,将HCT从15% 变化到45% 导致血液中总药物浓度的浓度 - 时间曲线下面积(AUC)预测差异为6 - 9%,血浆中游离药物浓度的预测差异为37 - 39%。增加静脉剂量会增加血液AUC的预测差异。对于口服给药至稳态,根据HCT、剂量和生物介质,谷浓度的预测差异范围在50% 至130% 之间,峰浓度(78 - 284%)和AUC(高达125%),例如谷浓度差异范围从50%(血液,5mg)到130%(血浆,10mg)。他克莫司剂量水平增加到高于临床相关剂量的假设情景显示,两种结合假设之间的结果差异减小。尽管忽略浓度依赖性结合的PBPK模型可能充分拟合观察到的数据,但它们可能需要对处置参数进行补偿性调整,从而限制了它们预测超出模型原始开发设置的临床情景的能力。

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