首页> 外文期刊>British Journal of Clinical Pharmacology >A pregnancy physiologically based pharmacokinetic (p-PBPK) model for disposition of drugs metabolized by CYP1A2, CYP2D6 and CYP3A4
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A pregnancy physiologically based pharmacokinetic (p-PBPK) model for disposition of drugs metabolized by CYP1A2, CYP2D6 and CYP3A4

机译:基于妊娠生理学的药代动力学(p-PBPK)模型,用于处理被CYP1A2,CYP2D6和CYP3A4代谢的药物

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Aims: Pregnant women are usually not part of the traditional drug development programme. Pregnancy is associated with major biological and physiological changes that alter the pharmacokinetics (PK) of drugs. Prediction of the changes to drug exposure in this group of patients may help to prevent under- or overtreatment. We have used a pregnancy physiologically based pharmacokinetic (p-PBPK) model to assess the likely impact of pregnancy on three model compounds, namely caffeine, metoprolol and midazolam, based on the knowledge of their disposition in nonpregnant women and information from in vitro studies. Methods: A perfusion-limited form of a 13-compartment full-PBPK model (Simcyp? Simulator) was used for the nonpregnant women, and this was extended to the pregnant state by applying known changes to all model components (including the gestational related activity of specific cytochrome P450 enzymes) and through the addition of an extra compartment to represent the fetoplacental unit. The uterus and the mammary glands were grouped into the muscle compartment. The model was implemented in Matlab Simulink and validated using clinical observations. Results: The p-PBPK model predicted the PK changes of three model compounds (namely caffeine, metoprolol and midazolam) for CYP1A2, CYP2D6 and CYP3A4 during pregnancy within twofold of observed values. The changes during the third trimester were predicted to be a 100% increase, a 30% decrease and a 35% decrease in the exposure of caffeine, metoprolol and midazolam, respectively, compared with the nonpregnant women. Conclusions: In the absence of clinical data, the in silico prediction of PK behaviour during pregnancy can provide a valuable aid to dose adjustment in pregnant women. The performance of the model for drugs metabolized by a single enzyme to different degrees (high and low extraction) and for drugs that are eliminated by several different routes warrants further study.
机译:目的:孕妇通常不属于传统药物开发计划的一部分。怀孕与改变药物的药代动力学(PK)的主要生物学和生理变化有关。预测该组患者的药物暴露变化可能有助于防止治疗不足或过度治疗。我们已经基于怀孕生理学上的药代动力学(p-PBPK)模型,基于对孕妇中非咖啡因的了解以及来自体外研究的信息,评估了怀孕对三种模型化合物(咖啡因,美托洛尔和咪达唑仑)的可能影响。方法:对非孕妇使用13室全PBPK模型(Simcyp?Simulator)的灌注受限形式,并通过对所有模型成分(包括妊娠相关活动)进行已知更改,将其扩展至怀孕状态特定的细胞色素P450酶),并通过添加一个额外的区室来代表胎盘素单元。子宫和乳腺被分为肌肉隔室。该模型在Matlab Simulink中实现,并使用临床观察进行了验证。结果:p-PBPK模型预测怀孕期间CYP1A2,CYP2D6和CYP3A4三种模型化合物(即咖啡因,美托洛尔和咪达唑仑)的PK变化在观察值的两倍范围内。与未怀孕的妇女相比,咖啡因,美托洛尔和咪达唑仑的暴露率在孕晚期的变化预计分别增加100%,减少30%和减少35%。结论:在缺乏临床数据的情况下,对怀孕期间PK行为的计算机模拟可为孕妇调整剂量提供有价值的帮助。对于由单一酶代谢至不同程度(高提取和低提取)的药物以及通过几种不同途径消除的药物,该模型的性能值得进一步研究。

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