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利用文献中的生理数据构建药代动力学模型,为孕妇有意义的临床研究设计提供支持。

Leveraging physiological data from literature into a pharmacokinetic model to support informative clinical study design in pregnant women.

机构信息

Department of Pharmacy and Pharmacology, Netherlands Cancer Institute/Slotervaart Hospital, Louwesweg 6, PO Box 90440, 1006 BK, Amsterdam, The Netherlands.

出版信息

Pharm Res. 2012 Jun;29(6):1609-17. doi: 10.1007/s11095-012-0671-2. Epub 2012 Jan 13.

Abstract

PURPOSE

Physiological changes during pregnancy can effect pharmacokinetic (PK) parameters, which may lead to altered dose requirements. We aimed to leverage literature-based physiological changes during pregnancy into a PK model and compare its performance to a published reference model in pregnant women and to use the literature-based model to determine informative PK sampling times for a clinical study that aims to quantify the PK of enoxaparin throughout pregnancy.

METHODS

Changes in total body water (BW) and creatinine clearance (CRCL) during pregnancy were described using regression models. BW and CRCL were linked to a PK model of enoxaparin in non-pregnant women. Performance of the literature-based PK model was compared to a previously published empirical reference model. D-optimal sampling times were determined and evaluated for literature-based and reference models.

RESULTS

The literature-based model adequately predicted anti-Xa plasma concentrations when compared to reference model predictions. An informative sampling design was successfully developed, with parameters expected with good precision (RSE < 36.4%).

CONCLUSION

A literature-based model describing enoxaparin PK during pregnancy was developed and evaluated. The modelling framework could be used to support development of informative designs in pregnancy when prior models are unavailable.

摘要

目的

妊娠期间的生理变化会影响药代动力学(PK)参数,从而导致剂量需求改变。我们旨在利用妊娠期间基于文献的生理变化来构建 PK 模型,并将其与已发表的妊娠女性参考模型进行比较,以及利用基于文献的模型来确定一个临床研究的信息性 PK 采样时间,该研究旨在定量评估依诺肝素在整个妊娠期间的 PK。

方法

使用回归模型描述妊娠期间总体液(BW)和肌酐清除率(CRCL)的变化。将 BW 和 CRCL 与非妊娠女性的依诺肝素 PK 模型联系起来。将基于文献的 PK 模型的性能与先前发表的经验参考模型进行比较。确定并评估基于文献和参考模型的 D-最优采样时间。

结果

与参考模型预测相比,基于文献的模型能够充分预测抗 Xa 血浆浓度。成功开发了一种信息性采样设计,具有良好精度(RSE < 36.4%)的预期参数。

结论

开发并评估了一种描述妊娠期间依诺肝素 PK 的基于文献的模型。当没有先前的模型时,该建模框架可用于支持妊娠期间信息性设计的开发。

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