基于生理学的药代动力学模型
体内
药代动力学
左旋多巴
生物信息学
最大值
药理学
药品
医学
体外
帕金森病
疾病
化学
内科学
生物
生物技术
基因
生物化学
作者
Erik Wollmer,Sandra Klein
标识
DOI:10.1016/j.ejpb.2022.09.015
摘要
Biorelevant in vitro release models are valuable analytical tools for oral drug development but often tailored to gastrointestinal conditions in 'average' healthy adults. However, predicting in vivo performance in individual patients whose gastrointestinal conditions do not match those of healthy adults would be of great value for optimizing oral drug therapy for such patients. This study focused on establishing patient-specific in vitro and in silico models to predict the in vivo performance of levodopa extended-release products in Parkinson's disease patients. Current knowledge on gastrointestinal conditions in these patients was incorporated into model development. Relevant in vivo pharmacokinetic data and patient-specific in vitro release data from a novel in vitro test setup were integrated into patient-specific physiologically-based pharmacokinetic models. AUC, cmax and tmax of the computed plasma profiles were calculated using PK-Sim®. For the products studied, levodopa plasma concentration-time profiles modeled using this novel approach compared far better with published average plasma profiles in Parkinson's disease patients than those derived from in vitro release data obtained from the 'average' healthy adult setup. Although further work is needed, results of this study highlight the importance of addressing patient-specific gastrointestinal conditions when aiming to predict drug release in such specific patient groups.
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