Laura Krumpholz, Aleksandra Klimczyk, Wiktoria Bieniek, Sebastian Polak, Barbara Wiśniowska
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引用次数: 0
摘要
体外-体内外推法是预测肝脏清除率的常用技术。目前有多种体外模型,如肝细胞、人肝微粒体或重组细胞色素 P450。根据游离药物理论,只有未结合部分(fu)的化学物质才能发生代谢变化。因此,为确保预测的可靠性,模型中的特异性和非特异性结合都应考虑在内。然而,实验中未结合的部分往往没有报告。本研究旨在提供一个详细的文献数据库,其中包括化合物在用于药物代谢评价的各种体外系统中的 fu 值以及相应的人体血浆结合水平。有关血浆和不同体外模型中游离部分的数据均附有以下信息:用于评估药物结合程度的实验方法、培养过程中的蛋白质或细胞浓度以及其他实验条件(如果与标准条件不同)、物种、来源出版物的参考文献以及作者姓名和发表日期。我们总共收集了 129 篇关于 1425 种不同化合物的文献研究。所提供的数据集可作为参与药代动力学/生理学药代动力学建模的科学家以及对基于化合物结构预测未结合部分的定量结构-活性关系模型感兴趣的研究人员的参考资料。数据库网址:https://data.mendeley.com/datasets/3bs5526htd/1.
Data set of fraction unbound values in the in vitro incubations for metabolic studies for better prediction of human clearance.
In vitro-in vivo extrapolation is a commonly applied technique for liver clearance prediction. Various in vitro models are available such as hepatocytes, human liver microsomes, or recombinant cytochromes P450. According to the free drug theory, only the unbound fraction (fu) of a chemical can undergo metabolic changes. Therefore, to ensure the reliability of predictions, both specific and nonspecific binding in the model should be accounted. However, the fraction unbound in the experiment is often not reported. The study aimed to provide a detailed repository of the literature data on the compound's fu value in various in vitro systems used for drug metabolism evaluation and corresponding human plasma binding levels. Data on the free fraction in plasma and different in vitro models were supplemented with the following information: the experimental method used for the assessment of the degree of drug binding, protein or cell concentration in the incubation, and other experimental conditions, if different from the standard ones, species, reference to the source publication, and the author's name and date of publication. In total, we collected 129 literature studies on 1425 different compounds. The provided data set can be used as a reference for scientists involved in pharmacokinetic/physiologically based pharmacokinetic modelling as well as researchers interested in Quantitative Structure-Activity Relationship models for the prediction of fraction unbound based on compound structure. Database URL: https://data.mendeley.com/datasets/3bs5526htd/1.