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药物物质浸出物和可提取物(E&Ls)的读值一致性方法的协调。

Harmonisation of read-across methodology for drug substance extractables and leachables (E&Ls).

机构信息

Gilead Sciences, Inc., Nonclinical Safety and Pathobiology (NSP), Foster City, CA, 94404, USA.

University of California Berkeley, Nutritional Sciences and Toxicology, Berkeley, CA, 94720, USA.

出版信息

Regul Toxicol Pharmacol. 2023 Dec;145:105494. doi: 10.1016/j.yrtph.2023.105494. Epub 2023 Sep 23.

DOI:10.1016/j.yrtph.2023.105494
PMID:37748702
Abstract

Health-based exposure limits (HBELs) are derived for leachables from polymeric components that interact with the drug substance which exceed a safety concern threshold (SCT). However, given the nature of leachables, there is not always chemical-specific toxicology data. Read-across methodology specific to extractables and leachables (E&Ls) was developed based on survey data collected from 11 pharmaceutical companies and methodology used in other industries. One additional challenge for E&L read-across is most toxicology data is from the oral route of administration, whereas the parenteral route is very common for the leachable HBEL derivation. A conservative framework was developed to estimate oral bioavailability and the corresponding oral to parenteral extrapolation factor using physical chemical data. When this conservative framework was tested against 73 compounds with oral bioavailability data, it was found that the predicted bioavailability based on physico-chemical properties was conservatively greater than or equal to the experimental bioavailability 79% of the time. In conclusion, an E&L read-across methodology has been developed to provide a consistent, health protective framework for deriving HBELs when toxicology data is limited.

摘要

基于健康的暴露限值 (HBEL) 是针对与药物物质相互作用的聚合物成分中的可浸出物制定的,这些可浸出物超过了安全关注阈值 (SCT)。然而,鉴于可浸出物的性质,并不总是有针对具体化学物质的毒理学数据。根据从 11 家制药公司收集的调查数据和其他行业使用的方法,专门为可提取物和可浸出物 (E&Ls) 开发了读取方法。E&L 读取的另一个挑战是,大多数毒理学数据来自口服途径,而可浸出物 HBEL 推导中经常使用的是肠胃外途径。开发了一个保守的框架,以使用物理化学数据估算口服生物利用度和相应的口服到肠胃外外推因子。当将该保守框架与具有口服生物利用度数据的 73 种化合物进行测试时,发现基于物理化学性质预测的生物利用度在 79%的时间内保守地大于或等于实验生物利用度。总之,当毒理学数据有限时,已经开发了一种 E&L 读取方法,为推导 HBEL 提供了一致的、保护健康的框架。

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