Sipes Nisha S, Wambaugh John F, Pearce Robert, Auerbach Scott S, Wetmore Barbara A, Hsieh Jui-Hua, Shapiro Andrew J, Svoboda Daniel, DeVito Michael J, Ferguson Stephen S
National Toxicology Program, National Institute of Environmental Health Sciences , 111 T.W. Alexander Drive, Research Triangle Park, North Carolina 27709, United States.
National Center for Computational Toxicology, U.S. Environmental Protection Agency , 109 T.W. Alexander Drive, Research Triangle Park, North Carolina 27711, United States.
Environ Sci Technol. 2017 Sep 19;51(18):10786-10796. doi: 10.1021/acs.est.7b00650. Epub 2017 Sep 6.
In vitro-in vivo extrapolation (IVIVE) analyses translating high-throughput screening (HTS) data to human relevance have been limited. This study represents the first report applying IVIVE approaches and exposure comparisons using the entirety of the Tox21 federal collaboration chemical screening data, incorporating assay response efficacy and quality of concentration-response fits, and providing quantitative anchoring to first address the likelihood of human in vivo interactions with Tox21 compounds. This likelihood was assessed using a maximum blood concentration to in vitro response ratio approach (C/AC), analogous to decision-making methods for clinical drug-drug interactions. Fraction unbound in plasma (f) and intrinsic hepatic clearance (CL) parameters were estimated in silico and incorporated in a three-compartment toxicokinetic (TK) model to first predict C for in vivo corroboration using therapeutic scenarios. Toward lower exposure scenarios, 36 compounds of 3925 unique chemicals with curated activity in the HTS data using high-quality dose-response model fits and ≥40% efficacy gave "possible" human in vivo interaction likelihoods lower than median human exposures predicted in the United States Environmental Protection Agency's ExpoCast program. A publicly available web application has been designed to provide all Tox21-ToxCast dose-likelihood predictions. Overall, this approach provides an intuitive framework to relate in vitro toxicology data rapidly and quantitatively to exposures using either in vitro or in silico derived TK parameters and can be thought of as an important step toward estimating plausible biological interactions in a high-throughput risk-assessment framework.
将高通量筛选(HTS)数据转化为人体相关数据的体外-体内外推法(IVIVE)分析一直受到限制。本研究首次报告了应用IVIVE方法和暴露比较,使用了Tox21联邦合作化学筛选数据的全部内容,纳入了测定反应效力和浓度-反应拟合质量,并提供了定量锚定,以首先解决人体与Tox21化合物体内相互作用的可能性。使用最大血药浓度与体外反应比值法(C/AC)评估这种可能性,类似于临床药物相互作用的决策方法。通过计算机模拟估算血浆中未结合分数(f)和肝脏内在清除率(CL)参数,并将其纳入三室毒代动力学(TK)模型,以首先预测体内的C值,以便在治疗场景下进行体内验证。对于较低暴露场景,在HTS数据中具有良好活性且使用高质量剂量-反应模型拟合且效力≥40%的3925种独特化学物质中的36种化合物,其“可能”的人体体内相互作用可能性低于美国环境保护局ExpoCast计划预测的人体暴露中位数。已设计了一个公开可用的网络应用程序,以提供所有Tox21-ToxCast剂量可能性预测。总体而言,这种方法提供了一个直观的框架,可利用体外或计算机模拟得出的TK参数,将体外毒理学数据与暴露迅速且定量地联系起来,可被视为在高通量风险评估框架中估算合理生物相互作用的重要一步。