Combined <i>In Vitro</i> and <i>In Silico</i> Workflow to Deliver Robust, Transparent, and Contextually Rigorous Models of Bioactivity

New approach methodologies (NAMs) are an increasing priority in the field of toxicology to fill data gaps and reduce time and resources in chemical safety assessment. We describe an NAMs workflow that integrates an in vitro high-throughput bioassay with an in silico computational model. In defining this workflow, we propose, as a crucial step of in silico development, the identification of explicit “purpose contexts”: a priori definitions of the scope and intent of an in silico solution, which provide natural targets for the mechanistic interpretation, validation, and output design of the model. By inspecting data from an in vitro assay measuring the displacement of fluorescent probe 8-anilino-1-naphthalenesulfonic acid (ANSA) from the serum transport protein transthyretin (TTR) as a proxy for potential disruption of thyroxine (T4) binding, in collaboration with the experimenters, we developed three relevant purpose contexts for this in silico modeling effort: (1) examination and confirmation of the in vitro assay principle via orthogonal information, (2) immediate integration with the in vitro experimental cycle to reduce costs and enhance hit rates, and (3) ultimate replacement of the use of single-concentration screening as a prioritization strategy for bioactivity testing of bulk chemical libraries. From these purpose contexts, we derived the foundations of a robust and transparent quantitative structure–activity relationship (QSAR) model that is constructively fit for purpose, characterized by first-principles mechanistic analysis, strict data quality evaluation, contextually rigorous performance testing and, finally, delivery of a quantitative recommendation schedule to simultaneously improve in vitro hit rates and in silico model learning potential.新方法学（NAMs）在毒理学领域日益受到重视，旨在填补数据空白、缩短化学品安全评估所需的时间与资源成本。本文介绍了一种整合体外（in vitro）高通量生物测定与计算机模拟（in silico）计算模型的NAMs工作流程。在构建该工作流程的过程中，我们提出将明确“目的情境”的识别作为计算机模拟开发的关键环节：即先验定义计算机模拟解决方案的适用范围与应用意图，为模型的机制阐释、验证与输出设计提供明确的靶向方向。本研究与实验人员合作，针对检测荧光探针8-苯胺基-1-萘磺酸（ANSA）从血清转运蛋白运甲状腺素蛋白（TTR）上解离情况的体外实验数据展开分析——该实验以检测甲状腺素（T4）结合潜在干扰为替代终点，最终为本次计算机模拟建模工作确立了三项相关目的情境：（1）通过正交信息验证体外实验的原理；（2）直接整合至体外实验流程，以降低成本并提升命中效率；（3）最终替代单浓度筛选策略，作为大规模化学品库生物活性测试的优先级筛选方案。基于上述目的情境，我们构建了兼具稳健性与透明度的定量构效关系（QSAR）模型框架，该模型贴合应用需求，具备以下特征：基于第一性原理的机制分析、严格的数据质量评估、符合情境的严谨性能测试，最终输出量化推荐方案，可同时提升体外实验命中效率与计算机模拟模型的学习潜力。