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

Abstract

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.