Emerging contaminants such as PFAS, PPCPs, EDCs, and heavy metals present complex challenges to U.S. drinking water systems, often evading conventional treatment and regulatory oversight. These in silico methods offer predictive capabilities for contaminant fate, toxicity, and transport, enabling high-throughput screening and mechanistic insight at molecular scales. Despite their scientific maturity, regulatory uptake remains limited due to lack of standardization, temporal misalignment with policy cycles, and poor scale translation to field-level applications. Approximately 41% of reviewed studies demonstrated policy relevance, interfacing with EPA programs such as ToxCast, UCMR, and TSCA. Systems thinking approaches, including Life-Cycle Assessment (LCA) and Integrated Assessment Models (IAMs), show promise in bridging molecular data with decision-making tools. The review advocates for transdisciplinary frameworks that align computational innovation with adaptive governance, emphasizing co-development, transparency, and regulatory receptivity. Advancing such integration is critical to modernizing environmental risk assessment and safeguarding public health amid increasing chemical complexity and infrastructure vulnerability.
Caesar et al. (Wed,) studied this question.