History of EPI Suite™ and future perspectives on chemical property estimation in US Toxic Substances Control Act new chemical risk assessments

TLDR

Chemical property estimation underpins the EPA’s risk assessment of the ~1000 annual new chemical pre‑manufacture notices, a process guided by the 1976 Toxic Substances Control Act and its 2016 amendments, and has evolved from early 19th‑century structure–activity correlations to modern, computer‑driven SAR models enabled by advances in computing and connectivity. EPA develops and refines predictive models—primarily housed in EPI Suite™—using publicly available data and quantitative structure–activity relationships to estimate the critical parameters needed for new chemical risk assessment. Over the past four decades, EPA has sporadically received chemical‑specific data with pre‑manufacture notices, and QSARs have shown both successes and failures while adapting to emerging trends.

Abstract

Chemical property estimation is a key component in many industrial, academic, and regulatory activities, including in the risk assessment associated with the approximately 1000 new chemical pre-manufacture notices the United States Environmental Protection Agency (US EPA) receives annually. The US EPA evaluates fate, exposure and toxicity under the 1976 Toxic Substances Control Act (amended by the 2016 Frank R. Lautenberg Chemical Safety for the 21st Century Act), which does not require test data with new chemical applications. Though the submission of data is not required, the US EPA has, over the past 40 years, occasionally received chemical-specific data with pre-manufacture notices. The US EPA has been actively using this and publicly available data to develop and refine predictive computerized models, most of which are housed in EPI Suite™, to estimate chemical properties used in the risk assessment of new chemicals. The US EPA develops and uses models based on (quantitative) structure-activity relationships ([Q]SARs) to estimate critical parameters. As in any evolving field, (Q)SARs have experienced successes, suffered failures, and responded to emerging trends. Correlations of a chemical structure with its properties or biological activity were first demonstrated in the late 19th century and today have been encapsulated in a myriad of quantitative and qualitative SARs. The development and proliferation of the personal computer in the late 20th century gave rise to a quickly increasing number of property estimation models, and continually improved computing power and connectivity among researchers via the internet are enabling the development of increasingly complex models.