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

• Published in: Environmental science--processes & impacts Vol. 19; no. 3; p. 203
• Main Authors: Card, Marcella L, Gomez-Alvarez, Vicente, Lee, Wen-Hsiung, Lynch, David G, Orentas, Nerija S, Lee, Mari Titcombe, Wong, Edmund M, Boethling, Robert S
• Format: Journal Article
• Language: English
• Published: England 22-03-2017
• Subjects: Animals; Chemical Industry - legislation & jurisprudence; Environmental Pollutants - chemistry; Environmental Pollutants - toxicity; Government Regulation; Hazardous Substances - chemistry; Hazardous Substances - toxicity; Humans; Models, Theoretical; Predictive Value of Tests; Quantitative Structure-Activity Relationship; Risk Assessment; United States; United States Environmental Protection Agency
• ISSN: 2050-7895
• DOI: 10.1039/c7em00064b

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 21
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 19
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 20
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.