Computer Models of Chemical Activity
Using structural data to generate activity predictions for new or poorly characterized chemicals can help researchers and regulators make decisions about further testing needs.
|Open-source quantitative structure-property relationship tools||NICEATM and collaborators at EPA developed tools that use molecular structures to predict the physicochemical features for a wide range of substances.||
|Quantitative structure–activity relationship (QSAR) models to screen for potential skin sensitizers||NICEATM and collaborators at the University of North Carolina-Chapel Hill (UNC-CH) developed QSAR models of human data that can either be combined with or used instead of animal data to screen for potential skin sensitizers.||
|Open-source tools for predicting estrogen and androgen receptor pathway activity||NICEATM is creating open-source versions of published computational models to predict activity relevant to endocrine disruption. Predictions from these models are available through NICEATM's Integrated Chemical Environment (ICE) resource.||
|QSAR models to predict critical parameters for in vitro to in vivo extrapolation (IVIVE)||NICEATM—as part of an open-source workflow for IVIVE—is developing QSAR models to predict properties, such as solubility in oily vs. aqueous solutions, that affect how substances behave in biological systems.||In progress|
|QSAR models to predict estrogenic, anti-androgenic, and acute systemic toxicity||NICEATM and EPA ran three global collaborations to leverage the expertise of the world-wide modeling community to predict estrogenic activity (CERAPP project), anti-androgenic activity (CoMPARA project) and acute oral systemic toxicity (CATMoS project). Predictions from these models will be available through the EPA Chemistry Dashboard and as stand-alone applications.||In progress|