VEGA-QSAR: AI Inside a Platform for Predictive Toxicology
نویسندگان
چکیده
Computer simulation and predictive models are widely used in engineering, much less considered in life sciences. We present an initiative aimed to establish a dialogue within the community of scientists, regulators, industry representatives, offering a platform which combines the predictive capability of computer models, with some explanation tools, which may be convincing and helpful for human users to derive a conclusion. The resulting system covers a large set of toxicological endpoints.
منابع مشابه
Predicting modes of toxic action from chemical structure: an overview.
In the field of environmental toxicology, and especially aquatic toxicology, quantitative structure activity relationships (QSARs) have developed as scientifically-credible tools for predicting the toxicity of chemicals when little or no empirical data are available. A basic and fundamental understanding of toxicological principles has been considered crucial to the continued acceptance and app...
متن کاملApproaches to developing alternative and predictive toxicology based on PBPK/PD and QSAR modeling.
Systematic toxicity testing, using conventional toxicology methodologies, of single chemicals and chemical mixtures is highly impractical because of the immense numbers of chemicals and chemical mixtures involved and the limited scientific resources. Therefore, the development of unconventional, efficient, and predictive toxicology methods is imperative. Using carcinogenicity as an end point, w...
متن کاملArtificial Neural Networks as Statistical Tools in SAR/QSAR Modeling
There are two broadly-defined applications of artificial neural networks (ANNs) in SAR/QSAR modeling. The first is the use of networks as preprocessors to reduce the dimensionality of chemical descriptors for use in statistical or network models. The second is to create classification models for predictive toxicology. This report discusses the use of ANNs as classifiers in SAR/QSAR modeling and...
متن کاملPredictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data.
Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors ...
متن کاملPredictive QSAR Models for the Toxicity of Disinfection Byproducts.
Several hundred disinfection byproducts (DBPs) in drinking water have been identified, and are known to have potentially adverse health effects. There are toxicological data gaps for most DBPs, and the predictive method may provide an effective way to address this. The development of an in-silico model of toxicology endpoints of DBPs is rarely studied. The main aim of the present study is to de...
متن کامل