Gnarus Systems is pleased to offer cat-SAR; a peer-reviewed in silico toxicity prediction expert system. The cat-SAR system associates 2-dimensional chemical fragments with active or inactive compounds in a learning set. Unlike many other approaches, cat-SAR is transparent and model parameter selection is controlled by the user. As such, the approach is sharable and allows unrestricted user scrutiny, intervention and model optimization throughout the SAR modeling process. This rationale negates any a priori requirements that a given set of data must fit the attributes of a predefined and often proprietary modeling process.
The cat-SAR system essentially “learns” about the biological activity of chemicals by analyzing “learning sets” of data. These are endpoint specific databases of toxicological or pharmacological chemical activity (e.g., carcinogens and developmental toxicants) that are assembled by us or others. Currently, we have validated and usable learning sets for a variety of health endpoints including cancer, anticancer, genotoxicity, developmental toxicity, and chemical allergy.
Currently, cat‐SAR models are available for:
Rats, mice, and rodents carcinogenesis including gender-specific submodels
Mammary Cancer in Rodents
Tissue/organ specific carcinogenesis for 12 tumor types
Salmonella mutagenicity (i.e. the Ames Assay)
Allergic Contact Dermatitis
Mouse Local Lymph Node Assay
Estrogen mimics based on the E-SCREEN assay
Anticancer activity to several different breast cancer cell lines
Develop user-specific computational (predictive models) and screen large natural product or synthetic chemical libraries for potentially active compounds.
Fragment-based structure-activity relationship (SAR) model and OECD Toolbox expertise for REACH/TSCA reporting requirement including QMRF/QPRF reports.
Fragment-based structure-activity relationship (SAR) model for Salmonella Mutagenicity (Ames) Assay
Structure-activity relationship (SAR) models for cancer based on National Toxicology Program (NTP) and Carcinogenic Potency Database (CPDB) cancer data for rats and mice. Additional models for non-mutagenic/non-genotoxic carcinogens, gender-specific, and organ-selective endpoints models are available.
Fragment-based structure-activity relationship (SAR) model for Allergic Contact Dermatitis (ACD) and Mouse Local Lymph Node Assay (LLNA).
Structure-activity relationship (SAR) models based on data developed in the Draize Eye Test
• Quantitative structure-activity relationship (QSAR) studies on pharmacophores or series of congeneric chemicals in order to optimize molecular targeting, enhance biological activity, or minimizing toxicity.
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