Genetic Toxicity
Genetic Toxicity Expert Alert Suite
The model uses data from bacterial mutation tests, specifically the Salmonella typhimurium histidine reversion gene mutation test. It includes various tester strains such as TA97, TA97a, TA1537, TA98, TA100, TA1535, TA102, and E. coli.
The model combines results from multiple bacterial strains to predict mutagenicity. The predictions are based on the structural features of the chemical being analyzed.
Genetic Toxicity Suite (Statistical)
The suite includes models for bacterial mutation tests, mammalian cell mutation tests, and chromosomal aberration tests.
These models analyze the chemical structure and predict potential genetic toxicity based on known data.
Irritation and Sensitization
Local Lymph Node Assay (LLNA): This model predicts the results of the Local Lymph Node Assay, which is an accepted test for assessing skin sensitization potential. The model uses data from various LLNA studies to predict the sensitizing potential of chemicals.
Human Data-Based Models: These models use data from human patch tests and other clinical studies to predict skin sensitization potential in humans, based on historical data.
ECETOC Categories: The service includes models to predict ECETOC (European Centre for Ecotoxicology and Toxicology of Chemicals) categories, which classify chemicals based on their sensitizing potential.
Integrated Hazard Assessment: The platform integrates multiple models and data sources to provide a comprehensive hazard assessment for skin sensitization. This approach combines data from in vitro, in vivo, and human studies to enhance the accuracy and reliability of the predictions.
Systemic Toxicity
Acute Oral Toxicity Model: This model predicts the acute oral toxicity of chemicals based on data from various oral toxicity studies. It provides insights into the potential toxic effects of chemicals when ingested.
Acute Inhalation Toxicity Model: This model predicts the acute inhalation toxicity of chemicals using data from inhalation studies. It assesses the potential toxic effects of chemicals when inhaled.
Acute Dermal Toxicity Model: This model predicts the acute dermal toxicity of chemicals based on data from dermal toxicity studies. It evaluates the potential toxic effects of chemicals when they come into contact with the skin.
Rodent Carcinogenicity Suite: This suite includes models that predict the carcinogenicity of chemicals based on long-term rodent studies. It analyzes data from both mice and rats to provide comprehensive predictions.
SAR Carcinogenicity Database: The software includes a SAR (Structure-Activity Relationship) Carcinogenicity Database, integrated with Leadscope (Q)SAR models to enhance the accuracy and reliability of the predictions.
FDA Models: The software includes models developed in collaboration with FDA scientists based on both proprietary and non-proprietary data. These models are designed to predict the potential carcinogenicity of pharmaceuticals, cosmetics, food ingredients, and other chemicals.
Reproductive Toxicity Suite: This suite includes models that predict the reproductive toxicity of chemicals based on data from various reproductive toxicity studies. It covers endpoints such as fertility, reproductive performance, and effects on offspring.
Developmental Toxicity Suite: This suite includes models that predict the developmental toxicity of chemicals based on data from various developmental toxicity studies. It covers endpoints such as teratogenicity, embryotoxicity, and effects on fetal development.
Organ-Specific Toxicity
Human Adverse Cardiac Effects Model: This model predicts the potential toxic effects of chemicals on the heart. It uses data from cardiotoxicity studies to assess the risk of adverse cardiac events.
Human Adverse Hepatobiliary Effects Model: This model predicts the potential toxic effects of chemicals on the liver and biliary system. It uses data from various hepatotoxicity studies to provide insights into the potential liver damage caused by chemicals.
Neurotoxicity Model: This model predicts the potential toxic effects of chemicals on the nervous system. It uses data from neurotoxicity studies to assess the risk of adverse neurological effects.
Environmental Toxicity
Acute Daphnia magna Model: This model predicts the acute toxicity of chemicals to Daphnia magna, a common freshwater invertebrate used in ecotoxicity testing. It uses data from short-term toxicity studies to assess the potential impact of chemicals on aquatic invertebrates.
Fish Acute Toxicity Model: This model predicts the acute toxicity of chemicals to fish species. It uses data from various fish toxicity studies to evaluate the potential harmful effects of chemicals on aquatic life.
Algal Toxicity Model: This model predicts the toxicity of chemicals to algae, which are primary producers in aquatic ecosystems. It uses data from algal growth inhibition studies to assess the potential impact of chemicals on algal populations.
Soil Organism Toxicity Model: This model predicts the toxicity of chemicals to soil organisms such as earthworms and soil microbes. It uses data from soil toxicity studies to evaluate the potential harmful effects of chemicals on terrestrial ecosystems.