TOXRIC: a comprehensive database of toxicological data and benchmarks
L Wu, B Yan, J Han, R Li, J Xiao, S He… - Nucleic Acids …, 2023 - academic.oup.com
The toxic effects of compounds on environment, humans, and other organisms have been a
major focus of many research areas, including drug discovery and ecological research …
major focus of many research areas, including drug discovery and ecological research …
Trade-off predictivity and explainability for machine-learning powered predictive toxicology: An in-depth investigation with Tox21 data sets
Selecting a model in predictive toxicology often involves a trade-off between prediction
performance and explainability: should we sacrifice the model performance to gain …
performance and explainability: should we sacrifice the model performance to gain …
toxCSM: comprehensive prediction of small molecule toxicity profiles
Drug discovery is a lengthy, costly and high-risk endeavour that is further convoluted by high
attrition rates in later development stages. Toxicity has been one of the main causes of …
attrition rates in later development stages. Toxicity has been one of the main causes of …
Machine learning toxicity prediction: latest advances by toxicity end point
CN Cavasotto, V Scardino - ACS omega, 2022 - ACS Publications
Machine learning (ML) models to predict the toxicity of small molecules have garnered great
attention and have become widely used in recent years. Computational toxicity prediction is …
attention and have become widely used in recent years. Computational toxicity prediction is …
ProTox 3.0: a webserver for the prediction of toxicity of chemicals
P Banerjee, E Kemmler, M Dunkel… - Nucleic Acids …, 2024 - academic.oup.com
Interaction with chemicals, present in drugs, food, environments, and consumer goods, is an
integral part of our everyday life. However, depending on the amount and duration, such …
integral part of our everyday life. However, depending on the amount and duration, such …
Machine learning based toxicity prediction: from chemical structural description to transcriptome analysis
Y Wu, G Wang - International journal of molecular sciences, 2018 - mdpi.com
Toxicity prediction is very important to public health. Among its many applications, toxicity
prediction is essential to reduce the cost and labor of a drug's preclinical and clinical trials …
prediction is essential to reduce the cost and labor of a drug's preclinical and clinical trials …
Machine learning and artificial intelligence in toxicological sciences
Abstract Machine learning and artificial intelligence approaches have revolutionized
multiple disciplines, including toxicology. This review summarizes representative recent …
multiple disciplines, including toxicology. This review summarizes representative recent …
Artificial intelligence in drug toxicity prediction: recent advances, challenges, and future perspectives
Toxicity prediction is a critical step in the drug discovery process that helps identify and
prioritize compounds with the greatest potential for safe and effective use in humans, while …
prioritize compounds with the greatest potential for safe and effective use in humans, while …
[HTML][HTML] Usage of model combination in computational toxicology
P Rodríguez-Belenguer, E March-Vila, M Pastor… - Toxicology Letters, 2023 - Elsevier
Abstract New Approach Methodologies (NAMs) have ushered in a new era in the field of
toxicology, aiming to replace animal testing. However, despite these advancements, they …
toxicology, aiming to replace animal testing. However, despite these advancements, they …
Molecular similarity-based predictions of the Tox21 screening outcome
To assess the toxicity of new chemicals and drugs, regulatory agencies require in vivo
testing for many toxic endpoints, resulting in millions of animal experiments conducted each …
testing for many toxic endpoints, resulting in millions of animal experiments conducted each …