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 …

Trade-off predictivity and explainability for machine-learning powered predictive toxicology: An in-depth investigation with Tox21 data sets

L Wu, R Huang, IV Tetko, Z Xia, J Xu… - Chemical research in …, 2021 - ACS Publications
Selecting a model in predictive toxicology often involves a trade-off between prediction
performance and explainability: should we sacrifice the model performance to gain …

toxCSM: comprehensive prediction of small molecule toxicity profiles

AGC de Sá, Y Long, S Portelli, DEV Pires… - Briefings in …, 2022 - academic.oup.com
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 …

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 …

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 …

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 …

Machine learning and artificial intelligence in toxicological sciences

Z Lin, WC Chou - Toxicological Sciences, 2022 - academic.oup.com
Abstract Machine learning and artificial intelligence approaches have revolutionized
multiple disciplines, including toxicology. This review summarizes representative recent …

Artificial intelligence in drug toxicity prediction: recent advances, challenges, and future perspectives

TTV Tran, A Surya Wibowo, H Tayara… - Journal of chemical …, 2023 - ACS Publications
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 …

[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 …

Molecular similarity-based predictions of the Tox21 screening outcome

MN Drwal, VB Siramshetty, P Banerjee… - Frontiers in …, 2015 - frontiersin.org
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 …