The Tox21 10K compound library: collaborative chemistry advancing toxicology

AM Richard, R Huang, S Waidyanatha… - Chemical Research …, 2020 - ACS Publications
Since 2009, the Tox21 project has screened∼ 8500 chemicals in more than 70 high-
throughput assays, generating upward of 100 million data points, with all data publicly …

An integrated assessment of ecological and human health risks of per-and polyfluoroalkyl substances through toxicity prediction approaches

N Hamid, M Junaid, R Manzoor, M Sultan… - Science of The Total …, 2023 - Elsevier
Per-and polyfluoroalkyl substances (PFAS) are also known as “forever chemicals” due to
their persistence and ubiquitous environmental distribution. This review aims to summarize …

Machine learning: new ideas and tools in environmental science and engineering

S Zhong, K Zhang, M Bagheri, JG Burken… - … science & technology, 2021 - ACS Publications
The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …

Ferric oxide nanoclusters with low-spin FeIII anchored g-C3N4 rod for boosting photocatalytic activity and degradation of diclofenac in water under solar light

F Li, T Huang, F Sun, L Chen, P Li, F Shao… - Applied Catalysis B …, 2022 - Elsevier
Fe 2 O 3, as an earth-abundant photocatalyst for water purification, has attracted great
attention. However, the high-spin Fe III in traditional Fe 2 O 3 restricts its catalytic …

Framework for identifying chemicals with structural features associated with the potential to act as developmental or reproductive toxicants

S Wu, J Fisher, J Naciff, M Laufersweiler… - Chemical Research …, 2013 - ACS Publications
Developmental and reproductive toxicity (DART) end points are important hazard end points
that need to be addressed in the risk assessment of chemicals to determine whether or not …

A Comprehensive Statistical Analysis of Predicting In Vivo Hazard Using High-Throughput In Vitro Screening

RS Thomas, MB Black, L Li, E Healy… - Toxicological …, 2012 - academic.oup.com
Over the past 5 years, increased attention has been focused on using high-throughput in
vitro screening for identifying chemical hazards and prioritizing chemicals for additional in …

Machine learning and artificial intelligence: a paradigm shift in big data-driven drug design and discovery

P Pasrija, P Jha, P Upadhyaya… - Current Topics in …, 2022 - benthamdirect.com
Background: The lengthy and expensive process of developing a novel medicine often takes
many years and entails a significant financial burden due to its poor success rate …

TIRESIA: an explainable artificial intelligence platform for predicting developmental toxicity

MV Togo, F Mastrolorito, F Ciriaco… - Journal of Chemical …, 2022 - ACS Publications
Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is
presented, which allows prediction of developmental toxicity, a challenging human-health …

Making sense of chemical space network shows signs of criticality

N Amoroso, N Gambacorta, F Mastrolorito, MV Togo… - Scientific Reports, 2023 - nature.com
Chemical space modelling has great importance in unveiling and visualising latent
information, which is critical in predictive toxicology related to drug discovery process. While …

Catalytic activation of formic acid using Pd nanocluster decorated graphitic carbon nitride for diclofenac reductive hydrodechlorination

F Shao, Y Gao, W Xu, F Sun, L Chen, F Li… - Journal of Hazardous …, 2023 - Elsevier
Halogenated pharmaceuticals exhibit high toxicity if released to natural environment, and
dehalogenation is a key process for their degradation. In this study, a reductive and …