An overview of machine learning and big data for drug toxicity evaluation

AH Vo, TR Van Vleet, RR Gupta… - Chemical research in …, 2019 - ACS Publications
Drug toxicity evaluation is an essential process of drug development as it is reportedly
responsible for the attrition of approximately 30% of drug candidates. The rapid increase in …

Open Targets Platform: supporting systematic drug–target identification and prioritisation

D Ochoa, A Hercules, M Carmona… - Nucleic acids …, 2021 - academic.oup.com
Abstract The Open Targets Platform (https://www. targetvalidation. org/) provides users with
a queryable knowledgebase and user interface to aid systematic target identification and …

[HTML][HTML] Using chemical and biological data to predict drug toxicity

A Liu, S Seal, H Yang, A Bender - SLAS Discovery, 2023 - Elsevier
Various sources of information can be used to better understand and predict compound
activity and safety-related endpoints, including biological data such as gene expression and …

Large-scale RNAi screening uncovers therapeutic targets in the parasite Schistosoma mansoni

J Wang, C Paz, G Padalino, A Coghlan, Z Lu… - Science, 2020 - science.org
Schistosome parasites kill 250,000 people every year. Treatment of schistosomiasis relies
on the drug praziquantel. Unfortunately, a scarcity of molecular tools has hindered the …

[HTML][HTML] Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients

MP Dent, E Vaillancourt, RS Thomas… - Regulatory Toxicology …, 2021 - Elsevier
Next generation risk assessment (NGRA) is an exposure-led, hypothesis-driven approach
that has the potential to support animal-free safety decision-making. However, significant …

Today's challenges to de-risk and predict drug safety in human “mind-the-gap”

RJ Weaver, JP Valentin - Toxicological Sciences, 2019 - academic.oup.com
Current gaps in drug safety sciences can result from the inability (1) to identify hazard across
multiple target organs,(2) to predict and risk assess with certainty against drug safety …

[HTML][HTML] Novel computational approach to predict off-target interactions for small molecules

MS Rao, R Gupta, MJ Liguori, M Hu, X Huang… - Frontiers in big …, 2019 - frontiersin.org
Most small molecule drugs interact with unintended, often unknown, biological targets and
these off-target interactions may lead to both preclinical and clinical toxic events. Undesired …

[HTML][HTML] Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology

R Ietswaart, S Arat, AX Chen, S Farahmand, B Kim… - …, 2020 - thelancet.com
Abstract Background Adverse drug reactions (ADRs) are one of the leading causes of
morbidity and mortality in health care. Understanding which drug targets are linked to ADRs …

Safety screening in early drug discovery: an optimized assay panel

S Bendels, C Bissantz, B Fasching, G Gerebtzoff… - … of pharmacological and …, 2019 - Elsevier
Background Several factors contribute to the development failure of novel pharmaceuticals,
one of the most important being adverse effects in pre-clinical and clinical studies. Early …

Emerging approaches for the identification of protein targets of small molecules-a practitioners' perspective

KM Comess, SM McLoughlin, JA Oyer… - Journal of medicinal …, 2018 - ACS Publications
Small-molecule (SM) leads in the early drug discovery pipeline are progressed primarily
based on potency against the intended target (s) and selectivity against a very narrow slice …