The use of structural alerts to avoid the toxicity of pharmaceuticals [PDF]
Toxicology Reports, 2018 In order to identify compounds with potential toxicity problems, particular attention is paid to structural alerts, which are high chemical reactivity molecular fragments or fragments that can be transformed via bioactivation by human enzymes into ...
Carmen Limban +8 more
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SApredictor: An Expert System for Screening Chemicals Against Structural Alerts [PDF]
Frontiers in Chemistry, 2022 The rapid and accurate evaluation of chemical toxicity is of great significance for estimation of chemical safety. In the past decades, a great number of excellent computational models have been developed for chemical toxicity prediction.
Yuqing Hua +7 more
doaj +7 more sources
Prediction of Respiratory Irritation and Respiratory Sensitization of Chemicals Using Structural Alerts and Machine Learning Modeling [PDF]
ToxicsInhalation of toxic substances and contaminants can have adverse effects on the respiratory tract, leading to a range of health problems, such as irritation and inflammation, allergic reaction and asthma, lung damage, or even death. It is not possible to
Yaroslav Chushak +2 more
doaj +6 more sources
In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts [PDF]
Frontiers in Chemistry, 2018 During drug development, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases.
Hongbin Yang +4 more
doaj +6 more sources
A Scheme to Evaluate Structural Alerts to Predict Toxicity – Assessing Confidence by Characterising Uncertainties [PDF]
Regulatory Toxicology and Pharmacology, 2022 Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are essential tools in in silico toxicology. Whilst other in silico methods have approaches for their evaluation,
Bruno Campos +2 more
exaly +5 more sources
Machine Learning for Predicting Risk of Drug-Induced Autoimmune Diseases by Structural Alerts and Daily Dose [PDF]
International Journal of Environmental Research and Public Health, 2021 An effective approach for assessing a drug’s potential to induce autoimmune diseases (ADs) is needed in drug development. Here, we aim to develop a workflow to examine the association between structural alerts and drugs-induced ADs to improve ...
Yue Wu, Huixiao Hong, Minjun Chen
exaly +4 more sources
Machine Learning-Based Classification for the Prioritization of Potentially Hazardous Chemicals With Structural Alerts in Nontarget Screening [PDF]
Environmental Science & TechnologyNontarget screening (NTS) with liquid chromatography high-resolution mass spectrometry (LC-HRMS) is commonly used to detect unknown organic micropollutants in the environment.
Frederic Been +2 more
exaly +4 more sources
Corrigendum: In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts [PDF]
Frontiers in Chemistry, 2018 [This corrects the article on p. 30 in vol. 6, PMID: 29515993.].
Hongbin Yang +4 more
doaj +3 more sources
The Good, The Bad, and The Perplexing: Structural Alerts and Read-Across for Predicting Skin Sensitization Using Human Data. [PDF]
Chem Res Toxicol, 2023 In our earlier work (Golden et al., 2021), we showed 70–80% accuracies for several skin sensitization computational tools using human data. Here, we expanded the data set using the NICEATM human skin sensitization database to create a final data set of ...
Golden E +5 more
europepmc +2 more sources
Unraveling Structural Alerts in Marketed Drugs for Improving Adverse Outcome Pathway Framework of Drug-Induced QT Prolongation. [PDF]
Int J Mol Sci, 2023 In pharmaceutical treatment, many non-cardiac drugs carry the risk of prolonging the QT interval, which can lead to fatal cardiac complications such as torsades de points (TdP).
Long W, Li S, He Y, Lin J, Li M, Wen Z.
europepmc +2 more sources