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   Articles with "toxicity prediction" as a keyword



Machine Learning‐Enabled Drug‐Induced Toxicity Prediction

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recommendations! Published in 2025 at "Advanced Science"

DOI: 10.1002/advs.202413405

Abstract: Unexpected toxicity has become a significant obstacle to drug candidate development, accounting for 30% of drug discovery failures. Traditional toxicity assessment through animal testing is costly and time‐consuming. Big data and artificial intelligence (AI), especially… read more here.

Keywords: induced toxicity; toxicity prediction; drug; toxicity ... See more keywords

5,6‐Dihydrotetrazolo[1,5‐c]quinazolines: Toxicity prediction, synthesis, antimicrobial activity, molecular docking, and perspectives

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recommendations! Published in 2023 at "Archiv der Pharmazie"

DOI: 10.1002/ardp.202300029

Abstract: Antimicrobial resistance is a never‐ending challenge, which should be considered seriously, especially when using unprescribed “over‐the‐counter” drugs. The synthesis and investigation of novel biologically active substances is among the directions to overcome this problem. Hence,… read more here.

Keywords: quinazolines toxicity; prediction synthesis; toxicity prediction; dihydrotetrazolo quinazolines ... See more keywords

Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction

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recommendations! Published in 2024 at "Chemical Research in Toxicology"

DOI: 10.1021/acs.chemrestox.3c00352

Abstract: The attrition rate of drugs in clinical trials is generally quite high, with estimates suggesting that approximately 90% of drugs fail to make it through the process. The identification of unexpected toxicity issues during preclinical… read more here.

Keywords: safety; toxicity prediction; drug; toxicity ... See more keywords

Machine Learning for Toxicity Prediction Using Chemical Structures: Pillars for Success in the Real World

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recommendations! Published in 2025 at "Chemical Research in Toxicology"

DOI: 10.1021/acs.chemrestox.5c00033

Abstract: Machine learning (ML) is increasingly valuable for predicting molecular properties and toxicity in drug discovery. However, toxicity-related end points have always been challenging to evaluate experimentally with respect to in vivo translation due to the… read more here.

Keywords: toxicity prediction; pillars success; machine learning; toxicity ... See more keywords

Artificial Intelligence in Drug Toxicity Prediction: Recent Advances, Challenges, and Future Perspectives

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recommendations! Published in 2023 at "Journal of chemical information and modeling"

DOI: 10.1021/acs.jcim.3c00200

Abstract: 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 also reducing the risk of costly… read more here.

Keywords: artificial intelligence; toxicity prediction; toxicity; drug toxicity ... See more keywords

Enhancing Toxicity Prediction of Synthetic Chemicals via Novel SMILES Fragmentation and Interpretable Deep Learning

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recommendations! Published in 2025 at "Journal of chemical information and modeling"

DOI: 10.1021/acs.jcim.5c01042

Abstract: Toxicity prediction and identification of structural alerts (SAs) for synthetic chemicals are critical for assessing risks to environmental and human health. Traditional methods, which rely heavily on molecular descriptors, often suffer from poor interpretability. Here,… read more here.

Keywords: deep learning; toxicity prediction; toxicity; smiles fragmentation ... See more keywords

toxFlow: A Web-Based Application for Read-Across Toxicity Prediction Using Omics and Physicochemical Data

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recommendations! Published in 2018 at "Journal of chemical information and modeling"

DOI: 10.1021/acs.jcim.7b00160

Abstract: We present toxFlow, a web application developed for enrichment analysis of omics data coupled with read-across toxicity prediction. A sequential analysis workflow is suggested where users can filter omics data using enrichment scores and incorporate… read more here.

Keywords: toxflow web; across toxicity; toxicity; read across ... See more keywords

Machine Learning Toxicity Prediction: Latest Advances by Toxicity End Point

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recommendations! Published in 2022 at "ACS Omega"

DOI: 10.1021/acsomega.2c05693

Abstract: 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 particularly advantageous in the early stages of drug… read more here.

Keywords: end point; toxicity prediction; machine learning; toxicity ... See more keywords

Identification of Optimal Machine Learning Algorithms and Molecular Fingerprints for Explainable Toxicity Prediction Models Using ToxCast/Tox21 Bioassay Data

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recommendations! Published in 2024 at "ACS Omega"

DOI: 10.1021/acsomega.4c04474

Abstract: Recent studies have primarily focused on introducing novel frameworks to enhance the predictive power of toxicity prediction models by refining molecular representation methods and algorithms. However, these methods are inherently complex and often pose challenges… read more here.

Keywords: toxcast tox21; prediction models; toxicity prediction; toxicity ... See more keywords

Multimodal deep learning for chemical toxicity prediction and management

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-95720-5

Abstract: The accurate prediction of chemical toxicity is a crucial research focus in chemistry, biotechnology, and national defense. The development of comprehensive datasets for chemical toxicity prediction remains limited due to security constraints and the structural… read more here.

Keywords: deep learning; toxicity prediction; toxicity; prediction ... See more keywords

BFGTP: A BERT-Guided Two-Stage Molecular Representation Learning Framework for Toxicity Prediction

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recommendations! Published in 2025 at "IEEE Journal of Biomedical and Health Informatics"

DOI: 10.1109/jbhi.2025.3556766

Abstract: Accurate prediction of molecular toxicity is vital for drug development. Most mainstream methods rely on fingerprints or graph-based feature extraction, the emergence of large language models (LLMs) offers new prospects for molecular representation learning in… read more here.

Keywords: toxicity prediction; representation learning; toxicity; prediction ... See more keywords