Predicting drug-induced liver injury using ensemble learning methods and molecular fingerprints

H Ai, W Chen, L Zhang, L Huang, Z Yin… - Toxicological …, 2018 - academic.oup.com
Drug-induced liver injury (DILI) is a major safety concern in the drug-development process,
and various methods have been proposed to predict the hepatotoxicity of compounds during …

[HTML][HTML] Prediction models for drug-induced hepatotoxicity by using weighted molecular fingerprints

E Kim, H Nam - BMC bioinformatics, 2017 - Springer
Background Drug-induced liver injury (DILI) is a critical issue in drug development because
DILI causes failures in clinical trials and the withdrawal of approved drugs from the market …

[HTML][HTML] In silico prediction of drug-induced liver injury based on ensemble classifier method

Y Wang, Q Xiao, P Chen, B Wang - International journal of molecular …, 2019 - mdpi.com
Drug-induced liver injury (DILI) is a major factor in the development of drugs and the safety
of drugs. If the DILI cannot be effectively predicted during the development of the drug, it will …

Comparing machine learning algorithms for predicting drug-induced liver injury (DILI)

E Minerali, DH Foil, KM Zorn, TR Lane… - Molecular …, 2020 - ACS Publications
Drug-induced liver injury (DILI) is one the most unpredictable adverse reactions to
xenobiotics in humans and the leading cause of postmarketing withdrawals of approved …

AI/ML models to predict the severity of drug-induced liver injury for small molecules

M Rao, V Nassiri, C Alhambra, J Snoeys… - Chemical Research …, 2023 - ACS Publications
Drug-induced liver injury (DILI), believed to be a multifactorial toxicity, has been a leading
cause of attrition of small molecules during discovery, clinical development, and …

Predicting drug-induced liver injury using convolutional neural network and molecular fingerprint-embedded features

TH Nguyen-Vo, L Nguyen, N Do, PH Le, TN Nguyen… - ACS …, 2020 - ACS Publications
As a critical issue in drug development and postmarketing safety surveillance, drug-induced
liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market …

[HTML][HTML] Development of decision forest models for prediction of drug-induced liver injury in humans using a large set of FDA-approved drugs

H Hong, S Thakkar, M Chen, W Tong - Scientific reports, 2017 - nature.com
Drug-induced liver injury (DILI) presents a significant challenge to drug development and
regulatory science. The FDA's Liver Toxicity Knowledge Base (LTKB) evaluated> 1000 …

Chemistry-based modeling on phenotype-based drug-induced liver injury annotation: from public to proprietary data

M Moein, M Heinonen, N Mesens… - Chemical Research …, 2023 - ACS Publications
Drug-induced liver injury (DILI) is an important safety concern and a major reason to remove
a drug from the market. Advancements in recent machine learning methods have led to a …

A predictive ligand-based Bayesian model for human drug-induced liver injury

S Ekins, AJ Williams, JJ Xu - Drug Metabolism and Disposition, 2010 - ASPET
Drug-induced liver injury (DILI) is one of the most important reasons for drug development
failure at both preapproval and postapproval stages. There has been increased interest in …

[HTML][HTML] Predicting drug-induced liver injury: The importance of data curation

E Kotsampasakou, F Montanari, GF Ecker - Toxicology, 2017 - Elsevier
Drug-induced liver injury (DILI) is a major issue for both patients and pharmaceutical
industry due to insufficient means of prevention/prediction. In the current work we present a …