AIMC Topic: Chemical and Drug Induced Liver Injury

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ChemBioHepatox: Multimodal Integrating Chemical Structure and Biological Fingerprint for Robust and Interpretable Hepatotoxicity Prediction.

Environmental science & technology
Drug-induced liver injury (DILI) is a leading cause of clinical trial attrition and postmarketing withdrawal and a major contributor to acute liver failure. As regulators increasingly encourage human-relevant, nonanimal approaches, accurate and inter...

Integrated multi-omics and machine learning approach reveals the mechanism of nicotinamide alleviating PFOS-induced hepatotoxicity.

Food & function
: Perfluorooctane sulphonate (PFOS) is a persistent environmental contaminant with well-documented hepatotoxic properties. Nicotinamide, the amide derivative of vitamin B3, is widely utilized as a nutritional supplement and exerts multiple biological...

In vitro test battery for testing molecular initiating events in chemical-induced cholestasis.

Toxicology
Cholestatic liver injury is a complex adversity leading to the toxic accumulation of.noxious bile salts in the liver and systemic circulation. Cholestasis can be instigated by a plethora of chemicals originating from several applicability domains. Cu...

The efficacy and toxicity equilibrium of emodin for liver injury: A bidirectional meta-analysis and machine learning.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Emodin, a hepatoprotective agent derived from various herbs, exhibits dual effects on liver injury, necessitating further investigation into its therapeutic and toxic properties. Traditional meta-analyses lack predictive capability for do...

Predicting Liver-Related In Vitro Endpoints with Machine Learning to Support Early Detection of Drug-Induced Liver Injury.

Chemical research in toxicology
Drug-induced liver injury (DILI) is a major cause of drug development failures and postmarket drug withdrawals, posing significant challenges to public health and pharmaceutical research. The biological mechanisms leading to DILI are highly complex a...

Enhancing DILI toxicity prediction through integrated graph attention (GATNN) and dense neural networks (DNN).

Toxicology
Drug-induced liver injury (DILI) toxicity is a condition when drugs have a destructive effect on the liver organ. The prediction of this toxicity becomes crucial in the drug development process to guarantee that drugs are safe from toxicity. Assessme...

Evaluating the synergistic use of advanced liver models and AI for the prediction of drug-induced liver injury.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Drug-induced liver injury (DILI) is a leading cause of acute liver failure. Hepatotoxicity typically occurs only in a subset of individuals after prolonged exposure and constitutes a major risk factor for the termination of drug develop...

Risk Prediction of Liver Injury in Pediatric Tuberculosis Treatment: Development of an Automated Machine Learning Model.

Drug design, development and therapy
PURPOSE: Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactions related to first-line anti-tuberculosis drugs in pediatric tuberculosis patients. This study aims to develop an automatic machine learning (AutoML)...

Efficient analysis of drug interactions in liver injury: a retrospective study leveraging natural language processing and machine learning.

BMC medical research methodology
BACKGROUND: Liver injury from drug-drug interactions (DDIs), notably with anti-tuberculosis drugs such as isoniazid, poses a significant safety concern. Electronic medical records contain comprehensive clinical information and have gained increasing ...

Deep Learning Prediction of Drug-Induced Liver Toxicity by Manifold Embedding of Quantum Information of Drug Molecules.

Pharmaceutical research
PURPOSE: Drug-induced liver injury, or DILI, affects numerous patients and also presents significant challenges in drug development. It has been attempted to predict DILI of a chemical by in silico approaches, including data-driven machine learning m...