AIMC Topic: Chemical and Drug Induced Liver Injury

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Development and Validation of a Novel Model to Discriminate Idiosyncratic Drug-Induced Liver Injury and Autoimmune Hepatitis.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIM: Discriminating between idiosyncratic drug-induced liver injury (DILI) and autoimmune hepatitis (AIH) is critical yet challenging. We aim to develop and validate a machine learning (ML)-based model to aid in this differentiation.

Prediction of Drug-Induced Liver Injury: From Molecular Physicochemical Properties and Scaffold Architectures to Machine Learning Approaches.

Chemical biology & drug design
The process of developing new drugs is widely acknowledged as being time-intensive and requiring substantial financial investment. Despite ongoing efforts to reduce time and expenses in drug development, ensuring medication safety remains an urgent p...

Best practice and reproducible science are required to advance artificial intelligence in real-world applications.

Briefings in bioinformatics
Drug-induced liver injury (DILI) is one of the most significant concerns in medical practice but yet it still cannot be fully recapitulated with existing in vivo, in vitro and in silico approaches. To address this challenge, Chen et al. [ 1] develope...

The prediction approach of drug-induced liver injury: response to the issues of reproducible science of artificial intelligence in real-world applications.

Briefings in bioinformatics
In the previous study, we developed the generalized drug-induced liver injury (DILI) prediction model-ResNet18DNN to predict DILI based on multi-source combined DILI dataset and achieved better performance than that of previously published described ...

Machine Learning from Omics Data.

Methods in molecular biology (Clifton, N.J.)
Machine learning (ML) already accelerates discoveries in many scientific fields and is the driver behind several new products. Recently, growing sample sizes enabled the use of ML approaches in larger omics studies. This work provides a guide through...

Editor's Highlight: Identification of Any Structure-Specific Hepatotoxic Potential of Different Pyrrolizidine Alkaloids Using Random Forests and Artificial Neural Networks.

Toxicological sciences : an official journal of the Society of Toxicology
Pyrrolizidine alkaloids (PAs) are characteristic metabolites of some plant families and form a powerful defense mechanism against herbivores. More than 600 different PAs are known. PAs are ester alkaloids composed of a necine base and a necic acid, w...

Antioxidant and hepatoprotective activities of Dicoma anomala Sond. aqueous root extract against carbon tetrachloride-induced liver damage in Wistar rats.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To evaluates the antioxidant and hepatoprotective potentials of Dicoma anomala Sond. (Asteraceae) on body weight, feed and water intake, biochemical parameters and organ histology.

Protective effect of Yiguanjian decoction against DNA damage on concanavalin A-induced liver injury mice model.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To investigate the inhibitory effect of Yiguanjian decoction (YD) on DNA damage in Concanavalin A (Con A)-induced liver injury mice model and to explain the possible mechanism.

Probing the Hypothesis of SAR Continuity Restoration by the Removal of Activity Cliffs Generators in QSAR.

Current pharmaceutical design
In this work we report the first attempt to study the effect of activity cliffs over the generalization ability of machine learning (ML) based QSAR classifiers, using as study case a previously reported diverse and noisy dataset focused on drug induc...