AI Medical Compendium Journal:
Chemical research in toxicology

Showing 11 to 20 of 54 articles

Prediction of Skin Sensitization for Compounds Flexible Evidence Combination Based on Machine Learning and Dempster-Shafer Theory.

Chemical research in toxicology
Skin sensitization is increasingly becoming a significant concern in the development of drugs and cosmetics due to consumer safety and occupational health problems. methods have emerged as alternatives to traditional animal testing due to ethical a...

Deus Ex Machina? The Rise of Artificial Intelligence in Toxicology.

Chemical research in toxicology
Artificial intelligence (AI) is rising rapidly, driven by big data, complex algorithms, and computing resources. Current research presented at the American Chemical Society Fall 2023 Meeting demonstrates AI to be a valuable predictive and supporting ...

Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition.

Chemical research in toxicology
Most drugs are mainly metabolized by cytochrome P450 (CYP450), which can lead to drug-drug interactions (DDI). Specifically, time-dependent inhibition (TDI) of CYP3A4 isoenzyme has been associated with clinically relevant DDI. To overcome potential D...

Systematic Approaches for the Encoding of Chemical Groups: A Case Study.

Chemical research in toxicology
Regulatory authorities aim to organize substances into groups to facilitate prioritization within hazard and risk assessment processes. Often, such chemical groupings are not explicitly defined by structural rules or physicochemical property informat...

TISBE: A Public Web Platform for the Consensus-Based Explainable Prediction of Developmental Toxicity.

Chemical research in toxicology
Despite being extremely relevant for the protection of prenatal and neonatal health, the developmental toxicity (Dev Tox) is a highly complex endpoint whose molecular rationale is still largely unknown. The lack of availability of high-quality data a...

Prediction of Spheroid Cell Death Using Fluorescence Staining and Convolutional Neural Networks.

Chemical research in toxicology
Three-dimensional (3D) cell culture is emerging for drug design and drug screening. Skin toxicity is one of the most important assays for determining the toxicity of a compound before being used in skin application. Much work has been done to find an...

Machine Learning Enables Accurate Prediction of Quinone Formation during Drug Metabolism.

Chemical research in toxicology
Metabolism helps in the elimination of drugs from the human body by making them more hydrophilic. Sometimes, drugs can be bioactivated to highly reactive metabolites or intermediates during metabolism. These reactive metabolites are often responsible...

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

Chemical research in toxicology
The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industry leverages QM models explicitly in covalent drug discovery and implicitly to characterize short-ran...

A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies.

Chemical research in toxicology
Drug toxicity prediction is an important step in ensuring patient safety during drug design studies. While traditional preclinical studies have historically relied on animal models to evaluate toxicity, recent advances in deep-learning approaches hav...

A Weakly Supervised Deep Learning Framework for Whole Slide Classification to Facilitate Digital Pathology in Animal Study.

Chemical research in toxicology
The pathology of animal studies is crucial for toxicity evaluations and regulatory assessments, but the manual examination of slides by pathologists remains time-consuming and requires extensive training. One inherent challenge in this process is the...