Introduction Healthcare systems are complex and challenging for all stakeholders, but
artificial intelligence (AI) has transformed various fields, including healthcare, with the …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

ADMETlab 3.0 is the second updated version of the web server that provides a
comprehensive and efficient platform for evaluating ADMET-related parameters as well as …

The rapid progress of AI impacts diverse scientific disciplines, including toxicology, and has
the potential to transform chemical safety evaluation. Toxicology has evolved from an …

The growth of artificial intelligence (AI) has led to an increase in the adoption of computer
vision and deep learning (DL) techniques for the evaluation of microscopy images and …

High dimensionality is one of the main challenges in Quantitative Structure-Activity
Relationship (QSAR) classification modeling, and feature selection as an effective …

Absorption is an important area of research in pharmacochemistry and drug development,
because the drug has to be absorbed before any drug effects can occur. Furthermore, the …

In the field of drug discovery, there is a substantial challenge in seeking out chemical
structures that possess desirable pharmacological, toxicological, and pharmacokinetic …

The rapid progress of AI impacts various areas of life, including toxicology, and promises a
major role for AI in future risk assessments. Toxicology has shifted from a purely empirical …

Toxicology has undergone a transformation from an observational science to a data-rich
discipline ripe for artificial intelligence (AI) integration. The exponential growth in computing …