During drug development, safety is always the most important issue, including a variety of
toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial …

The applied use of in silico technologies (aka computational toxicology, in silico toxicology,
computer-assisted tox, e-tox, i-drug discovery, predictive ADME, etc.) for predicting …

Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties play key
roles in the discovery/development of drugs, pesticides, food additives, consumer products …

Background A frequent problem in computational modeling is the interconversion of
chemical structures between different formats. While standard interchange formats exist (for …

In this chapter, we present a survey of algorithms for dense subgraph discovery. The
problem of dense subgraph discovery is closely related to clustering though the two …

In this review, we highlight recent applications of machine learning to virtual screening,
focusing on the use of supervised techniques to train statistical learning algorithms to …

In the past decades, chemical carcinogenicity has been the object of mechanistic studies
that have been translated into valuable experimental (eg, the Salmonella assays system) …

Structural alerts are a simple and easy way to identify toxic compounds being widely used in
environmental toxicology research and drug discovery. With the emergence of big data …

Publisher Summary A quality development candidate compound after a positive proof of
concept clinical trial has a good chance of making it to be a marketed drug. It is the role of …

The need to assess the ability of a chemical to act as a mutagen or a genotoxic carcinogen
(collectively termed genotoxicity) is one of the primary requirements in regulatory toxicology …