Technologies currently employed to find and identify drug metabolites in complex biological
matrices generally yield results that offer a comprehensive picture of the drug metabolite …

The discovery and development of drugs is a long and expensive process with a high
attrition rate. Computational drug discovery contributes to ligand discovery and optimization …

In a pharmaceutical context, metabolomics is an underexplored area of research.
Nevertheless, its utility in clinical pathology, biomarker discovery, metabolic subtyping, and …

The ability to determine and predict metabolically labile atom positions in a molecule (also
called “sites of metabolism” or “SoMs”) is of high interest to the design and optimization of …

The discovery of a drug requires over a decade of intensive research and financial
investments–and still has a high risk of failure. To reduce this burden, we developed the …

After the biotransformation of xenobiotics in the human body, the biological activity of the
metabolites may differ from the activity of parent compounds. Therefore, to assess the overall …

Cytochrome P450 enzymes aid in the elimination of a preponderance of small molecule
drugs, but can generate reactive metabolites that may adversely react with protein and DNA …

Adverse drug metabolism often severely impacts patient morbidity and mortality.
Unfortunately, drug metabolism experimental assays are costly, inefficient, and slow …

(1) Background: Machine learning algorithms are finding fruitful applications in predicting
the ADME profile of new molecules, with a particular focus on metabolism predictions …

The growing amount of experimental data on chemical objects includes properties of small
molecules, results of studies of their interaction with human and animal proteins, and …