Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments

• Published in: Molecules (Basel, Switzerland) Vol. 28; no. 2; p. 776
• Main Authors: Dulsat, Júlia, López-Nieto, Blanca, Estrada-Tejedor, Roger, Borrell, José I
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 12.01.2023; MDPI
• Subjects: absorption; Biological activity; Biotechnology; Biotechnology industry; Confidentiality; distribution; elimination; Hydrogen bonds; Laboratories; Mathematical models; Metabolism; Metabolites; Models, Biological; Models, Molecular; Molecular modelling; Optimization; Parameters; Pharmaceutical industry; Pharmaceutical sciences; Pharmacokinetics; Pharmacology; Predictions; Protein-tyrosine kinase; Research centers; Research projects; Review; Software; Toxicity; Tyrosine; toxicity; tyrosine kinase inhibitors; web servers; absorption; pharmacokinetics; metabolism; distribution; elimination; in silico predictions
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules28020776

For a new molecular entity (NME) to become a drug, it is not only essential to have the right biological activity also be safe and efficient, but it is also required to have a favorable pharmacokinetic profile including toxicity (ADMET). Consequently, there is a need to predict, during the early stages of development, the ADMET properties to increase the success rate of compounds reaching the lead optimization process. Since Lipinski's rule of five, the prediction of pharmacokinetic parameters has evolved towards the current in silico tools based on empirical approaches or molecular modeling. The commercial specialized software for performing such predictions, which is usually costly, is, in many cases, not among the possibilities for research laboratories in academia or at small biotech companies. Nevertheless, in recent years, many free online tools have become available, allowing, more or less accurately, for the prediction of the most relevant pharmacokinetic parameters. This paper studies 18 free web servers capable of predicting ADMET properties and analyzed their advantages and disadvantages, their model-based calculations, and their degree of accuracy by considering the experimental data reported for a set of 24 FDA-approved tyrosine kinase inhibitors (TKIs) as a model of a research project.