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Review

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

by
Júlia Dulsat
,
Blanca López-Nieto
,
Roger Estrada-Tejedor
and
José I. Borrell
*
Grup de Química Farmacèutica, IQS School of Engineering, Universitat Ramon Llull, Via Augusta 390, E-08017 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Molecules 2023, 28(2), 776; https://doi.org/10.3390/molecules28020776
Submission received: 30 November 2022 / Revised: 27 December 2022 / Accepted: 10 January 2023 / Published: 12 January 2023

Abstract

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.
Keywords: absorption; distribution; metabolism; elimination; toxicity; pharmacokinetics; in silico predictions; tyrosine kinase inhibitors; web servers absorption; distribution; metabolism; elimination; toxicity; pharmacokinetics; in silico predictions; tyrosine kinase inhibitors; web servers

Share and Cite

MDPI and ACS Style

Dulsat, J.; López-Nieto, B.; Estrada-Tejedor, R.; Borrell, J.I. Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments. Molecules 2023, 28, 776. https://doi.org/10.3390/molecules28020776

AMA Style

Dulsat J, López-Nieto B, Estrada-Tejedor R, Borrell JI. Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments. Molecules. 2023; 28(2):776. https://doi.org/10.3390/molecules28020776

Chicago/Turabian Style

Dulsat, Júlia, Blanca López-Nieto, Roger Estrada-Tejedor, and José I. Borrell. 2023. "Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments" Molecules 28, no. 2: 776. https://doi.org/10.3390/molecules28020776

APA Style

Dulsat, J., López-Nieto, B., Estrada-Tejedor, R., & Borrell, J. I. (2023). Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments. Molecules, 28(2), 776. https://doi.org/10.3390/molecules28020776

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