TY - JOUR
T1 - Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments
AU - Dulsat, Júlia
AU - López-Nieto, Blanca
AU - Estrada-Tejedor, Roger
AU - Borrell, José I.
N1 - Funding Information:
This research was funded by Ministerio de Ciencia, Innovación y Universidades, Proyectos de I+D+I “Retos Investigación” del Programa Estatal de I+D+I orientada a los Retos de la Sociedad, grant number RTI2018-096455-B-I00.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - absorption
KW - distribution
KW - elimination
KW - in silico predictions
KW - metabolism
KW - pharmacokinetics
KW - toxicity
KW - tyrosine kinase inhibitors
KW - web servers
KW - Absorption
KW - Distribution
KW - Elimination
KW - In silico predictions
KW - Metabolism
KW - Pharmacokinetics
KW - Toxicity
KW - Tyrosine kinase inhibitors
KW - Web servers
UR - http://www.scopus.com/inward/record.url?scp=85146802642&partnerID=8YFLogxK
U2 - 10.3390/molecules28020776
DO - 10.3390/molecules28020776
M3 - Review
C2 - 36677832
AN - SCOPUS:85146802642
SN - 1420-3049
VL - 28
JO - Molecules
JF - Molecules
IS - 2
M1 - 776
ER -