Abstract

OLASCOAGA-DEL ANGEL, Kevin Samael; KONIGSBERG-FAINSTEIN, Mina; PEREZ-VILLANUEVA, Jaime  and  LOPEZ DIAZ-GUERRERO, Norma Edith. Artificial intelligence in drug repurposing research. TIP [online]. 2022, vol.25, e450.  Epub June 20, 2023. ISSN 1405-888X.  https://doi.org/10.22201/fesz.23958723e.2022.450.

The development of sophisticated artificial intelligence algorithms and the massive availability of biomedical data have driven accelerated research to discover novel treatments using drugs previously developed and approved for other uses. This process is known as drug repositioning (DR), and it can be addressed by a branch of artificial intelligence (AI) known as machine learning (ML). Machine learning is based on a set of algorithms that, combined with well-established computational techniques in the field of drug discovery, have been able to infer new previously unknown pharmacological properties and relationships with high efficiency. Thus, new targets and potential treatments against various diseases such as cancer and neurodegenerative and infectious diseases have been identified. The objective of this review is to contribute to the literature in Spanish on the use of Artificial Intelligence and machine learning in drug repositioning research.

Keywords : drug repurposing; artificial intelligence; drug discovery; machine learning; chemoinformatics.