Title:Precision Psychiatry: Machine Learning as a Tool to Find New Pharmacological
Targets
Volume: 22
Issue: 15
Author(s): João Rema*, Filipa Novais and Diogo Telles-Correia
Affiliation:
- Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal
- Serviço de Psiquiatria e Saúde Mental, Centro
Hospitalar Universitário Lisboa Norte, Lisboa, Portugal
Keywords:
Machine learning, Artificial intelligence, Neural networks, Psychiatry, Drugs, Pharmacological targets.
Abstract:
Objectives: The present work reviews current evidence regarding the contribution of machine
learning to the discovery of new drug targets.
Methods: Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection
published until May 2021 were included in this review.
Results: The most significant areas of research are schizophrenia, depression and anxiety,
Alzheimer´s disease, and substance use disorders. ML techniques have pinpointed target gene candidates
and pathways, new molecular substances, and several biomarkers regarding psychiatric disorders.
Drug repositioning studies using ML have identified multiple drug candidates as promising
therapeutic agents.
Conclusion: Next-generation ML techniques and subsequent deep learning may power new findings
regarding the discovery of new pharmacological agents by bridging the gap between biological
data and chemical drug information.