Literature DB >> 34075855

Artificial intelligence in early drug discovery enabling precision medicine.

Fabio Boniolo1,2, Emilio Dorigatti1,3, Alexander J Ohnmacht1,4, Dieter Saur2, Benjamin Schubert1,5, Michael P Menden1,4,6.   

Abstract

Introduction: Precision medicine is the concept of treating diseases based on environmental factors, lifestyles, and molecular profiles of patients. This approach has been found to increase success rates of clinical trials and accelerate drug approvals. However, current precision medicine applications in early drug discovery use only a handful of molecular biomarkers to make decisions, whilst clinics gear up to capture the full molecular landscape of patients in the near future. This deep multi-omics characterization demands new analysis strategies to identify appropriate treatment regimens, which we envision will be pioneered by artificial intelligence.Areas covered: In this review, the authors discuss the current state of drug discovery in precision medicine and present our vision of how artificial intelligence will impact biomarker discovery and drug design.Expert opinion: Precision medicine is expected to revolutionize modern medicine; however, its traditional form is focusing on a few biomarkers, thus not equipped to leverage the full power of molecular landscapes. For learning how the development of drugs can be tailored to the heterogeneity of patients across their molecular profiles, artificial intelligence algorithms are the next frontier in precision medicine and will enable a fully personalized approach in drug design, and thus ultimately impacting clinical practice.

Entities:  

Keywords:  Artificial intelligence; biomarker discovery; deep learning; drug repurposing; machine learning; patient stratification; precision medicine; protein design; small molecule design; vaccine design

Mesh:

Year:  2021        PMID: 34075855     DOI: 10.1080/17460441.2021.1918096

Source DB:  PubMed          Journal:  Expert Opin Drug Discov        ISSN: 1746-0441            Impact factor:   6.098


  2 in total

Review 1.  Hydroxypyridinones as a Very Promising Platform for Targeted Diagnostic and Therapeutic Radiopharmaceuticals.

Authors:  Xu Zhou; Linlin Dong; Langtao Shen
Journal:  Molecules       Date:  2021-11-19       Impact factor: 4.411

2.  Decoding the protein-ligand interactions using parallel graph neural networks.

Authors:  Carter Knutson; Mridula Bontha; Jenna A Bilbrey; Neeraj Kumar
Journal:  Sci Rep       Date:  2022-05-10       Impact factor: 4.996

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.