Natural language processing in drug discovery: bridging the gap between text and therapeutics with artificial intelligence.

Journal: Expert opinion on drug discovery
Published Date: Apr 30, 2025

Abstract

INTRODUCTION: The field of Natural Language Processing (NLP) within the life sciences has exploded in its capacity to aid the extraction and analysis of data from scientific texts in recent years through the advancement of Artificial Intelligence (AI). Drug discovery pipelines have been innovated and accelerated by the uptake of AI/Machine Learning (ML) techniques.

Authors

  • Christine Ann Withers
    Chemical Biology Services, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK.
  • Amina Mardiyyah Rufai
    Literature Services, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK.
  • Aravind Venkatesan
    Institut de Biologie Computationnelle (IBC), Univ. of Montpellier, Montpellier, France.
  • Santosh Tirunagari
    Department of Psychology, Middlesex University, London, United Kingdom. Correspondence to: Dr Santosh Tirunagari, Department of Psychology, Middlesex University, London, United Kingdom. s.tirunagari@mdx.ac.uk.
  • Sebastian Lobentanzer
    Heidelberg University, Faculty of Medicine and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany. sebastian.lobentanzer@gmail.com.
  • Melissa Harrison
    Data Services Teams, EMBL's European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, UK.
  • Barbara Zdrazil
    Division of Drug Design and Medicinal Chemistry, Department of Pharmaceutical Chemistry, University of Vienna, Althanstrasse 14, 1090, Vienna, Austria. barbara.zdrazil@univie.ac.at.

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