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Artificial intelligence revolutionizing CNS drug discovery and development

  • Md E.K. Talukder
  • , Mohammad Rashedul Islam
  • , Saghir Ali
  • , Jia Zhou
  • , Andrew A. Bolinger

Research output: Contribution to journal › Review article › peer-review

Abstract

Central nervous system (CNS) drug discovery faces high attrition rates, long timelines and substantial costs due to complex disease biology and the difficulties in safe drug delivery. Conventional CNS processes remain slow and trial-and-error driven. These challenges often result in poor brain penetration, off-target toxicity or limited efficacy after years of development. Recently, the integration of artificial intelligence (AI) with computer-aided drug design (CADD) has enabled more precise and scalable approaches for therapeutic development. AI-powered tools prioritize high-value analogs, streamlining design and optimization. This review provides an overview of how AI technologies are redefining early-stage CNS drug discovery, particularly for complex and underserved neurological diseases.

Original languageEnglish (US)
Article number104667
JournalDrug Discovery Today
Volume31
Issue number3
DOIs
StatePublished - May 2026

Keywords

  • artificial intelligence
  • central nervous system
  • computer-aided drug design
  • deep learning
  • machine learning
  • medicinal chemistry
  • neurodegenerative diseases

ASJC Scopus subject areas

  • Pharmacology
  • Drug Discovery

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