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 language | English (US) |
|---|---|
| Article number | 104667 |
| Journal | Drug Discovery Today |
| Volume | 31 |
| Issue number | 3 |
| DOIs | |
| State | Published - 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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