Table 2.

The promise of AI/ML‐based drug discovery strategies in CNS disorders

Application field	Schizophrenia	Autism spectrum disorder	Depression	PD	AD	Anesthesia	Pain treatment
Diagnosis/prognosis	✓	✓	✓	✓	✓	‐	✓
Subtyping	✓	‐	‐	‐	‐	‐	‐
Heterogeneity detection	✓	‐	‐	‐	‐	‐	‐
Target identification	✓	‐	‐	‐	✓	‐	✓
Inhibitor discovery	✓	✓	✓	✓	✓	‐	‐
Multitarget drug discovery	‐	‐	‐	‐	✓	‐	✓
Drug repositioning	✓	✓	✓	✓	✓	‐	‐
Drug response	‐	✓	✓	‐	‐	‐	‐
Variant effect	‐	✓	‐	‐	‐	‐	‐
Developmental neurotoxicants	✓	✓	‐	‐	‐	‐	‐
Pharmacological decision support	‐	‐	✓	‐	‐	✓	✓
Drug response monitoring	‐	‐	‐	✓	‐	✓	‐
Adverse drug effects	‐	‐	‐	✓	‐	✓	‐
Drug screening	‐	‐	‐	✓	‐	‐	‐
Overdose and misuse	‐	‐	‐	‐	‐	‐	✓

Abbreviations: AD, Alzheimer's disease; AI, artificial intelligence; CNS, central nervous system; ML, machine learning; PD, Parkinson's disease.