| ADMET | Absorption, distribution, metabolism, excretion, and toxicity |
| AI | Artificial intelligence |
| AML | Acute myeloid leukemia |
| CV | Computer vision |
| DDD | Drug discovery and development |
| DL | Deep learning |
| GM | Generative model |
| HGSOC | High-grade serous ovarian cancer |
| HTS | High-throughput screening |
| IBD | Inflammatory bowel disease |
| IND | Investigational new drug |
| IPF | Idiopathic pulmonary fibrosis |
| KG | Knowledge graph |
| KPIs | Key performance indicators |
| ML | Machine learning |
| MMS | Molecular modeling and simulation |
| NLP | Natural language processing |
| NSCLC | Non-small cell lung cancer |
| OCD | Obsessive–compulsive disorder |
| OM | Omics integration |
| PBM | Physics-based modeling |
| PK/PD | Pharmacokinetics/pharmacodynamics |
| PRISMA | Preferred reporting items for systematic reviews and meta-analyses |
| QSAR | Quantitative structure–activity relationship |
| R&D | Research and development |
| RL | Reinforcement learning |
| SBDD | Structure-based drug design |
| SLE | Systemic lupus erythematosus |
| TNBC | Triple-negative breast cancer |