Integrating artificial intelligence in drug discovery and early drug development: a transformative approach
Universidad San Pablo CEU · Instituto de Investigación Sanitaria del Hospital Clínico San Carlos · +10 more institutions
Abstract
Artificial intelligence (AI) can transform drug discovery and early drug development by addressing inefficiencies in traditional methods, which often face high costs, long timelines, and low success rates. In this review we provide an overview of how to integrate AI to the current drug discovery and development process, as it can enhance activities like target identification, drug discovery, and early clinical development. Through multiomics data analysis and network-based approaches, AI can help to identify novel oncogenic vulnerabilities and key therapeutic targets. AI models, such as AlphaFold, predict protein structures with high accuracy, aiding druggability assessments and structure-based drug design. AI…
Citation impact
- FWCI
- 140.75
- Percentile
- 100%
- References
- 110
Authors
7- AOAlberto OcañaCorresponding
Universidad San Pablo CEU, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Centro de Investigación Biomédica en Red de Cáncer
- APAtanasio Pandiella
Instituto de Investigación Biomédica de Salamanca, Centro de Investigación del Cáncer, Centro de Investigación Biomédica en Red de Cáncer
- CPCristian Privat
Asociación de Investigación de la Industria Textil
- IBIván Bravo
University of Castilla-La Mancha
- MLMiguel Luengo-Oroz
Hospital General Universitario de Albacete
Topics & keywords
- Computer science
- Drug development
- Drug discovery
- Data science
- Identification (biology)
- Artificial intelligence
- Transformative learning
- Risk analysis (engineering)