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Rethinking drug design in the artificial intelligence era
Petra Schneider1, W Patrick Walters2, Alleyn T Plowright3
1ETH Zurich, RETHINK, Department of Chemistry and Applied Biosciences, Zurich, Switzerland.
Nature Reviews. Drug Discovery
|December 6, 2019
Summary
Artificial intelligence (AI) offers new opportunities and challenges in drug discovery. Experts discuss key hurdles and strategies for integrating AI into small-molecule drug development, balancing potential with current realities.
Area of Science:
- Pharmacology
- Computational Chemistry
- Biotechnology
Background:
- Artificial intelligence (AI) is increasingly utilized in pharmaceutical research and development.
- Debate exists regarding the tangible impact of AI on drug discovery projects, with some experts optimistic and others awaiting concrete evidence.
- AI integration presents novel challenges for scientific researchers and the biopharmaceutical industry's established drug development pipelines.
Purpose of the Study:
- To present expert perspectives on the significant challenges in applying AI to small-molecule drug discovery.
- To explore potential approaches and strategies for overcoming these identified challenges.
- To provide a balanced view on the current state and future of AI in medicinal chemistry.
Main Methods:
- The study compiles insights from a diverse group of international experts in the field.
- Expert opinions were gathered regarding the 'grand challenges' in AI-driven small-molecule drug discovery.
- Discussions focused on practical approaches to address the identified challenges.
Main Results:
- AI presents both significant opportunities and considerable challenges in drug discovery.
- Key challenges include integrating AI into existing workflows and validating AI-driven results.
- Expert consensus highlights the need for new strategies and interdisciplinary collaboration.
Conclusions:
- AI is transforming small-molecule drug discovery, necessitating adaptation within the biopharma industry.
- Addressing the 'grand challenges' requires innovative approaches and a realistic assessment of AI's current capabilities.
- Further research and development are crucial to fully realize AI's potential in accelerating medicine development.
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