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Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence?
Edward J Griffen1, Alexander G Dossetter1, Andrew G Leach2
1MedChemica Ltd, Biohub, Alderley Park, Macclesfield SK10 4TG, UK.
Drug Discovery Today
|March 27, 2018
Summary
Artificial intelligence (AI) accelerates medicinal chemistry for drug discovery. By leveraging unbiased, pre-competitive knowledge, AI enhances lead optimization across all disease areas.
Area of Science:
- Medicinal Chemistry
- Drug Discovery
- Artificial Intelligence
Background:
- Drug lead optimization is a critical bottleneck in pharmaceutical research.
- Existing knowledge in medicinal chemistry is often siloed and not fully exploited.
Purpose of the Study:
- To demonstrate how artificial intelligence can accelerate lead optimization.
- To highlight the use of pre-competitive knowledge in an unbiased manner.
Main Methods:
- Development of AI algorithms for analyzing chemical data.
- Integration of diverse, pre-competitive datasets.
- Application of AI to identify and optimize drug leads.
Main Results:
- Significant acceleration in the lead optimization process.
- Identification of novel chemical matter through unbiased AI analysis.
- Demonstrated applicability across various disease areas.
Conclusions:
- AI provides a powerful, unbiased approach to accelerate medicinal chemistry.
- Leveraging pre-competitive knowledge with AI can significantly advance drug discovery efforts.
- AI-driven lead optimization holds promise for all therapeutic areas.
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