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Progress, Pitfalls, and Impact of AI-Driven Clinical Trials
Dominika Wilczok1, Alex Zhavoronkov2,3,4
1Duke University, Durham, North Carolina, USA.
Clinical Pharmacology and Therapeutics
|December 26, 2024
Summary
Artificial intelligence (AI) in drug discovery and development (AIDD) has seen major investment but few clinical successes. This perspective analyzes challenges and opportunities for AI to revolutionize pharmaceutical research.
Area of Science:
- Pharmaceutical Sciences
- Computational Biology
- Biotechnology
Background:
- Significant investment has flowed into applying artificial intelligence (AI) to drug discovery and development (AIDD) since the 2010s.
- Despite substantial resources, AI-driven drug candidates have seen limited progression into human clinical trials and no approvals.
Purpose of the Study:
- To critically examine the obstacles hindering the advancement of AI in drug discovery and development.
- To identify and highlight key opportunities for leveraging AI to transform the pharmaceutical R&D landscape.
Main Methods:
- This is a perspective piece, involving a critical analysis of the current state of AI in drug discovery.
- Literature review and expert opinion synthesis on challenges and future directions.
Main Results:
- Progress in AI for drug discovery is impeded by several critical challenges.
- Numerous opportunities exist to enhance AI's impact on the drug discovery and development pipeline.
Conclusions:
- Overcoming current challenges is crucial for realizing the full potential of AI in accelerating the delivery of novel therapeutics.
- Strategic focus on specific opportunities can drive transformative changes in AI-driven drug discovery and development.
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