AI in Drug Discovery Faces Clinical Impact Hurdles
TL;DR. A new perspective discusses the limited clinical impact of AI in drug discovery, despite high interest in the field. - Researchers highlight insufficient focus on clinical translation and issues with applying AI to life science data. - The analysis recommends benchmarking AI tools on their ability to improve decision-making, not just model validation. - The piece suggests a shift from 'technology push' to 'science pull' for better real-world relevance.
- AI in drug discovery has shown limited clinical impact despite high interest.
- Reasons include insufficient clinical translation focus and difficulty with life science data.
- Recommendations call for benchmarking AI tools on decision-making improvement.
- The article suggests moving beyond model validation to real-world application.
Sources
- AI in drug discovery — what it is, where we stand and the path forward — nature.com
- AI in drug discovery – what it is, where we stand and the path forward — science.org
- analyticsindiamag.com — analyticsindiamag.com