Summary of Deepcre: Transforming Drug R&d Via Ai-driven Cross-drug Response Evaluation, by Yushuai Wu et al.
DeepCRE: Transforming Drug R&D via AI-Driven Cross-drug Response Evaluation
by Yushuai Wu, Ting Zhang, Hao Zhou, Hainan Wu, Hanwen Sunchu, Lei Hu, Xiaofang Chen, Suyuan Zhao, Gaochao Liu, Chao Sun, Jiahuan Zhang, Yizhen Luo, Peng Liu, Zaiqing Nie, Yushuai Wu
First submitted to arxiv on: 6 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG); Quantitative Methods (q-bio.QM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This AI research paper presents a solution to improve clinical trial success rates by introducing DeepCRE, a pioneering AI model that predicts Cross-drug Response (CRE) effectively in the late stages of drug development. The existing methodologies are limited to early stages and have shown limited improvement to clinical success rates. DeepCRE outperforms existing models by achieving an average performance improvement of 17.7% in patient-level CRE and a 5-fold increase in indication-level CRE, enabling more accurate personalized treatment predictions and better pharmaceutical value assessment for indications. The model has also identified drug candidates with enhanced therapeutic effects, demonstrating its potential to transform drug research and development. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary DeepCRE is an AI model designed to predict how drugs will work on different patients and diseases. It’s like a supercomputer that helps scientists find the right medicine for the right person. Right now, it takes too many tests and trials to figure out which medicines will be most effective. DeepCRE can help speed up this process by looking at lots of data and making predictions about how well drugs will work. This could lead to better treatments and new medicines that are more effective. |
