Construction of Sonosensitizer‐Drug Co‐Assembly Based on Deep Learning Method (Small 40/2025)
Drug Co-Assemblies An artificial intelligence-based sonosensitizer-drug interaction model was proposed to construct co-assembled drugs, achieving 90.00% accuracy and 96.00% recall. Ablation experiments and gradient visualization analyzed the impact of atomic properties and molecular structures on predictions. Using this model, a nanomedicine composed of methotrexate and emodin was successfully constructed for liver cancer treatment guided by fluorescence imaging. More in article number 2502328, Yang Zhao, Dong Li, Gang Liu, and co-workers.
Authors
- Xiaowei Lu (ORCID: https://orcid.org/0000-0002-0205-6142)
- Liuyin Yang (ORCID: https://orcid.org/0000-0002-4095-8841)
- Yang Zhao (ORCID: https://orcid.org/0000-0002-5140-5126)
- Kanqi Wang (ORCID: https://orcid.org/0000-0002-4703-8677)
- Yilin Wang (ORCID: https://orcid.org/0000-0001-6582-923X)
- Gang Liu (ORCID: https://orcid.org/0000-0003-2613-7286)
- Man Cheng (ORCID: https://orcid.org/0009-0002-2322-0551)
- Qingmin Chen (ORCID: https://orcid.org/0000-0002-5645-3338)
- Xiran Gui
- Dong Sheng Li
Institutions
- Jimei University (CN)
- Xiamen University (CN)
- Xiamen University of Technology (CN)
Publication Details
- Journal
- Small
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/smll.70744
- Primary Topic
- Innovative Microfluidic and Catalytic Techniques Innovation
- Type
- article
- Field-Weighted Citation Impact
- 0.00