Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data
Machine learning effectively identified baseline characteristics predictive of HbA1c response to imeglimin, supporting the potential for personalized type 2 diabetes treatment strategies.
Authors
- Kohei Kaku (ORCID: https://orcid.org/0000-0003-1574-0565)
- Katsuhiko Hagi (ORCID: https://orcid.org/0000-0003-1389-1474)
- Kazumasa Yoshida (ORCID: https://orcid.org/0000-0002-0181-9857)
- Kohjiro Ueki (ORCID: https://orcid.org/0000-0003-1523-8102)
- Hirotaka Watada
Institutions
- Kawasaki Medical School (JP)
- Sumitomo Dainippon Pharma (Japan) (JP)
- Juntendo University (JP)
- National Center for Global Health and Medicine (JP)
Publication Details
- Journal
- Journal of Diabetes Investigation
- Published
- 2025-12-08
- DOI
- https://doi.org/10.1111/jdi.70215
- Primary Topic
- Diabetes Management and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Eli Lilly and Company
- AstraZeneca
- Sanofi
- Abbott Japan
- Kowa Company
- Kissei
- Boehringer Ingelheim Japan
- Novo Nordisk
- Astellas Pharma
- Teijin Pharma
- Mitsubishi Tanabe Pharma Corporation
- Ono Pharmaceutical
- Eli Lilly Japan
- Daiichi Sankyo Europe