Home › Research › Digital health tools
The role for artificial intelligence in identifying combination therapies for Alzheimer’s disease
Feixiong Cheng, Zhendong Sha, Yadi Zhou, Yuan Hou, Pengyue Zhang, Andrew A. Pieper, Jeffrey L. Cummings. The Journal of Prevention of Alzheimer s Disease, 2025-10-27
Topic: Amyloid, tau and blood-test diagnosis
Despite substantial investment in biomedical and pharmaceutical research over the past two decades, the global prevalence of Alzheimer's disease (AD) and AD-related dementias (AD/ADRD) is still rising. This underscores the significant unmet need for identifying effective disease-modifying therapies. Here, we provide a critical perspective on the application of data science and artificial intelligence (AI) to the rational design of drug combinations in AD and ADRD, addressing their potential to transform therapeutic development. We examine AI's current and prospective capabilities in therapeutic discovery, identify areas where AI-driven strategies can enhance drug combination development, and outline how multidisciplinary professionals in the field, including clinical trialists, neuropsychiatrists, pharmacologists, medicinal chemists, and computational scientists, can leverage these tools to address therapeutic gaps. We also highlight AI's role in synthesizing the rapidly growing amount of biomedical data in the field of AD/ADRD, especially clinical trials, biomarkers, multi-omics data (genomics, transcriptomics, proteomics, metabolomics, interactomics, and radiomics), and real-world patient data. We further explore AI's utility in prioritizing potential drug combination regimens and estimating clinical effect size in combination therapy trials for AD/ADRD. Lastly, we emphasize AI-powered network medicine methodologies for prioritizing drug combinations targeting AD/ADRD co-pathologies and summarize the challenges of their translation to clinical practice.
Key findings
- This underscores the significant unmet need for identifying effective disease-modifying therapies.
Why it matters
This perspective discusses how data science and AI could help design combinations of drugs for Alzheimer's disease and related dementias. It is a discussion of a possible approach, not evidence that any combination therapy works to treat, cure, or prevent the disease.
New to this subject? Start with our plain-English guide: Digital health →
Study details
- Evidence strengthLow
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (The Journal of Prevention of Alzheimer s Disease) |
| Journal's citation record | 0 / 4 | The Journal of Prevention of Alzheimer s Disease: journal h-index 63 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 5 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 2.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 5 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Jeffrey L. Cummings: h-index 175 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Case Western Reserve University: institution h-index 1,159 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 8 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41145341) |
| Free to read | 2 / 2 | Free to read |
| Total | 39 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1016/j.tjpad.2025.100366
- PubMed: 41145341
- Original source →
- Free full text: The Journal of Prevention of Alzheimer s Disease →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Cheng, F., Sha, Z., Zhou, Y., Hou, Y., Zhang, P., Pieper, A. A., et al. (2025). The role for artificial intelligence in identifying combination therapies for Alzheimer’s disease. The Journal of Prevention of Alzheimer s Disease. https://doi.org/10.1016/j.tjpad.2025.100366
Vancouver
Cheng F, Sha Z, Zhou Y, Hou Y, Zhang P, Pieper AA, et al. The role for artificial intelligence in identifying combination therapies for Alzheimer’s disease. The Journal of Prevention of Alzheimer s Disease. 2025. doi:10.1016/j.tjpad.2025.100366. PMID: 41145341.
BibTeX
@article{cheng2025-41145341,
author = {Cheng, Feixiong and Sha, Zhendong and Zhou, Yadi and Hou, Yuan and Zhang, Pengyue and Pieper, Andrew A. and Cummings, Jeffrey L.},
title = {{The role for artificial intelligence in identifying combination therapies for Alzheimer’s disease}},
journal = {The Journal of Prevention of Alzheimer s Disease},
year = {2025},
doi = {10.1016/j.tjpad.2025.100366},
pmid = {41145341},
url = {https://doi.org/10.1016/j.tjpad.2025.100366}
}
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.