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44/100

✓ Peer-reviewed alzhub usefulness score 44 out of 100. Digital health tools

Topic: Amyloid, tau and blood-test diagnosis

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disorder, recognized as the most prevalent form of dementia. It is characterized by multiple pathological processes, including amyloid-beta accumulation, neurofibrillary tangles, and neuroinflammation. The therapeutic efficacy of traditional single-target drugs has been limited, failing to cure, halt, or reverse disease progression. Therefore, this complex disease warrants comprehensive therapeutic strategies like multi-target drug design (MTDD). MTDD represents a promising strategy to target multiple pathological pathways concurrently. The integration of advanced technologies, including artificial intelligence, machine learning, and nanomedicine, can further enhance the precision and effectiveness of MTDD. This review explores various MTDD approaches, including multi-target-directed ligands, multi-target compound combinations, and polypharmacology. These strategies aim to address the multifaceted nature of AD pathology more effectively than single-target approaches. MTDD offers key advantages, including pathway-level synergy, broader therapeutic scope, and potential for improved efficacy. However, MTDD faces various challenges and limitations, such as the complexity of drug design, difficulty of crossing the blood-brain barrier, and regulatory hurdles. Despite these challenges, recent advancements in computational methods and drug delivery systems show promise in overcoming these barriers. Future research should focus on optimizing delivery systems, improving in silico modeling, and translating multi-target strategies into clinically viable therapies for AD. This review addresses these needs by critically analyzing recent technologies, advantages, challenges, limitations, and future directions of MTDD, underscoring its potential to transform AD treatment.

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

APA 7th

Hossain, M. S., & Hussain, M. H. (2025). Multi-Target Drug Design in Alzheimer's Disease Treatment: Emerging Technologies, Advantages, Challenges, and Limitations. Pharmacology research & perspectives. https://doi.org/10.1002/prp2.70131

Vancouver

Hossain MS, Hussain MH. Multi-Target Drug Design in Alzheimer's Disease Treatment: Emerging Technologies, Advantages, Challenges, and Limitations. Pharmacology research & perspectives. 2025. doi:10.1002/prp2.70131. PMID: 40531439.

BibTeX

@article{hossain2025-40531439,
  author  = {Hossain, M. S. and Hussain, M. H.},
  title   = {{Multi-Target Drug Design in Alzheimer's Disease Treatment: Emerging Technologies, Advantages, Challenges, and Limitations}},
  journal = {Pharmacology research \& perspectives},
  year    = {2025},
  doi     = {10.1002/prp2.70131},
  pmid    = {40531439},
  url     = {https://doi.org/10.1002/prp2.70131}
}

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Key findings

MTDD offers key advantages, including pathway-level synergy, broader therapeutic scope, and potential for improved efficacy.
However, MTDD faces various challenges and limitations, such as the complexity of drug design, difficulty of crossing the blood-brain barrier, and regulatory hurdles.
Despite these challenges, recent advancements in computational methods and drug delivery systems show promise in overcoming these barriers.
Future research should focus on optimizing delivery systems, improving in silico modeling, and translating multi-target strategies into clinically viable therapies for AD.
This review addresses these needs by critically analyzing recent technologies, advantages, challenges, limitations, and future directions of MTDD, underscoring its potential to transform AD treatment.

Why it matters

This review describes multi-target drug design as a strategy to target multiple pathological pathways in Alzheimer's disease at once, since traditional single-target drugs have failed to cure, halt, or reverse disease progression. It notes that this approach faces challenges including complex drug design, difficulty crossing the blood-brain barrier, and regulatory hurdles.

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Study details

Evidence strengthLow

How this study scored 44/100

Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.

Component	Points	Why
Journal tier	7 / 10	Tier 3 — peer-reviewed journal (Pharmacology research & perspectives)
Journal's citation record	0 / 4	Pharmacology Research & Perspectives: journal h-index 61 (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)
Randomized / blinded	0 / 2	No randomization or blinding stated — scores zero (not stated in the record — scored 0)
Times cited	4 / 7	Cited 90 times (OpenAlex, 2026-10-10)
Citations per year	4 / 5	30.0 citations a year over 3 year(s) since 2025
Impact for its field and year	6 / 6	Cited 49.4× 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	3 / 4	Cited 90 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record	1 / 4	Last-listed author Md Hamed Hussain: h-index 6 (OpenAlex, whole career)
Institution's track record	0 / 3	East West University: institution h-index 100 (OpenAlex)
Multicenter collaboration	0 / 3	OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete)
Indexed in PubMed	2 / 2	Indexed in PubMed (PMID 40531439)
Free to read	2 / 2	Free to read
Total	44 / 100	—

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