Evidence map›Paper›PMID 41898168›Full record

ReviewBiomedicines2026

Nanotechnology-Based Strategies for Hair Regeneration: Mechanistic Insights and Translational Perspectives for Androgenetic Alopecia.

Wenran Zhou, Rongcheng Han

Abstract readReview
In one paragraph

Review in Biomedicines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Wenran ZhouBeijing Hairverse Biotechnology Co., Ltd., Beijing 100192, China.
Rongcheng HanLaboratory of Integrative Physiology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0002-5058-3932

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Androgenetic alopecia (AGA) is a highly prevalent and progressive disorder characterized by follicular miniaturization and dysregulation of the hair follicle microenvironment. Although minoxidil (MXD) and finasteride remain first-line therapies, their long-term efficacy is limited by poor follicular bioavailability, systemic side effects, and suboptimal patient compliance. In recent years, nanotechnology-based strategies have emerged as promising alternatives by enabling efficient follicular targeting and controlled therapeutic delivery. This review critically summarizes recent advances in nanotechnology-enabled approaches for AGA management, including nanocarrier-based formulations and nanotechnology-based microneedle systems. Beyond functioning as passive drug carriers, emerging nanoplatforms increasingly act as active modulators of the follicular niche by attenuating oxidative stress, inflammation, impaired angiogenesis, and stem cell dysfunction-key pathological drivers of AGA progression-thereby representing a conceptual shift from delivery-centered to microenvironment-remodeling strategies. To enhance translational relevance, we compare nanotechnology-based therapies with conventional treatments in terms of efficacy, safety, and clinical feasibility, and summarize representative preclinical studies, patent landscapes, and ongoing or completed clinical trials. Finally, key challenges related to safety evaluation, manufacturing reproducibility, and regulatory classification are discussed, highlighting nanotechnology as a promising framework for next-generation, mechanism-oriented AGA therapy and precision trichology.

Indexed as

androgenetic alopeciahair folliclehair regenerationnanomaterialsnanotechnogytranslational nanomedicine

Identifiers

PMID41898168
PMCPMC13023890

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.