Microneedle Technology in Psoriasis Management: Mechanistic Insights, Technological Innovation, Clinical Progress, and Challenges
Bibliographic record
Abstract
Psoriasis is a chronic dermatological disorder that affects millions worldwide, impairing their quality of life. Current therapeutic modalities, topical, conventional systemic, and biologic, present significant limitations. Topical agents often exhibit inadequate penetration through psoriatic plaques, yielding suboptimal outcomes. Systemic therapies and biologics, while more potent, carry risks of serious adverse effects, necessitating rigorous monitoring and limiting their long-term utility. Despite these challenges, optimizing existing treatment strategies remains valuable. Microneedle technology has emerged as a minimally invasive, skin-targeted approach offering enhanced drug delivery, localization, and patient compliance. This review provides an in-depth analysis of microneedle-based strategies tailored for psoriasis, beginning with current therapy shortcomings, unmet needs in psoriasis management, and principles of microneedle technology. We then critically evaluate microneedle integration across diverse therapeutic domains, from topical formulations to biologics, off-label therapies, and phytomedicines, alongside emerging therapeutic innovations. Additionally, we highlight microneedle potential in psoriasis diagnosis and monitoring, underscoring its versatility and growing significance in psoriasis management. The review wraps up by discussing key limitations of microneedle technology, outlining strategic pathways for clinical translation, and offering a comparative perspective of various microneedle types in psoriasis care. Altogether, microneedles represent a paradigm shift toward precision dermatology, with the potential to revolutionize psoriasis management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".