Evidence map›Paper›PMID 36559297›Full record

ArticlePharmaceutics2022

Enhanced Micro-Channeling System via Dissolving Microneedle to Improve Transdermal Serum Delivery for Various Clinical Skincare Treatments.

Jeeho Sim, SeongDae Gong, Geonwoo Kang, Mingyu Jang, Huisuk Yang, Jaesung Park, Youngchan Kim, Hyunkyu Lee, Hyunji Jung, Youseong Kim and 6 more

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 49% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
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

16 authors at 2 institutions in 1 country.

Jeeho SimDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.ORCID 0000-0003-1686-5642
SeongDae GongDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Geonwoo KangDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.ORCID 0000-0002-5716-5426
Mingyu JangJUVIC Inc., No. 208, Digital-ro 272, Guro-gu, Seoul 08389, Republic of Korea.ORCID 0000-0003-0869-5719
Huisuk YangJUVIC Inc., No. 208, Digital-ro 272, Guro-gu, Seoul 08389, Republic of Korea.
Jaesung ParkGraduate School, Department of Mechanical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea.ORCID 0000-0003-1396-5760
Youngchan KimGraduate School, Department of Mechanical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea.
Hyunkyu LeeDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Hyunji JungDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Youseong KimDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Chansol JeonDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Hyeri AhnDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.ORCID 0000-0002-6065-1345
Minkyung KimDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Jaibyung ChoiDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Ho LeeSchool of Convergence, Department of Robot and Smart System Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea.
Hyungil JungDepartment of Biotechnology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Yonsei University · KRKyungpook National University · KR

Funding

Ministry of Trade, Industry and Energy 20000462
6 · The paper itself

Abstract

Topical liquid formulations, dissolving microneedles (DMNs), and microscale needles composed of biodegradable materials have been widely used for the transdermal delivery of active compounds for skincare. However, transdermal active compound delivery by topical liquid formulation application is inhibited by skin barriers, and the skincare efficacy of DMNs is restricted by the low encapsulation capacity and incomplete insertion. In this study, topical serum application via a dissolvable micro-channeling system (DMCS) was used to enhance serum delivery through micro-channels embedded with DMNs. Transdermal serum delivery was evaluated after the topical-serum-only application and combinatorial serum application by assessing the intensity of allophycocyanin (APC) loaded with the serum in the porcine skin. APC intensity was significantly higher in the skin layer at a depth of 120-270 μm upon combinatorial serum application as compared to topical-serum-only application. In addition, the combinatorial serum application showed significantly improved efficacy in the clinical assessment of skin hydration, depigmentation, improvement of wrinkles, elasticity, dermal density, skin pores, and skin soothing without any safety issues compared to the serum-only application. The results indicate that combinatorial serum application with DMCS is a promising candidate for improving skincare treatments with optimal transdermal delivery of active compounds.

Indexed as

dissolvable micro-channeling systemserumskin depigmentationskin hydrationtopical applicationtransdermal deliverywrinkle improvement

Identifiers

PMID36559297
PMCPMC9781352
OpenAlexW4311510819

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.