Evidence map›Paper›PMID 35214018›Full record

ReviewPharmaceutics2022

Nanostructured Drug Delivery Systems for Targeting 5-α-Reductase Inhibitors to the Hair Follicle.

Silvia Tampucci, Valentina Paganini, Susi Burgalassi, Patrizia Chetoni, Daniela Monti

Open access · goldAbstract readReview
In one paragraph

Review in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 24 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Silvia TampucciDepartment of Pharmacy, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0002-8927-6083
Valentina PaganiniDepartment of Pharmacy, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0002-5864-2845
Susi BurgalassiDepartment of Pharmacy, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0002-0795-2886
Patrizia ChetoniDepartment of Pharmacy, University of Pisa, 56126 Pisa, Italy.
Daniela MontiDepartment of Pharmacy, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0001-7622-4367
University of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Androgenetic alopecia is a multifactorial condition characterized by noticeable hair loss, affecting both men and women and representing a debilitating and chronic disorder that considerably affects the quality of life. Available topical treatments based on minoxidil or finasteride require repeated applications and are associated with a certain number of adverse effects. The challenges associated with current treatments pave the way for the research of new therapeutic strategies, more precise and selective, and capable of providing long-term results. In this context, the present review examines the new proposed formulation strategies to deliver 5-α-reductase inhibitors in order to obtain a targeted drug delivery, for improving drug retention at the site of action in the hair follicle, contemporaneously reducing drug systemic absorption, which is the cause of important adverse effects. In particular, the research will be focused on the several aspects that influence the performance of nanostructured drug delivery systems in creating a depot in the hair follicles, such as particle size, surface charge, excipients, and combined application with external stimuli (infrared radiation, mechanical massage, ultrasounds application).

Indexed as

androgenetic alopeciadrug deliverydutasteridefinasteridehair folliclenanostructuresskin

Identifiers

PMID35214018
PMCPMC8876829
OpenAlexW4210736029

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.