Evidence map›Paper›PMID 36986712›Full record

ArticlePharmaceutics2023

Self-Assembled Lecithin-Chitosan Nanoparticles Improved Rotigotine Nose-to-Brain Delivery and Brain Targeting Efficiency.

Paramita Saha, Prabhjeet Singh, Himanshu Kathuria, Deepak Chitkara, Murali Monohar Pandey

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.7field-weighted citation impact, top 5% 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

12 citing papers in PubMed, 33 citations in OpenAlex.

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  12. Research progress in brain-targeted nasal drug delivery.Frontiers in aging neuroscience · 2023
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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.

Paramita SahaIndustrial Research Laboratory, Department of Pharmacy, Birla Institute of Technology & Science, Pilani Rajasthan 333031, India.
Prabhjeet SinghIndustrial Research Laboratory, Department of Pharmacy, Birla Institute of Technology & Science, Pilani Rajasthan 333031, India.
Himanshu KathuriaNusmetics Pte Ltd., E-Centre@Redhill, 3791 Jalan Bukit Merah, Singapore 159471, Singapore.ORCID 0000-0002-9502-2901
Deepak ChitkaraIndustrial Research Laboratory, Department of Pharmacy, Birla Institute of Technology & Science, Pilani Rajasthan 333031, India.
Murali Monohar PandeyIndustrial Research Laboratory, Department of Pharmacy, Birla Institute of Technology & Science, Pilani Rajasthan 333031, India.ORCID 0000-0001-8988-046X
Birla Institute of Technology and Science, Pilani · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rotigotine (RTG) is a non-ergoline dopamine agonist and an approved drug for treating Parkinson's disease. However, its clinical use is limited due to various problems, viz. poor oral bioavailability (<1%), low aqueous solubility, and extensive first-pass metabolism. In this study, rotigotine-loaded lecithin-chitosan nanoparticles (RTG-LCNP) were formulated to enhance its nose-to-brain delivery. RTG-LCNP was prepared by self-assembly of chitosan and lecithin due to ionic interactions. The optimized RTG-LCNP had an average diameter of 108 nm with 14.43 ± 2.77% drug loading. RTG-LCNP exhibited spherical morphology and good storage stability. Intranasal RTG-LCNP improved the brain availability of RTG by 7.86 fold with a 3.84-fold increase in the peak brain drug concentration (C

Indexed as

brain distribution studyintranasal deliverylecithin-chitosan hybrid nanoparticlesnose-to-brain uptakerotigotine

Identifiers

PMID36986712
PMCPMC10052746
OpenAlexW4323313218

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.