ArticleInternational journal of pharmaceutics2024
Development of in situ forming implants for controlled delivery of punicalagin.
Article in International journal of pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- An Overview of In Vitro Release Methods for Long-Acting Injectable Products Based on PLGA.Methods and protocols · 2026Review
- PLGA-Based In Situ-Forming Implants, a Quality by Design Perspective.Pharmaceutics · 2026Review
- Phase-Inversion In Situ Systems: Problems and Prospects of Biomedical Application.Pharmaceutics · 2025Review
- In Silico Insights into the Inhibition of ADAMTS-5 by Punicalagin and Ellagic Acid for the Treatment of Osteoarthritis.International journal of molecular sciences · 2025Article
- Advanced nanoparticles for osteoarthritis: a review.Frontiers in medicine · 2025Review
- Fabrication and Optimization of a Silodosin In Situ-Forming PLGA Implants for the Treatment of Benign Prostatic Hyperplasia: In Vitro and In Vivo Study.Pharmaceutics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Due to efficient drainage of the joint, the development of intra-articular depots for long-lasting drug release is a difficult challenge. Moreover, a disease-modifying osteoarthritis drug (DMOAD) that can effectively manage osteoarthritis has yet to be identified. The current study was undertaken to explore the potential of injectable, in situ forming implants to create depots that support the sustained release of punicalagin, a promising DMOAD. In vitro experiments demonstrated punicalagin's ability to suppress production of interleukin-1β and prostaglandin E2, confirming its chondroprotective properties. Regarding the entrapment of punicalagin, it was demonstrated by LC-MS/MS to be stable within PLGA in situ forming implants for several weeks and capable of inhibiting collagenase upon release. In vitro punicalagin release kinetics were tunable through variation of solvent, PLGA lactide:glycolide ratio, and polymer concentration, and an optimized formulation supported release for approximately 90 days. The injection force of this formulation steadily increased with plunger advancement and higher rates of advancement were associated with greater forces. Although the optimal formulation was highly cytotoxic to primary chondrocytes if cells were exposed immediately or shortly after implant formation, upwards of 70 % survival was achieved when the implants were first allowed to undergo a 24-72 h period of phase inversion prior to cell exposure. This study demonstrates a PLGA-based in situ forming implant for the controlled release of punicalagin. With modification to address cytotoxicity, such an implant may be suitable as an intra-articular therapy for OA.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.