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Pharmaceutical Nanotechnology

Editor-in-Chief

ISSN (Print): 2211-7385
ISSN (Online): 2211-7393

Research Article

Formulation Development of Folic Acid Conjugated PLGA Nanoparticles for Improved Cytotoxicity of Caffeic Acid Phenethyl Ester

Author(s): Harshad S. Kapare , Sathiyanarayanan Lohidasan*, Arulmozhi Sinnathambi and Kakasaheb Mahadik

Volume 9, Issue 2, 2021

Published on: 11 January, 2021

Page: [111 - 119] Pages: 9

DOI: 10.2174/2211738509666210111160528

Price: $65

Abstract

Background: Honey bee propolis is one of the natural products reported in various traditional systems of medicines, including Ayurveda. Caffeic acid phenethyl ester (CAPE) is an active constituent of propolis which is well known for its anticancer potential. The therapeutic effects of CAPE are restricted owing to its less aqueous solubility and low bioavailability.

Objective: In this study CAPE loaded folic acid conjugated nanoparticle system (CLFPN) was investigated to enhance solubility, achieve sustained drug release, and improved cytotoxicity of CAPE

Methods: Formulation development, characterization, and optimization were carried out by the design of experiment approach. In vitro and in vivo cytotoxicity study was carried out for optimized formulations.

Results: Developed nanoparticles showed particle size and encapsulation efficiency of 170 ± 2-195 ± 3 nm and 75.66 ± 1.52-78.80 ± 1.25%, respectively. Optimized formulation CLFPN showed sustained drug release over a period of 42 h. GI50 concentration was decreased by 46.09% for formulation compared to CAPE in MCF-7 cells, indicating the targeting effect of CLFPN. An improved in vitro cytotoxic effect was reflected in the in vivo Daltons Ascites Lymphoma model by reducing tumor cell count.

Conclusion: The desired nanoparticle characteristic with improved in vivo and in vitro cytotoxicity was shown by the developed formulation. Thus it can be further investigated for biomedical applications.

Keywords: Anticancer, drug delivery, CAPE, nanotechnology, SRB assay, caffeic acid.

Graphical Abstract


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