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Effect of network mesh size and swelling to the drug delivery from pH responsive hydrogels
Author(s) -
Hegab Rachel A.,
Pardue Sibile,
Shen Xinggui,
Kevil Christopher,
Peppas Nicholas A.,
CaldoreraMoore Mary E.
Publication year - 2020
Publication title -
journal of applied polymer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.575
H-Index - 166
eISSN - 1097-4628
pISSN - 0021-8995
DOI - 10.1002/app.48767
Subject(s) - swelling , self healing hydrogels , drug delivery , materials science , chemical engineering , acrylic acid , methacrylate , controlled release , polymer chemistry , nanotechnology , copolymer , composite material , polymer , engineering
pH responsive hydrogels are ideal platforms for numerous therapeutic delivery applications, including oral delivery, as they are capable of overcoming the many barriers that must be considered when creating an effective drug delivery system. Understanding of the innate hydrogel network structure and its swelling behavior at environmentally relevant conditions is vital for designing hydrogel network capable of effective controlled drug release. Herein, we explored how to expand traditional techniques of swelling and pore characterization to gain better insight into the performance of anionic microparticles composed of the poly(methyl methacrylate‐ co ‐acrylic acid) with varying molar percentage of 10, 20, and 30 mol% of MMA, for controlled release of low‐molecular‐weight drugs. By evaluating these carrier systems at environmental conditions, we can observe changes in swelling and pore size of the anionic hydrogel networks as a function of MMA, which was then correlated with the release profiles of the small‐molecular‐weight drug sodium nitrate. With the correlation of the swelling behavior of the networks and the release profiles, we demonstrated how the expansion of swelling parameters at relevant pH values provides further incite for evaluating for the optimal blend for controlled release. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137 , 48767.