Chitosan–Alginate Polyelectrolyte Systems: From Classical Release Models to the D‐PARMO Framework.
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| Title: | Chitosan–Alginate Polyelectrolyte Systems: From Classical Release Models to the D‐PARMO Framework. |
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| Authors: | Rekab, Parastoo1 (AUTHOR) 22701890@emu.edu.tr, Oladipo, Akeem Adeyemi2 (AUTHOR) akeem.oladipo@emu.edu.tr |
| Source: | Macromolecular Materials & Engineering. May2026, Vol. 311 Issue 5, p1-33. 33p. |
| Subjects: | Polyelectrolytes, Electrostatic interaction, Alginic acid, Drug delivery systems, Chitosan, Macroscopic kinetics |
| Abstract: | Despite the extensive preclinical optimization of biocompatible chitosan–alginate (CS/ALG) polyelectrolyte complexes for drug delivery, their clinical translation is hindered by a lack of predictive models linking formulation parameters to in vivo performance. This review bridges this "predictive gap" by critically deconstructing the physicochemical foundations of CS/ALG systems. We highlight the inadequacy of classical semi‐empirical models (e.g., Higuchi, Korsmeyer‐Peppas), which rely on descriptive curve‐fitting rather than a priori prediction. To overcome this, we introduce the Dual‐Polyelectrolyte Adaptive Release Mechanistic Outlook (D‐PARMO). This novel framework mechanistically unifies the key coupled phenomena governing release: dual‐polymer ionization equilibria, Flory‐Rehner swelling, Donnan partitioning, and multi‐modal transport kinetics. We condense this into an operational model that translates release data into physically meaningful parameters: a diffusion rate constant (kd), erosion/swelling amplitude and rate (ke, ks), and an electrostatic coupling coefficient (α). Comparative simulations demonstrate that D‐PARMO successfully identifies underlying physical drivers where classical models fail. Adopting this mechanistically informed operational framework provides a rational, science‐based pathway to support the design and de‐risk the translation of smart biomaterials. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Despite the extensive preclinical optimization of biocompatible chitosan–alginate (CS/ALG) polyelectrolyte complexes for drug delivery, their clinical translation is hindered by a lack of predictive models linking formulation parameters to in vivo performance. This review bridges this "predictive gap" by critically deconstructing the physicochemical foundations of CS/ALG systems. We highlight the inadequacy of classical semi‐empirical models (e.g., Higuchi, Korsmeyer‐Peppas), which rely on descriptive curve‐fitting rather than a priori prediction. To overcome this, we introduce the Dual‐Polyelectrolyte Adaptive Release Mechanistic Outlook (D‐PARMO). This novel framework mechanistically unifies the key coupled phenomena governing release: dual‐polymer ionization equilibria, Flory‐Rehner swelling, Donnan partitioning, and multi‐modal transport kinetics. We condense this into an operational model that translates release data into physically meaningful parameters: a diffusion rate constant (kd), erosion/swelling amplitude and rate (ke, ks), and an electrostatic coupling coefficient (α). Comparative simulations demonstrate that D‐PARMO successfully identifies underlying physical drivers where classical models fail. Adopting this mechanistically informed operational framework provides a rational, science‐based pathway to support the design and de‐risk the translation of smart biomaterials. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 14387492 |
| DOI: | 10.1002/mame.70232 |
