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Chitosan–Alginate Polyelectrolyte Systems: From Classical Release Models to the D-PARMO Framework
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DOI：10.1002/mame.70232.png)
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Abstract
En 中文
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.
Keywords:
clinical translation
controlled release
D-PARMO
drug delivery
nanocarriers
polyelectrolyte complex
predictive modeling
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