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Mathematical model accurately predicts protein release from an affinity-based delivery system.

Katarina Vulic1, Malgosia M Pakulska2, Rohit Sonthalia3

  • 1Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3E1, Canada; The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.

Journal of Controlled Release : Official Journal of the Controlled Release Society
|December 3, 2014
PubMed
Summary

Controlled release systems using affinity binding can be tuned by diffusion and unbinding kinetics. This mathematical model explains how to control therapeutic release profiles by adjusting binding strength and system geometry.

Keywords:
Affinity releaseControlled releaseDimensionless analysisMathematical modelingProtein releaseProtein stability

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Area of Science:

  • Biomaterials Science
  • Drug Delivery Systems
  • Chemical Engineering

Background:

  • Affinity-based controlled release utilizes transient binding and unbinding for therapeutic delivery.
  • Understanding the parameters that govern release kinetics is crucial for optimizing drug delivery systems.

Purpose of the Study:

  • To develop a mathematical model for analyzing affinity-based controlled release.
  • To identify key parameters that can be modulated to control therapeutic release profiles.

Main Methods:

  • Mathematical modeling based on simple binding kinetics.
  • Comprehensive asymptotic analysis to identify release regimes.
  • Validation using simulations and experimental data from an affinity release system.

Main Results:

  • Identified three characteristic release regimes controlled by diffusion or unbinding kinetics.
  • Demonstrated that release can occur in single or dual stages.
  • Provided equations for tuning release rate by altering affinity strength (KD), ligand concentration, dissociation rate (koff), and hydrogel properties.

Conclusions:

  • The mathematical model provides a fundamental framework for understanding and controlling affinity-based release.
  • The findings explain discrepancies in existing literature regarding release parameters.
  • The analysis is applicable to any single-species affinity-based system for designing desired release profiles.