Enhanced Analytic Approach for Describing pH Triggered Fast Drug Release Systems

Elmas A., Akyuz G., Bergal A., Andaç M., Andaç Ö.

CURRENT DRUG DELIVERY, vol.18, no.8, pp.1118-1124, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 18 Issue: 8
  • Publication Date: 2021
  • Doi Number: 10.2174/1567201818999210112181853
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, Biotechnology Research Abstracts, Chemical Abstracts Core, EMBASE, MEDLINE
  • Page Numbers: pp.1118-1124
  • Keywords: Drug release, drug delivery, mathematical modeling, controlled release, pH, blood circulation
  • Ondokuz Mayıs University Affiliated: Yes


Background: pH sensitive dendrimers attached to nanocarriers, as one of the drug release systems, have become quite popular due to their ease of manufacture in experimental conditions and the ability to generate fast drug release in the targeted area. This kind of fast release behavior cannot be represented properly in most of the existing kinetic mathematical models. Besides, these models have either no pH dependence or pH dependence added separately. Therefore, they remained one dimensional. Objective: The aim of this study was to establish the proper analytic equation to describe the fast release of drugs from pH sensitive nanocarrier systems, and to combine it with the pH dependent equation for to establish a two-dimensional model for whole system. Methods: We used four common kinetic models for the comparison and we fitted them to the release data. As a result, only Higuchi and Korsmeyer-Peppas models show acceptable suitable results. None of these models have pH dependence. To get a better description for pH triggered fast release, we observed the behavior of the slope angle of the release curve. Then we proposed a new analytic equation by using relation between the slope angle and time. Result: By adding a pH dependent equation, we assumed the drug release is "on" or "off" above/below specific pH value and we modified a step function to get a desired behavior. Conclusion: Our new analytic model shows good fitting, not only one-dimensional time dependent release, but also two-dimensional pH dependent release, that provides a useful analytic model to represent release profiles of pH sensitive fast drug release systems.