Weibull β value for the discernment of drug release mechanism of PLGA particles

Abstract

Mathematical models are used to characterize and optimize drug release in drug delivery systems (DDS). One of the most widely used DDS is the poly(lactic-co-glycolic acid) (PLGA)-based polymeric matrix owing to its biodegradability, biocompatibility, and easy manipulation of its properties through the manipulation of synthesis processes. Over the years, the Korsmeyer-Peppas model has been the most widely used model for characterizing the release profiles of PLGA DDS. However, owing to the limitations of the Korsmeyer-Peppas model, the Weibull model has emerged as an alternative for the characterization of the release profiles of PLGA polymeric matrices. The purpose of this study was to establish a correlation between the n and β parameters of the Korsmeyer-Peppas and Weibull models and to use the Weibull model to discern the drug release mechanism. A total of 451 datasets describing the overtime drug release of PLGA-based formulations from 173 scientific articles were fitted to both models. The Korsmeyer-Peppas model had a mean Akaike Information Criteria (AIC) value of 54.52 and an n value of 0.42, while the Weibull model had a mean AIC of 51.99 and a β value of 0.55, and by using reduced major axis regression values, a high correlation was found between the n and β values. These results demonstrate the ability of the Weibull model to characterize the release profiles of PLGA-based matrices and the usefulness of the β parameter for determining the drug release mechanism.