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

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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.