Encapsulation efficiency determination methods for the analysis of different antigenic peptides within phosphatidylserine-liposomes
摘要
The prevalence of autoimmune diseases (AIDs) is increasing and persists in individuals of all ages as reported by Pisetsky (Nat Rev Nephrol, 2023). Only palliative treatments are currently available as the development of a treatment that selectively eliminates the immune system autoreaction, without affecting its normal functioning, is not an easy task. In this regard, an innovative strategy based on phosphatidylserine-liposomes (PS-Liposomes) loaded with the autoantigenic peptide that triggers the autoimmune attack has demonstrated efficacy in different AIDs as described by Almenara-Fuentes et al. (Nanomedicine 48, 2023) and Pujol-Autonell et al. (PLoS One 10, 2015). Encapsulation efficiency (EE) determination in liposomal therapeutic formulations is considered one of the most important attributes, as the encapsulated drug concentration is usually related to the treatment’s effectiveness. In this regard, several methods have been described in the literature for the determination of specific peptides within liposomes. However, the described methodologies cannot usually be applied to other peptides with different properties. In this study, peptides with different lengths and physicochemical properties encapsulated in PS-Liposome formulations were used as models to evaluate several methods for both free and total antigen quantification. Different approaches for liposome lysis and subsequent total or encapsulated antigen quantification were studied. On the other hand, a comprehensive comparison of different centrifugal filters and an ultracentrifugation method was performed for free antigen determination. Identification and quantification of the autoantigenic peptides were performed by reversed-phase high-performance liquid chromatography with ultraviolet detection (RP-HPLC-UV). Results obtained for direct and indirect EE determinations were compared for PS-Liposome formulations, and the best conditions for each peptide were selected.
Graphical Abstract