A Comparative Mathematical Analysis of Drug Release from Lipid-Based Nanoparticles

• Published in: AAPS PharmSciTech Vol. 25; no. 7; p. 208
• Main Authors: Porbaha, Pedram, Ansari, Ramin, Kiafar, Mohammad Reza, Bashiry, Rahman, Khazaei, Mohammad Mehdi, Dadbakhsh, Amirhossein, Azadi, Amir
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 05.09.2024
• Subjects: Biochemistry; Biomedical and Life Sciences; Biomedicine; Biotechnology; Chemistry, Pharmaceutical - methods; Drug Carriers - chemistry; Drug Delivery Systems - methods; Drug Liberation; Emulsions - chemistry; Lipids - chemistry; Liposomes - chemistry; Models, Theoretical; Nanoparticles - chemistry; Pharmacology/Toxicology; Pharmacy; Research Article; release kinetics; nano/micro emulsions; lipid-based nanoparticles; liposomes; nanostructured lipid carriers; solid lipid nanoparticles
• ISSN: 1530-9932; 1530-9932
• DOI: 10.1208/s12249-024-02922-7

Mathematical modeling of drug release from drug delivery systems is crucial for understanding and optimizing formulations. This research provides a comparative mathematical analysis of drug release from lipid-based nanoparticles. Drug release profiles from various types of lipid nanoparticles, including liposomes, nanostructured lipid carriers (NLCs), solid lipid nanoparticles (SLNs), and nano/micro-emulsions (NEMs/MEMs), were extracted from the literature and used to assess the suitability of eight conventional mathematical release models. For each dataset, several metrics were calculated, including the coefficient of determination (R 2 ), adjusted R 2 , the number of errors below certain thresholds (5%, 10%, 12%, and 20%), Akaike information criterion (AIC), regression sum square (RSS), regression mean square (RMS), residual sum of square (rSS), and residual mean square (rMS). The Korsmeyer-Peppas model ranked highest among the evaluated models, with the highest adjusted R 2 values of 0.95 for NLCs and 0.93 for other liposomal drug delivery systems. The Weibull model ranked second, with adjusted R 2 values of 0.92 for liposomal systems, 0.94 for SLNs, and 0.82 for NEMs/MEMs. Thus, these two models appear to be more effective in forecasting and characterizing the release of lipid nanoparticle drugs, potentially making them more suitable for upcoming research endeavors. Graphical Abstract