Diffusion-controlled Drug Delivery Systems: Calculation of the Required Composition to Achieve Desired Release Profiles
Overview
Authors
Affiliations
The aim of this study was to investigate the effect of the composition of diffusion-controlled release devices (type and amount of plasticizer, type of polymer) on the drug diffusivity and the resulting release kinetics in a quantitative way. Diltiazem hydrochloride and theophylline were investigated in ethyl cellulose (EC) and Eudragit((R)) RS 100, plasticized with various amounts of acetyltributyl citrate (ATBC), acetyltriethyl citrate (ATEC), dibutyl phthalate (DBP), dibutyl sebacate (DBS), diethyl phthalate (DEP), and tributyl citrate (TBC). Thin drug-containing films (monolithic solutions) were used to determine the diffusion coefficients experimentally. The effect of the type and amount of plasticizer on the drug diffusivity was found to be significant, whereas the chain length of the polymer only played a minor rule in the investigated systems. Interestingly, a quantitative relationship between the diffusion coefficient of the drug and the plasticizer level could be established. Based on these results, the release kinetics of diffusion-controlled drug delivery systems could be predicted. In this study, the release patterns from microparticles were calculated and the significant effect of the composition of the device on the resulting release rate was simulated. The latter could be effectively modified by varying the type and amount of plasticizer. Independent experiments verified the theoretical predictions. The practical benefit of the presented method is to calculate the required composition of diffusion-controlled drug delivery systems (monolithic solutions) to achieve desired release profiles.
Nanocellulose/Nanoporous Silicon Composite Films as a Drug Delivery System.
Garrido-Miranda K, Pesenti H, Contreras A, Vergara-Figueroa J, Recio-Sanchez G, Chumpitaz D Polymers (Basel). 2024; 16(14).
PMID: 39065372 PMC: 11280883. DOI: 10.3390/polym16142055.
Fluidic enabled bioelectronic implants: opportunities and challenges.
Coles L, Oluwasanya P, Karam N, Proctor C J Mater Chem B. 2022; 10(37):7122-7131.
PMID: 35959561 PMC: 9518646. DOI: 10.1039/d2tb00942k.
Gohn A, Nolte A, Ravotti E, Forster S, Giles M, Rudd N Pharmaceutics. 2022; 14(6).
PMID: 35745712 PMC: 9231147. DOI: 10.3390/pharmaceutics14061139.
Zaman M, Hassan R, Razzaq S, Mahmood A, Amjad M, Abdul Ghafoor Raja M Sci Prog. 2020; 103(4):36850420964302.
PMID: 33151131 PMC: 10358599. DOI: 10.1177/0036850420964302.
Bugatti V, Viscusi G, Gorrasi G Foods. 2020; 9(10).
PMID: 33036319 PMC: 7599727. DOI: 10.3390/foods9101414.