2018/03/31 by Kosmas Kosmidis, Panos Macheras
Biochemistry, Genetics and Molecular Biology · Chemistry · Mathematics · Pharmacology, Toxicology and Pharmaceutics · Physics and Astronomy · #Analytical Chemistry and Chromatography #Biological system #Biology #Chemistry #Classical mechanics #Drug Solubulity and Delivery Systems #Fractal #Function (biology) #Kinetics #Mathematical analysis #Mathematics #Monte Carlo method #Physics #Protein purification and stability #Statistical physics #Statistics #Thermodynamics #Weibull distribution #physics.bio-ph
paper · pdf · doi:10.1016/j.ijpharm.2018.03.060
published as Int. Journal of Pharmaceutics, volume 543, pages 269-273 (2018)
openalex publication_date 2018/03/31 · arxiv created 2018/05/04 · arxiv updated 2018/05/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We compare two of the most successful models for the description and analysis of drug release data. The fractal kinetics approach leading to release profiles described by a Weibull function and the fractional kinetics approach leading to release profiles described by a Mittag-Leffler function. We used Monte Carlo simulations to generate artificial release data from euclidean and fractal substrates. We have also used real release data from the literature and found that both models are capable in describing release data up to roughly 85% of the release. For larger times both models systematically overestimate the number of particles remaining in the release device.