Literature DB >> 25989144

Analysis of Diffusion-Controlled Dissolution from Polydisperse Collections of Drug Particles with an Assessed Mathematical Model.

Yanxing Wang1, Bertil Abrahamsson2, Lennart Lindfors2, James G Brasseur1.   

Abstract

We introduce a "hierarchical" modeling strategy designed to be systematically extensible to increase the detail of dissolution predictions from polydisperse collections of drug particles and to be placed on firm mathematical and physical foundations with diffusion-dominated dissolution at its core to predict dissolution and the evolution of particle size distribution. We assess the model with experimental data and demonstrate higher accuracy by treating the polydisperse nature of dissolution. A level in the hierarchy is applied to study elements of diffusion-driven dissolution, in particular the role of particle-size distribution width with varying dose level and the influences of "confinement" on the process of dissolution. Confinement influences surface molecular flux, directly by the increase in bulk concentration and indirectly by the relative volume of particles to container. We find that the dissolution process can be broadly categorized within three "regimes" defined by the ratio of total concentration Ctot to solubility CS . Sink conditions apply in the first regime, when C tot /CS<∼0.1. When C tot /CS>∼5 (regime 3) dissolution is dominated by confinement and normalized saturation time follows a simple power law relationship. Regime 2 is characterized by a "saturation singularity" where dissolution is sensitive to both initial particle size distribution and confinement.
© 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Entities:  

Keywords:  computer-aided drug design; diffusion; dissolution; dissolution rate; in silico modeling; in vitro models; mathematical model; particle size; simulations; solubility

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Substances:

Year:  2015        PMID: 25989144     DOI: 10.1002/jps.24472

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  4 in total

Review 1.  Formulation predictive dissolution (fPD) testing to advance oral drug product development: An introduction to the US FDA funded '21st Century BA/BE' project.

Authors:  Bart Hens; Patrick D Sinko; Nicholas Job; Meagan Dean; Jozef Al-Gousous; Niloufar Salehi; Robert M Ziff; Yasuhiro Tsume; Marival Bermejo; Paulo Paixão; James G Brasseur; Alex Yu; Arjang Talattof; Gail Benninghoff; Peter Langguth; Hans Lennernäs; William L Hasler; Luca Marciani; Joseph Dickens; Kerby Shedden; Duxin Sun; Gregory E Amidon; Gordon L Amidon
Journal:  Int J Pharm       Date:  2018-06-23       Impact factor: 5.875

2.  Selection of In Vivo Predictive Dissolution Media Using Drug Substance and Physiological Properties.

Authors:  Deanna M Mudie; Nasim Samiei; Derrick J Marshall; Gregory E Amidon; Christel A S Bergström
Journal:  AAPS J       Date:  2020-01-27       Impact factor: 4.009

3.  Dissolution Kinetics of a BCS Class II Active Pharmaceutical Ingredient: Diffusion-Based Model Validation and Prediction.

Authors:  Yuan Gao; Brian Glennon; Yunliang He; Philip Donnellan
Journal:  ACS Omega       Date:  2021-03-19

4.  Characterization of Membrane-Type Dissolution Profiles of Clinically Available Orally Inhaled Products Using a Weibull Fit and a Mechanistic Model.

Authors:  Irès van der Zwaan; Frans Franek; Rebecca Fransson; Ulrika Tehler; Göran Frenning
Journal:  Mol Pharm       Date:  2022-08-08       Impact factor: 5.364

  4 in total

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