Literature DB >> 10393573

General solution for diffusion-controlled dissolution of spherical particles. 1. Theory.

J Wang1, D R Flanagan.   

Abstract

Three classical particle dissolution rate expressions are commonly used to interpret particle dissolution rate phenomena. Our analysis shows that an assumption used in the derivation of the traditional cube-root law may not be accurate under all conditions for diffusion-controlled particle dissolution. Mathematical analysis shows that the three classical particle dissolution rate expressions are approximate solutions to a general diffusion layer model. The cube-root law is most appropriate when particle size is much larger than the diffusion layer thickness, the two-thirds-root expression applies when the particle size is much smaller than the diffusion layer thickness. The square-root expression is intermediate between these two models. A general solution to the diffusion layer model for monodispersed spherical particles dissolution was derived for sink and nonsink conditions. Constant diffusion layer thickness was assumed in the derivation. Simulated dissolution data showed that the ratio between particle size and diffusion layer thickness (a0/h) is an important factor in controlling the shape of particle dissolution profiles. A new semiempirical general particle dissolution equation is also discussed which encompasses the three classical particle dissolution expressions. The success of the general equation in explaining limitations of traditional particle dissolution expressions demonstrates the usefulness of the general diffusion layer model.

Mesh:

Year:  1999        PMID: 10393573     DOI: 10.1021/js980236p

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


  26 in total

1.  Modeling heterogeneity of properties and random effects in drug dissolution.

Authors:  P Lánský; M Weiss
Journal:  Pharm Res       Date:  2001-07       Impact factor: 4.200

2.  Utility of Physiologically Based Pharmacokinetic Absorption Modeling to Predict the Impact of Salt-to-Base Conversion on Prasugrel HCl Product Bioequivalence in the Presence of Proton Pump Inhibitors.

Authors:  Jianghong Fan; Xinyuan Zhang; Liang Zhao
Journal:  AAPS J       Date:  2017-07-14       Impact factor: 4.009

Review 3.  Mechanistic approaches to predicting oral drug absorption.

Authors:  Weili Huang; Sau Lawrence Lee; Lawrence X Yu
Journal:  AAPS J       Date:  2009-04-21       Impact factor: 4.009

Review 4.  Understanding the effect of API properties on bioavailability through absorption modeling.

Authors:  Filippos Kesisoglou; Yunhui Wu
Journal:  AAPS J       Date:  2008-11-06       Impact factor: 4.009

5.  Utility of physiologically based modeling and preclinical in vitro/in vivo data to mitigate positive food effect in a BCS class 2 compound.

Authors:  Binfeng Xia; Tycho Heimbach; Tsu-han Lin; Shoufeng Li; Hefei Zhang; Jennifer Sheng; Handan He
Journal:  AAPS PharmSciTech       Date:  2013-08-17       Impact factor: 3.246

6.  Dissolution testing of powders for inhalation: influence of particle deposition and modeling of dissolution profiles.

Authors:  Sabine May; Birte Jensen; Claudius Weiler; Markus Wolkenhauer; Marc Schneider; Claus-Michael Lehr
Journal:  Pharm Res       Date:  2014-05-23       Impact factor: 4.200

7.  A Physiologically Based Pharmacokinetic Model for Optimally Profiling Lamotrigine Disposition and Drug-Drug Interactions.

Authors:  Todd M Conner; Ronald C Reed; Tao Zhang
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2019-06       Impact factor: 2.441

Review 8.  Lipid-associated oral delivery: Mechanisms and analysis of oral absorption enhancement.

Authors:  Oljora Rezhdo; Lauren Speciner; Rebecca Carrier
Journal:  J Control Release       Date:  2016-08-09       Impact factor: 9.776

9.  Fabrication and development of pectin microsphere of metformin hydrochloride.

Authors:  Pritam Banerjee; Jyotirmoy Deb; Amitava Roy; Amitava Ghosh; Prithviraj Chakraborty
Journal:  ISRN Pharm       Date:  2012-08-01

Review 10.  Population-based mechanistic prediction of oral drug absorption.

Authors:  Masoud Jamei; David Turner; Jiansong Yang; Sibylle Neuhoff; Sebastian Polak; Amin Rostami-Hodjegan; Geoffrey Tucker
Journal:  AAPS J       Date:  2009-04-21       Impact factor: 4.009

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.