Literature DB >> 16447175

Process simulation in the pharmaceutical industry: a review of some basic physical models.

D M Kremer1, B C Hancock.   

Abstract

This study reviews process modeling efforts which have been developed to elucidate the fundamental physical process underlying the manufacture and delivery of pharmaceutical dosage forms. Within the pharmaceutical industry, process models have been applied to a diverse array of physical processes at length and time scales that vary by orders of magnitude. As such, both large-scale continuum and particle-scale discrete approaches will be discussed in this study. Challenges associated with the practical application of process models within the pharmaceutical industry will be discussed, and opportunities for future research will be identified. Copyright 2006 Wiley-Liss, Inc. and the American Pharmacists Association.

Mesh:

Year:  2006        PMID: 16447175     DOI: 10.1002/jps.20583

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


  4 in total

1.  Rapid Reconstitution Packages (RRPs) implemented by integration of computational fluid dynamics (CFD) and 3D printed microfluidics.

Authors:  Albert Chi; Sebastian Curi; Kevin Clayton; David Luciano; Kameron Klauber; Alfredo Alexander-Katz; Sebastian D'hers; Noel M Elman
Journal:  Drug Deliv Transl Res       Date:  2014-08       Impact factor: 4.617

2.  Scale-Up Strategy in Quality by Design Approach for Pharmaceutical Blending Process with Discrete Element Method Simulation.

Authors:  Su Bin Yeom; Du Hyung Choi
Journal:  Pharmaceutics       Date:  2019-06-06       Impact factor: 6.321

Review 3.  Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry.

Authors:  Su Bin Yeom; Eun-Sol Ha; Min-Soo Kim; Seong Hoon Jeong; Sung-Joo Hwang; Du Hyung Choi
Journal:  Pharmaceutics       Date:  2019-08-15       Impact factor: 6.321

Review 4.  Direct Compaction Drug Product Process Modeling.

Authors:  Alexander Russell; John Strong; Sean Garner; William Ketterhagen; Michelle Long; Maxx Capece
Journal:  AAPS PharmSciTech       Date:  2022-01-31       Impact factor: 3.246

  4 in total

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