Literature DB >> 1790180

Use of experimental design in the pharmaceutical industry.

N Kettaneh-Wold1.   

Abstract

Statistical modelling and experimental design (SMED) are essential tools for the development and understanding of complicated products and processes. SMED allows efficient experimentation in which all or a large subset of factors are together varied over a set of experiments, in contrast to the traditional approach of varying only one at a time. An overview of the SMED methodology and the generalization of statistical design to multivariate design is presented. The following examples illustrating the use of these methods are discussed: (1) use of factorial designs to improve drug solubility; (2) testing the robustness of an analytical method; and (3) use of multivariate design to select the solvent in analytical method development.

Mesh:

Year:  1991        PMID: 1790180     DOI: 10.1016/0731-7085(91)80185-c

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  3 in total

1.  Multivariate data analysis of factors affecting the in vitro dissolution rate and the apparent solubility for a model basic drug substance in aqueous media.

Authors:  Anita Maria Persson; Curt Pettersson; Josefin Rosén
Journal:  Pharm Res       Date:  2010-03-27       Impact factor: 4.200

2.  Hydrogel design of experiments methodology to optimize hydrogel for iPSC-NPC culture.

Authors:  Jonathan Lam; S Thomas Carmichael; William E Lowry; Tatiana Segura
Journal:  Adv Healthc Mater       Date:  2014-11-05       Impact factor: 9.933

3.  Quality by Design (QbD)-Based Numerical and Graphical Optimization Technique for the Development of Osmotic Pump Controlled-Release Metoclopramide HCl Tablets.

Authors:  Sadaf Farooqi; Rabia Ismail Yousuf; Muhammad Harris Shoaib; Kamran Ahmed; Sabah Ansar; Tazeen Husain
Journal:  Drug Des Devel Ther       Date:  2020-11-26       Impact factor: 4.162

  3 in total

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