Literature DB >> 21442525

Optimum design of experiments for enzyme inhibition kinetic models.

Barbara Bogacka1, Maciej Patan, Patrick J Johnson, Kuresh Youdim, Anthony C Atkinson.   

Abstract

We find closed-form expressions for the D-optimum designs for three- and four-parameter nonlinear models arising in kinetic models for enzyme inhibition. We calculate the efficiency of designs over a range of parameter values and make recommendations for design when the parameter values are not well known. In a three-parameter experimental example, a standard design has an efficiency of 18.2% of the D-optimum design. Experimental results from a standard design with 120 trials and a D-optimum design with 21 trials give parameter estimates that are in close agreement. The estimated standard errors of these parameter estimates confirm our theoretical results on efficiency and thus on the serious savings that can be made by the use of D-optimum designs.

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Year:  2011        PMID: 21442525     DOI: 10.1080/10543406.2010.489979

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  3 in total

1.  Standardized maximim D-optimal designs for enzyme kinetic inhibition models.

Authors:  Ping-Yang Chen; Ray-Bing Chen; Heng-Chin Tung; Weng Kee Wong
Journal:  Chemometr Intell Lab Syst       Date:  2017-09-06       Impact factor: 3.491

2.  Using Differential Evolution to Design Optimal Experiments.

Authors:  Zack Stokes; Abhyuday Mandal; Weng Kee Wong
Journal:  Chemometr Intell Lab Syst       Date:  2020-01-28       Impact factor: 3.491

3.  A design criterion for symmetric model discrimination based on flexible nominal sets.

Authors:  Radoslav Harman; Werner G Müller
Journal:  Biom J       Date:  2020-01-20       Impact factor: 1.715

  3 in total

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