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Pharmaceutical Applications of a Multi-Stage Group Testing Method

  • Brian Bond
  • Valeri Fedorov
  • Matthew Jones
  • Anatoly Zhigljavsky
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 51)

Abstract

An important problem in pharmaceutical research is whether individual testing of components should be made, or alternatively, if the components should be tested in groups. It is important that the experiment is economically viable since, for multi-stage procedures, the cost of additional stages must be taken into consideration along with the cost of testing the mixtures of components. Optimum group sizes are calculated for two-stage and three-stage members of Li’s family of algorithms and for row-and-column procedures, along with the minimum number of tests required to determine all of the active components. Finally, comparisons are made between the costs of the one-, two- and three-stage procedures using two different cost functions for the cost of testing mixtures of components.

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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Brian Bond
    • 1
  • Valeri Fedorov
    • 1
  • Matthew Jones
    • 2
  • Anatoly Zhigljavsky
    • 2
  1. 1.Statistical Sciences DepartmentSmithkline Beecham PharmaceuticalsUK
  2. 2.School of MathematicsCardiff UniversityUK

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