Literature DB >> 8058615

An assessment of the 4-6-20 rule for acceptance of analytical runs in bioavailability, bioequivalence, and pharmacokinetic studies.

R O Kringle1.   

Abstract

A recent conference report described a decision rule, hereafter referred to as the 4-6-20 rule, for acceptance/rejection of analytical runs in bioavailability, bioequivalence, and pharmacokinetic studies. This procedure requires that quality control specimens at three concentrations (low, medium, and high) be assayed in duplicate in each run. For run acceptance, at least four of the six assay values must be within +/- 20% of their respective nominal concentrations, and at least one of the two values at each concentration must be within these limits. An inherent flaw in this decision rule is that the risk of rejecting runs, when the assay performance has in fact not deteriorated, varies for each assay and is neither known nor controlled. In this paper simulation methods are used to evaluate the operating characteristics of the 4-6-20 rule in comparison to those of classical statistical quality control procedures.

Mesh:

Year:  1994        PMID: 8058615     DOI: 10.1023/a:1018922701174

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


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2.  Statistical simulation study of new proposed uniformity requirement for bioequivalency studies.

Authors:  J D Haynes
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Authors:  V P Shah; K K Midha; J W Findlay; H M Hill; J D Hulse; I J McGilveray; G McKay; K J Miller; R N Patnaik; M L Powell; A Tonelli; C T Viswanathan; A Yacobi
Journal:  Pharm Res       Date:  2000-12       Impact factor: 4.200

2.  A total error approach for the validation of quantitative analytical methods.

Authors:  David Hoffman; Robert Kringle
Journal:  Pharm Res       Date:  2007-03-21       Impact factor: 4.200

3.  Statistical considerations for assessment of bioanalytical incurred sample reproducibility.

Authors:  David Hoffman
Journal:  AAPS J       Date:  2009-08-08       Impact factor: 4.009

4.  Measuring precision in bioassays: Rethinking assay validation.

Authors:  Michael P Fay; Michael C Sachs; Kazutoyo Miura
Journal:  Stat Med       Date:  2017-10-19       Impact factor: 2.373

  4 in total

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