Use of Monte Carlo simulations in the assessment of calibration strategies – Part III: an evaluation of linear calibration

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Abstract

Background: The acceptance criteria for chromatographic bioassays are generally based upon the specifications found in the US FDA Guidance for Industry document, whereas regression analysis is a statistical process and, thus, most suited to large data populations, rather than the small populations used in assay calibration. Data that form part of the statistical population are often excluded in order that calibrations meet these acceptance criteria. Results/discussion: Monte Carlo simulations of various linear regression calibration strategies, which take into account guidance acceptance criteria, have been used to quantify calibration errors. Conclusion: It is concluded that 1/x2 weighting generally produces results that meet both theoretical and regulatory requirements, and that use of single, rather than duplicate, calibrators can result in misleading statistics at the LLOQ.

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