Total Analytical Error in Validation of Analytical Procedures of Pharmaceuticals

Published on: 
Pharmaceutical Technology, Pharmaceutical Technology, May 2023, Volume 47, Issue 5
Pages: 32–41, 45

This paper demonstrates how assay data sets of a formulated liquid product, drug substance, and an impurity, obtained from combined accuracy-precision studies, are evaluated to calculate statistical intervals (prediction and tolerance intervals) and to graphically display the total analytical error (TAE) to account for the systematic and random errors.

Abstract

This paper demonstrates how assay data sets of a formulated liquid product, drug substance, and an impurity, obtained from combined accuracy-precision studies, are evaluated to calculate statistical intervals (prediction and tolerance intervals) and to graphically display the total analytical error (TAE) to account for the systematic and random errors. Inclusion of either the statistical intervals or the TAE within the allowed accuracy limits is an indication of a successful validation of the accuracy and precision method characteristics. This paper subsequently evaluates the capability of common procedures of pharmaceutical analysis to accommodate acceptable TAE and statistical intervals. While considering typical values of standard deviations (0.5–2.5% relative standard deviation) of chromatographic tests and typical specifications (±2, ±5, or ±10%) of pharmaceuticals, it is shown that a substantial portion of specification tolerance is taken up by either the statistical intervals or by the TAE, particularly in cases of narrow specifications and imprecise procedures.

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Peer-Reviewed

Submitted: February 20, 2023

Accepted: March 9, 2023

About the author

Raphael Bar, is a Consultant at BR Consulting, Israel, rbar@netvision.net.il

Article details

Pharmaceutical Technology
Vol. 47, No. 5
May 2023
Pages: 32–41, 45

Citation

When referring to this article, please cite it as Bar, R. Total Analytical Error in Validation of Analytical Procedures of Pharmaceuticals. Pharmaceutical Technology 2023 47 (5).