Pharmaceutical Research

, Volume 24, Issue 6, pp 1157–1164

A Total Error Approach for the Validation of Quantitative Analytical Methods

Authors

    • Preclinical and Research Biostatistics, sanofi-aventis
  • Robert Kringle
    • Preclinical and Research Biostatistics, sanofi-aventis
Research Paper

DOI: 10.1007/s11095-007-9242-3

Cite this article as:
Hoffman, D. & Kringle, R. Pharm Res (2007) 24: 1157. doi:10.1007/s11095-007-9242-3

Abstract

Purpose

Typical acceptance criteria for analytical methods are not chosen with regard to the concept of method suitability and are commonly based on ad-hoc rules. Such approaches yield unknown and uncontrolled risks of accepting unsuitable analytical methods and rejecting suitable analytical methods. This paper proposes a formal statistical framework for the validation of analytical methods, which incorporates the use of total error and controls the risks of incorrect decision-making.

Materials and Methods

A total error approach for method validation based on the use of two-sided β-content tolerance intervals is proposed. The performance of the proposed approach is compared to the performance of current ad-hoc approaches via simulation techniques.

Results

The current ad-hoc approaches for method validation fail to control the risk of incorrectly accepting unsuitable analytical methods. The proposed total error approach controls the risk of incorrectly accepting unsuitable analytical methods and provides adequate power to accept truly suitable methods.

Conclusion

Current ad-hoc approaches to method validation are inconsistent with ensuring method suitability. A total error approach based on the use of two-sided β-content tolerance intervals was developed. The total error approach offers a formal statistical framework for assessing analytical method performance. The approach is consistent with the concept of method suitability and controls the risk of incorrectly accepting unsuitable analytical methods.

Key words

analysis of variancebioanalytical assaymethod validationtolerance intervaltotal error

Copyright information

© Springer Science+Business Media, LLC 2007