title: Statistical methods for assessing long-term analyte stability in biological matrices.
abstract: The objective of a long-term stability experiment is to confirm analyte stability in a given biological matrix, encompassing the duration of time from sample collection to sample analysis for a clinical or preclinical study. While long-term analyte stability has been identified as a key component of bioanalytical method validation, current regulatory guidance provides no specific recommendations regarding the design and analysis of such experiments. This paper reviews and evaluates various experimental designs, data analysis methods, and acceptance criteria for the assessment of long-term analyte stability. Statistical equivalence tests based on linear regression techniques are advocated. Both a nested errors and bivariate mixed model regression approach are suitable for application to long-term stability assessment, and control the risk of falsely concluding stability.
authors.affiliation: Preclinical and Research Biostatistics, sanofi-aventis, Bridgewater, NJ, USA. david.hoffman@sanofi-aventis.com
authors.forename: David
authors.initials: D
authors.lastname: Hoffman
authors.forename: Robert
authors.initials: R
authors.lastname: Kringle
authors.forename: Julia
authors.initials: J
authors.lastname: Singer
authors.forename: Stuart
authors.initials: S
authors.lastname: McDougall
mesh_terms: D000818:Animals; D001774:Blood Chemical Analysis; D005069:Evaluation Studies as Topic; D017408:Guidelines as Topic; D006801:Humans; D012107:Research Design; D013223:Statistics as Topic / Q000379:methods*