Estimating analytical variability in two-dimensional data

Abstract

Throughout the course of drug development there are many instances in which a variability assessment within a set of analytical data is required, which may be challenging for techniques that produce two-dimensional data. This note describes an interval-based approach to variability assessment and demonstrates its applicability for analysis of near-UV circular dichroism (CD) spectra. The approach is generalizable and could be applied to two-dimensional data from other analytical techniques as well.