Framework for Multivariate Selectivity Analysis, Part II: Experimental Applications

Abstract

In Part I of this paper, a framework for multivariate selectivity was introduced that is both calculable from first principles and experimentally tractable. In this part, we employ the proposed selectivity framework for analyzing both in vitro and in vivo near-infrared experimental data. Two in vitro data sets are used to compare different methods for estimating selectivity and to demonstrate the benefits obtained from validation data with expanded interferant concentration ranges. The in vitro data also demonstrate that the experimentally estimated selectivities provide insights into the properties of the calibration models that are difficult or impossible to infer by other means. The merits of the proposed selectivity function are further demonstrated using a complex in vivo application: the noninvasive measurement of ethanol in humans. Results indicate that in vivo calibration model sensitivity, selectivity, and concentration correlations can be systematically interrogated using the proposed selectivity framework and judicious use of experimental measurements. These analyses not only provide selectivity and sensitivity information, but also the variance components of the total MSEP, which is invaluable information for both method development and analytical method characterization.