Reversed Headspace Analysis for Characterization, Identification, and Analysis of Solid and Liquid Matrices: Part I.

Abstract

This paper offers a methodology of an experimentally simple reversed headspace (RHS) analysis for measuring of matrix effects and their use for identification and characterization of condensed matrices such as pharmaceuticals, polymers, chromatographic packing, etc. applicable for both quality control monitoring and research and development investigation. In RHS methods, the matrix is spiked and equilibrated with a mixture of volatile chemicals containing various functional groups (molecular sensor array or MSA mixture). Headspace chromatograms of the same spikes of a sample and an empty vial are compared. Examination of basic headspace theory shows that matrix specific constants (M), rather than partition coefficients (K), can be calculated from the headspace chromatograms and M=(K-1)xbeta, where beta is a degree of matrix volume change during equilibration. Matrix specific constants can be plotted against any property of chemicals (polarity, dielectric constant, solubility parameter, vapor pressure, etc.) or just against a set of consecutive numbers, each representing a chemical in MSA. This plot is, in a sense, a molecular affinity spectrum (MAS) specific for a given matrix at a given temperature and is independent of an instrument. Changes in MAS that correspond to chemicals with a particular functional group give an insight to the type of differences between matrices and may quantitatively define them.