Validation of the use of ToF-SIMS for analysis of glycosaminoglycans

Abstract

Glycosaminoglycans (GAGs) have a range of biological roles and are of particular interest for their pharmaceutical efficacy and their potential as biomarkers or drug targets. Heparin, used globally as an anticoagulant and an antithrombotic, is predominantly derived from porcine sources but bovine and ovine sources are increasingly being considered to reduce the substantial risk of reliance on a single animal species. However, high sensitivity chemical discrimination of heparins from different species is a significant analytical challenge. In this study ToF-SIMS analysis of GAGs is investigated as a methodology to achieve specific chemical discrimination between GAGs of different types and heparins from different animal sources. The ToF-SIMS data acquisition is relatively fast (≈1 min per sample) and requires minimal sample amounts (75 pg of sample analysed). Multivariate analysis (MVA) models enabled high selectivity between GAG type and animal source of heparin, and for the high sensitivity detection of GAG-contaminants within porcine derived heparin. Contaminants are detected down to 0.001 wt%, with the exception of ovine derived heparin where differences could be detected to 0.01 wt%. Assessments of specificity, precision, robustness and quantification limits are conducted to validate the approach for heparin analysis.