Streamlining\nLC-MS Characterization of Pharmaceutical\nPolymers by Fourier-Transform-Based Deconvolution and Macromolecular\nMass Defect Analysis

Polymer conjugation has risen in importance over the\npast three\ndecades as a means of increasing the <i>in vivo</i> half-life\nof biotherapeutics, with benefits including better stability, greater\ndrug efficacy, and lower toxicity. However, the intrinsic variability\nof polymer synthesis results in products with broad distributions\nin chain length and branching structure, complicating quality control\nfor successful functionalization and downstream conjugation. Frequently,\na combination of several analytical techniques is required for comprehensive\ncharacterization. While liquid chromatography–mass spectrometry\n(LC-MS) is a powerful platform that can provide detailed molecular\nfeatures of polymers, the mass spectra are inherently challenging\nto interpret due to high mass polydispersity and overlapping charge\ndistributions. Here, by leveraging Fourier transform-based deconvolution\nand macromolecular mass defect analysis, we demonstrate a new way\nto streamline pharmaceutical polymer analysis, shedding light on polymer\nsize, composition, branching, and end-group functionalization with\nthe capability for reaction monitoring.