Streamlining LC-MS Characterization of Pharmaceutical Polymers by Fourier-Transform-Based Deconvolution and Macromolecular Mass Defect Analysis

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