Abstract
Poloxamer 188 (P188) is an alternative surfactant to polysorbates in biologic formulations, stabilizing biotherapeutic drugs in solution. By mitigating the inherent risk of polysorbate 20/80 (PS 20/80) degradation by host cell proteins, P188 ensured product integrity. In cell culture, it is used to minimize bubble formation and reduce shear stress. However, P188's susceptibility to chemical degradation necessitates vigilant monitoring during production, formulation, and storage to ensure biotherapeutic quality and patient safety. The complex composition of P188 poses a significant analytical challenge for its characterization and quantification in the pharmaceutical industry. In this work, we demonstrate two liquid chromatography (LC) methods that can be coupled with either a mass spectrometer (MS) for characterization and measurement of intact P188 and its degradants or a charged aerosol detector (CAD) for quantitative analysis. First, a reversed-phase liquid chromatography (RP-LC) method was developed for the characterization of P188 raw material in solution. Second, a strong anion exchange liquid chromatography (SAX-LC) method was developed for the direct measurement of the poloxamer in biotherapeutic drug products. After online separation via the LC methods mentioned above, we utilize charge reduction mass spectrometry and two-dimensional ion density mapping visualization for rapid profiling, fingerprinting, and speciation of this polymer excipient. This approach offers a streamlined ion map for comprehensive identification of P188 species and their mass distribution in detail, including poloxamers, poly-(ethylene oxides), and poly-(propylene oxides). The graphical representation of the data in two dimensions facilitates the visualization of these characteristics, enabling a prompt diagnosis of the purity and stability of P188. Consequently, both drug substances and drug products formulated with P188 can be directly analyzed, preserving high-integrity sample information. Simplified workflow and computer-assisted data processing also help increase the throughput.