Predictive Methodology for Selecting the “Fit-for-Purpose” LC-HRMS Method for Quality Assessment in Peptide Synthesis

Abstract

Peptides are essential in pharmaceuticals and function as therapeutic agents for a wide range of conditions. The chemical synthesis process of peptides often leaves impurities, such as inorganic salts and residual reagents, which can interfere with the analysis and contaminate the mass spectrometer’s source in in-process quality control (IPQC). Moreover, process monitoring using short liquid chromatography-high-resolution mass spectrometry (LC-HRMS) runtimes presents challenges due to the presence of multiple organic impurities. To address this, four distinct LC-HRMS templates were developed to accommodate a diverse range of peptides. A principal component analysis (PCA)-based methodology was then developed and validated to select the appropriate LC-HRMS method based on the peptides’ physicochemical properties, including sequence length, hydrophobicity, isoelectric point, molecular weight, and clog P. The PCA methodology efficiently classified peptides into distinct quadrants, guiding the selection of the appropriate short LC-HRMS method without the need for trial-and-error LC-HRMS method development. With a success rate exceeding 90%, the methodology accurately predicted the appropriate LC-HRMS method for the peptides. This systematic approach streamlines method selection and ensures the precise elution of peptides. Furthermore, by directing the initial LC flow to waste, the short methods minimize the risk of mass source contamination from inorganic impurities. This developed methodology is suitable for peptides with sequence lengths ranging from tetrapeptides to octapeptides, providing a robust tool for peptide analysis in IPQC workflows.