Assessment of the Higher-Order Structure of Formulated Monoclonal Antibody Therapeutics by 2D Methyl Correlated NMR and Principal Component Analysis

Abstract

Characterization of the higher-order structure (HOS) of protein therapeutics, and in particular of monoclonal antibodies, by 2D ¹H-¹³C methyl correlated NMR has been demonstrated as precise and robust. Such characterization can be greatly enhanced when collections of spectra are analyzed using multivariate approaches such as principal component analysis (PCA), allowing for the detection and identification of small structural differences in drug substance that may otherwise fall below the limit of detection of conventional spectral analysis. A major limitation to this approach is the presence of aliphatic signals from formulation or excipient components, which result in spectral interference with the protein signal of interest; however, the recently described Selective Excipient Reduction and Removal (SIERRA) filter greatly reduces this issue. Here we will outline how basic 2D ¹H-¹³C methyl−correlated NMR may be combined with the SIERRA approach to collect ‘clean’ NMR spectra of formulated monoclonal antibody therapeutics (i.e., drug substance spectra free of interfering component signals), and how series of such spectra may be used for HOS characterization by direct PCA of the series spectral matrix. © 2020 U.S. Government.

Basic Protocol 1: NMR data acquisition

Basic Protocol 2: Full spectral matrix data processing and analysis

Support Protocol: Data visualization and cluster analysis