Innovative solution for higher-order structure assessment of biopharmaceuticals combining spectroscopy with machine learning and statistical method.

The market for new modalities of biopharmaceutical, such as therapeutic antibodies and nucleic acid drugs, has been dramatically expanding over the past decade. Biopharmaceuticals exhibit their efficacy by forming higher-order structures (HOS) driven by covalent and non-covalent bond formation. So, the HOS can be affected by various stimuli during the manufacturing process, resulting in the formation of various structural impurities derived from native substances and reduced drug efficacy. While biopharmaceuticals are a successful modality, it is crucial to understand and manage the unique nature of HOS.
Spectroscopy, including circular dichroism (CD) is a powerful tool for the rapid, non-destructive acquisition of biopharmaceuticals HOS knowledge.
Innovative HOS evaluation of each process from R&D to production is possible by combining spectral data with machine learning and statistical methods. Furthermore, the importance of orthogonal assessment, which combines multiple spectroscopic methods with different principles, is increasing.
In this session, we report an innovative solution for the structural analysis of therapeutic antibodies using a new structure estimation algorithm, a spectral similarity evaluation methodology, and using multiple spectroscopic instruments.