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Technical decision making with higher order structure data: higher order structure characterization during protein

Yijia Jiang¹, Cynthia Li, Jenny Li

¹Attribute Sciences, Amgen Inc., Thousand Oaks, California, 91320.

Journal of Pharmaceutical Sciences

|February 27, 2015

Summary

Selecting optimal protein therapeutics involves evaluating higher-order structure (HOS) characteristics. Early HOS analysis aids in choosing candidates with superior manufacturability, purity, and stability, avoiding future development challenges.

Keywords:

CD DLS DSC SEC biophysical characterization candidate selection higher order structure protein stability

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Area of Science:

Biopharmaceutical development
Protein characterization
Drug discovery

Background:

Protein therapeutics possess complex higher-order structures (HOS), post-translational modifications, and heterogeneity, distinguishing them from small molecules.
Early-stage drug development involves producing multiple molecular candidates for the same target, necessitating comparative analysis.

Purpose of the Study:

To present a case study on utilizing higher-order structure (HOS) characterization methods for selecting optimal protein therapeutic candidates.
To demonstrate the role of HOS data in identifying and mitigating potential development challenges.

Main Methods:

Application of selected higher-order structure (HOS) characterization techniques.
Comparative analysis of multiple protein molecular candidates based on HOS profiles.

Main Results:

Higher-order structure (HOS) data proved instrumental in ranking protein candidates.
HOS characterization facilitated the identification of candidates with favorable manufacturability, purity, and stability.

Conclusions:

Early assessment of higher-order structure (HOS) is crucial for selecting the most promising protein therapeutic candidates.
Integrating HOS data into candidate selection can proactively address potential manufacturing and stability issues, optimizing the development pathway.