Biologic therapeutics such as monoclonal antibodies and biosimilars are complex proteins that are susceptible to post-translational modifications (PTMs). These chemical modifications can affect the performance and activity of the biologic, potentially resulting in decreased potency and increased immunogenicity. Such modifications include glycosylation, deamidation, oxidation and disulfide bond shuffling. These PTMs can be signs of protein degradation, manufacturing issues or improper storage. Several of these modifications are well characterized, and methods exist for detecting them during biologic manufacture. However, disulfide shuffling is not particularly well characterized for biologics, and no methods exist to easily detect and quantify disulfide bond shuffling in biologics.
Normally the cysteines in a protein will pair with a predictable or “normal” partner residue either within a polypeptide chain or between two polypeptide chains when they form disulfide bonds. These normal disulfide bonds are important for final protein conformation and stability. Indeed, disulfide bonds are considered an important quality indicator for biologics.
In a recently published study, Coghlan and colleagues designed a semi-automated method for characterizing disulfide bond shuffling on two IgG1 biologics: rituximab (originator drug Rituxan® and biosimilar Acellbia®) and bevacizumab (originator Avastin® and biosimilar Avegra®).
Several pharmaceutical companies have biosimilar versions of therapeutic mAbs in development. Biosimilars can promise significant cost savings for patients, but the unavoidable differences
between the original and thencopycat biologic raise questions regarding product interchangeability. Both innovator mAbs and biosimilars are heterogeneous populations of variants characterized by differences in glycosylation,oxidation, deamidation, glycation, and aggregation state. Their heterogeneity could potentially affect target protein binding through the F´ab domain, receptor binding through the Fc domain, and protein aggregation.
As more biosimilar mAbs gain regulatory approval, having clear framework for a rapid characterization of innovator and biosimilar products to identify clinically relevant differences is important. A recent reference (1) applied a comprehensive mass spectrometry (MS)-based strategy using bottom-up, middle-down, and intact strategies. These data were then integrated with ion mobility mass spectrometry (IM-MS) and collision-induced unfolding (CIU) analyses, as well as data from select biophysical techniques and receptor binding assays to comprehensively evaluate biosimilarity between Remicade and Remsima.
The authors observed that the levels of oxidation, deamidation, and mutation of individual amino acids were remarkably similar. they found different levels of C-terminal truncation, soluble protein aggregates, and glycation that all likely have a limited clinical impact. Importantly, they identified more than 25 glycoforms for each product and observed glycoform population differences.
Overall the use of mass spectrometry-based analysis provides rapid and robust analytical information vital for biosimilar development. They demonstrated the utility of our multiple-attribute monitoring workflow using the model mAbs Remicade and Remsima and have provided a template for analysis of future mAb biosimilars.
In his address to the clinicians, researchers, and patients at the American Association for Cancer Research meeting in April, US Vice President Joe Biden, revealed that the goal of the #cancermoonshot initiative is to accomplish 10 years of cancer research in just five years, effectively doubling the pace of cancer research (1).
Treatments developed from cancer research have come a long way with dramatic differences in the experiences and prognoses for patients, just looking back over the last 25 years. How can we double the pace of cancer research? The #cancermoonshot will one, encourage data sharing among researchers, particularly data from clinical trials. Second, it seeks to increase collaboration across industry, academic and government scientists—each community being positioned to make unique contributions to the field. And third, the initiative looks to change the current grants award process that encourages scientists to keep data and results “quiet” until they can be published or protected legally as intellectual property.
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