Systematic Approach to Optimization and Comparability of Biopharmaceutical Glycosylation Throughout the Drug Life Cycle

Fernandes, Daryl L.

doi:10.1002/9783527653096.ch17

Cited by 2 publications

(2 citation statements)

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“…These effects have been found in drugs such as Cetuximab (a monoclonal antibody (mAb) for treatment of metastatic colorectal cancer), Herceptin (a mAb for treatment of breast cancer) and erythropoietin (EPO—a drug for increasing red blood cells in patients with renal failure and cancer patients undergoing chemotherapy). Given this, there are now increasing pressures from regulatory authorities for drug manufacturers to measure, optimize and control their drug’s glycosylation [ 6 ]. This task is very challenging given the structural complexity of biopharmaceutical glycosylation and achieving it has required adoption of a new approach to drug design—namely Quality by Design (QbD).…”

Section: Introductionmentioning

confidence: 99%

“…Studies of the QbD approach by the CMC Biotech Working Group (a consortium of experts from leading biopharma organizations including Genentech, Amgen, Eli Lilly, and Pfizer), indicate that definition of the QbD Design Space may require analysis of tens of thousands of drug samples [ 8 ]. Successful adoption of QbD for development of glycoprotein therapeutics requires glycoprofiling systems that can cope with this very high level of sample throughput—in effect it will need to be built on a glycomics framework [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

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High-Throughput Analysis and Automation for Glycomics Studies

et al. 2014

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This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics—for example in Genome Wide Association Studies—to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%