The market for monoclonal antibodies (mAbs) is rapidly expanding, with a current worth of over $330 billion and expected to double by 2030. However, developers face challenges in measuring and maintaining critical quality attributes (CQAs) of mAbs. One key CQA is aggregation, which can affect product quality and patient safety.
Traditionally, aggregation screening occurs late in the process development, leading to risks of eliminating stable clones early on. Recent technological advances now allow for early detection of aggregation, saving time and costs in the development process. Plate-based assays enable developers to measure aggregation in multiple samples simultaneously, providing comparable results to existing methods such as HPLC-SEC and DLS.
The plate-based technology offers efficient aggregation data generation and high reproducibility, allowing for early identification of stable molecules. Automating these assays in the future may further enhance their utility in mAb development. Managing aggregation earlier in the process benefits patients by potentially shortening the lengthy development timelines for mAbs.
Dr. Elisa Nent, a global product manager at Beckman Coulter Life Sciences, with expertise in cellular biology, emphasizes the importance of managing CQAs to bring lifesaving therapies to patients sooner. By addressing aggregation issues early in the development process, developers can streamline their efforts and accelerate the availability of new therapeutic options for patients in need.
References:
– Grand View Research. Biologics Market Size & Trends.
– Pang, KT, Yang, YS, et al: Understanding and Controlling the Molecular Mechanisms of Protein Aggregation in mAb Therapeutics.
– Swanson, M, Rios, S, et al: Immunogenicity Risk Assessment of Spontaneously Occurring Therapeutic Monoclonal Antibody Aggregates.
– Beckman Coulter Life Sciences. Performance of the Valita Aggregation Pure assay vs HPLC-SEC.
– Morris ZS, Wooding S, Grant, J: The answer is 17 years, what is the question: understanding time lags in translational research.
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