Considering a journey from biopharmaceutical characterization to multi-attribute monitoring?
The biopharmaceutical industry and market has grown tremendously in the past decades and, according to one estimate, biologics now account for about 40% of all prescription drug spending in the U.S.1 In 2016, 8 of top 10 best selling drugs were biologics, and five of these were monoclonal antibody drugs.2
Given this tremendous growth potential, biotherapeutic developers are facing increased competitive pressure from both innovator and biosimilar producers, and are therefore looking for innovative tools and technologies that can increase product and process understanding, enhance product quality, fuel productivity gains and ultimately accelerate their product development and commercialization efforts.
These goals align well with the Quality by Design (QbD) initiative supported by the U.S. Food and Drug Administration (FDA), which aims to enhance the quality of these drugs, thereby minimizing adverse events and/or product recalls.2 QbD by definition is: a systematic approach to development that begins with pre-defined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management.”
QbD requires companies develop a thorough understanding of the product and process in the early stage of manufacturing development, and the deployment of tools to monitor critical quality attributes (CQAs) throughout the production process so as to ensure high quality production throughout the pre- and post-commercialization processes.
The implementation of QbD programs for the increasing number of biotherapeutics/biosimilars in development represents a significant challenge for the biopharmaceutical industry. These large, highly complex molecular modalities often require sophisticated analytical tools to be characterized, and sensitive and robust monitoring tools to ensure they remain unchanged throughout development and production.
BLA review shows mass spectrometry is essential to biotherapeutic characterization
Over the last decade, mass spectrometry (MS) has emerged as the most indispensable technology for protein and nucleic acid based therapeutics characterization. In a recent review article,4 authors investigated the use of MS in biotherapeutics characterization – looking at BLAs that were approved by U.S. FDA between 2000 and 2015. 79 out of 80 BLAs electrically submitted used MS for product and attribute characterization with growing application diversity.
The improvements in both capabilities and robustness of LC-MS technology under GxP compliant-ready informatics for biopharmaceutical analysis has prepared the industry to expand the role of MS technologies beyond product characterization toward monitoring product and process quality attributes in upstream and downstream development, manufacturing, and for QC lot release testing as well.
Multi-attribute monitoring using MS is gaining currency
In recent years, the idea of multi-attribute monitoring (MAM) has gained considerable currency within the biopharmaceutical industry. Taking advantage of the sensitivity and selectivity MS offers compared to traditional optical detection, LC-MS based analytical approaches can monitor and quantify multiple product and/or process attributes within a single analysis.
Effective attribute monitoring typically requires:
Prior knowledge of the product achieved through extensive characjterization work
A defined set of product and/or process attributes for targeted monitoring
Robust analytical tools that are scalable, easy-to-use and provide consistent testing performance
Compliant-ready informatics to ensure data integrity and provide seamless method transfer to regulated environments
At Waters we have developed and support two separate approaches to LC-MS based multi-attribute-monitoring (MAM) of monoclonal antibodies (mAbs): One focused on mAb subunit-based analysis, and the other on peptide mapping based analysis.
Our next post in this series will discuss the advancement and challenges with each of these workflows.
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