The history of medical science is full of exciting technological advances. From antibiotics deemed “wonder drugs” in 1929 to the discovery of DNA’s double helix by James Watson and Francis Crick in 1953, we have seen huge scientific advances as an outcome of and response to massive global health challenges. Is the Multi-Attribute Method (MAM) next in line to be one of the greatest technical developments of the healthcare industry in this decade — reducing the frequency and severity of immense manufacturing challenges of the biopharmaceutical industry?
The biopharmaceutical market has grown rapidly over the past few decades due to increased demand and the promise of biotherapeutics treating life-threatening diseases. More and more companies are becoming active in developing both innovator products and biosimilars. But, unlike small molecules, protein biotherapeutics are quite complex, containing molecular heterogeneity caused by post-translational modifications, higher-order structural changes, and aggregation. All these characteristics may contribute to the safety and efficacy profile of the biopharmaceutical and therefore must be characterized and monitored from drug discovery through quality control in manufacturing.
Using analytics to alleviate biopharmaceutical manufacturing bottlenecks
Over the past several decades, the structural complexity challenges of characterizing biotherapeutics have been largely addressed with a variety of analytical methods that must often be used orthogonally. However, the streamling of analytics is becoming necessary because of the increased need for deeper product and process understanding driven by quality-by-design principles (QbD) and heightened time and cost pressures of biopharmaceutical manufacturing due to the sheer number of products coming through the development pipeline. For further reading on this topic, please visit the new Thermo Fisher Scientific MAM learning page.
The MAM movement is a perfect example of where opportunities in science, driven by technological advances, meet industry necessity. Inline with QbD principles, the Multi-Attribute Method was first developed by analytical scientists at Amgen to allow for the simultaneous monitoring of multiple product quality attributes. MAM is based on LC-MS peptide mapping techniques, typically using high-resolution mass spectrometry to acquire high resolution and high accuracy mass data. As the technique has progressed over the years, the focus has turned to automation and software development to allow for automated identification and quantitative analysis of each molecular attribute. For more information on MAM software, view “Performing the biopharmaceutical multi-attribute method (MAM).” With automation and software developments, a true benefit of MAM can be realized by building a comprehensive molecular attribute database linked to process conditions which can then be used to increase product and process knowledge throughout the development pipeline. With this increased product and process knowledge, MAM can reduce the amount of time taken to develop a product, reduce the time needed to manufacture and release a product by adding efficient process controls, and reduce the time needed to investigate a process issue. MAM can help to solve major manufacturing challenges plaguing the biopharmaceutical industry today as they strive to develop more biotherapeutics on a faster timeline.
Hear more on MAM from NIBRT
Will MAM lead to an impactful change in biopharmaceutical drug development? This is a space to watch over the next 10 years as the biopharmaceutical industry races to change how the world develops new medicines. Do you want to hear more from an industry perspective? Listen to Sara Carrillo from NIBRT speaking about “Understanding Product Quality Attributes of Biotherapeutics using Thermo Scientific HR Multi-Attribute Method (HR MAM) Workflow” in the upcoming webinar on September 16, 2020.
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