Revolutionizing mAb Development: How Cutting-Edge Technology Enhances Monitoring of Critical Quality Attributes

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The monoclonal antibodies (mAbs) market is booming, worth over $330 billion and expected to exceed that by 2030. As researchers push forward, they face tough challenges, especially in tracking critical quality attributes (CQAs).

One major concern is aggregation. This happens when proteins clump together, causing them to lose their shape and function. Several factors influence this process, like the protein’s sequence and manufacturing conditions such as changes in pH, temperature, and mechanical stress.

Aggregates can hide important binding sites on mAbs, which can affect how well they work. They also pose risks to patient safety, possibly causing unwanted immune responses. Developers monitor aggregation levels closely to meet regulatory standards.

Typically, researchers start looking for aggregation in the later stages of development, sifting through hundreds of clones that are the best candidates. Unfortunately, they might overlook their most stable clones in this process. If the selected clones aren’t optimal, they’ll have to restart their search, wasting time and resources.

However, new technology allows for earlier detection of aggregation. By identifying problematic clones sooner, developers can find those that are likely to keep aggregation below 5%, speeding up the path to patients who need these therapies.

Early Aggregation Detection

Traditionally, mAb developers used methods like high-performance liquid chromatography (HPLC) and dynamic light scattering (DLS) to monitor aggregation. These methods are time-consuming and require trained personnel, often leading developers to outsource this work, which can delay timelines and reduce the number of clones evaluated.

New plate-based assays are changing the game. These allow developers to test aggregation in 96 samples at once, significantly increasing efficiency. The plates use a fluorescent molecule that attaches to protein aggregates, measuring changes in light rotation to determine aggregation levels.

With this technology, results for 96 samples can be ready in just 15 minutes. Unlike traditional methods that can take hours, this approach streamlines the process, making it much quicker.

Validating New Methods

In a side-by-side comparison, the new method performed similarly to HPLC. The results were consistent, showing low variations across tests. Both methods ranked aggregation levels effectively, helping scientists find their most stable clones quickly.

Starting the aggregation screening earlier with these plate-based technologies could save considerable time and resources. If a clone turns out to have high aggregation, it can be eliminated early, avoiding wasted effort.

Moreover, adding automation to these assays could further enhance accuracy and efficiency, minimizing human error in the testing process.

Focusing on controlling aggregation earlier not only speeds up development but also improves outcomes for patients. The average time for mAb development can stretch up to 17 years, and any advancement that shortens this timeline brings vital therapies to those in need faster.

About the author: Dr. Elisa Nent has over 11 years of experience in life sciences, holding a PhD and master’s in neuroscience. She is the global product manager for Cell Health at Beckman Coulter Life Sciences, where she supports customers in cell line development.

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