Partnership Delivers on Efficiency with Downstream Manufacturing

A new collaboration to develop integrated analytical solutions to provide robust data for downstream biomanufacturing, has expanded an existing agreement between Waters and Sartorius that initially began with upstream bioprocessing analytics.

"From the beginning of our collaboration with Sartorius, we've strived to give bioprocess engineers faster and more direct access to critical quality attribute information about their drug products in the name of improving production yields and getting drugs to patients faster," said Jon Pratt, Senior Vice President, Waters Division. "Based on the positive response of customers to our collaborative efforts with upstream bioprocessing analytics, we see tremendous benefit to combining the PATROL Process Analysis System (UPLC) and the Sartorius BioSMB (multi-column platform) to bring timely point-of-decision analytics to downstream biomanufacturing for monoclonal antibodies, recombinant proteins, vaccines and AAV gene therapies."

"Now that intensified, continuous manufacturing of biologics is becoming a reality, there is a greater need for real-time analytical measurement," said René Fáber, Head of Bioprocess Solutions Division, Sartorius. "The value of combining technologies from Sartorius and Waters lies in bringing fundamentally important analytics to the point where it is needed and giving bioprocess engineers a more complete understanding of their downstream manufacturing processing and its effects on drug product quality. We believe this can have significant impacts on drug production costs by helping to increase yields and reduce waste."

In-process sampling and the analysis of biological drugs sent to a central laboratory can take weeks before the results of necessary quality checks are in. The combined efforts from Waters and Sartorius have been to show how this process can be streamlined so that product quality tests for protein A, aggregation and charge variants occur closer to the process, with potentially significant reductions in production time.

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