• How Real Time Titer Measurement And Monitoring Is Advancing Bioproduction Across Multiple Applications

  • Feb 29 2024
  • Length: 41 mins
  • Podcast

How Real Time Titer Measurement And Monitoring Is Advancing Bioproduction Across Multiple Applications

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  • Summary

  • This panel discussion was originally published in the eBook “ Monoclonal Antibody Manufacturing Trends, Challenges, and Analytical Solutions to Eliminate Bioprocessing Bottlenecks” You can download all the articles in the series, by downloading the eBook. Panel discussion members: Carrie Mason - Associate Director, R&D at Lonza Biologics Laura Madia - Independent Industry Consultant Alan Opper – Director of HaLCon Sales at RedShiftBio David Sloan, PhD – Senior Vice President, Life Sciences at RedShiftBio Brandy Sargent, Editor in-chief, Cell Culture Dish and Downstream Column (Moderator) In this panel discussion, we talked with industry experts about antibody process development and manufacturing. Specifically focusing on current antibody titer expectations, analytical challenges and how real time titer measurement is a game changer for bioproduction moving forward. Where is the industry at today with titer expectations and what are the best practices for measuring titer? Laura Madia With respect to expectations regarding titer over the years, what we’ve seen is a need for increased titer within the upstream development of a drug. As an industry, we have moved from the 80s where titers were closer to .2 to .5 grams per liter to the early 2000s where concentrations of titer production rose to 3 to 5 grams per liter. What we see today is a continued increase in titer concentrations, which creates a challenge to make sure that you have technologies that can accurately measure titer concentration without introducing any errors. The other thing that we have seen within the industry is the need for more data to not only understand what is happening in the tank, but also to be able to make decisions about the product as the process is running or shortly after. Lastly, it is important to consider people and resources. It has been exacerbated by COVID, but it is difficult to find people to work within the industry and there are fewer people within a production suite. This has helped to drive the need for online and remote monitoring and automation to make it easier to get the necessary measurements. David Sloan To follow up on the lack of workers, one of the things that we constantly hear from the customers we are working with is that training employees can be a real challenge and a very time-intensive process. Technologies that are easier to use and require less expertise help get people up and running and minimize errors amongst new users of a technology. Laura Madia As for the current best practices for measuring titer, HPLC is the gold standard. But HPLC presents some challenges including training and HPLC requires a highly skilled person to get accurate results. There is a need for something that is simple and easy to use when it comes to measuring titer. You will still need HPLC results for approval and decisions at the end, but to be able to monitor titer throughout the process is important. What are the challenges associated with the way that titer is measured today and what can we do as an industry to improve? Laura Madia One of the challenges is that most of the assays available today are batch processes, so that lends itself to providing a retrospective look and means that most people don’t run samples throughout the process. This is because most people save these tests until the end when they can run a batch and make it more cost effective, and it is typically a long time to result so running it during the process isn’t helpful. Systems today are more for batch process and are not set up for at-line measurement, unless you are lucky enough to be able to have an HPLC that’s dedicated to that tank. Another challenge is speed and accuracy. Many of the techniques that are offline today are longer assays because they’re running as a batch. You must wait for the entire batch, which is a long time to first result.
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