Your process works perfectly at two-liter bench scale. Then you hit fifty liters and titer drops 20%. By two hundred liters, aggregation appears and charge variants shift. Your management team asks: "How long to fix this?" The honest answer? Three to twelve month, because you're flying blind.

In Part 2 of this Quality by Design Master Class, David Brühlmann reveals why scale-up chaos isn't inevitable. It's a solvable engineering problem. Drawing on experience leading bioprocess innovation at Merck and guiding biotech companies through CMC development, David delivers the process control framework that transforms reactive troubleshooting into predictive manufacturing.

The core truth: eighty percent of quality problems stem from twenty percent of your process variables. David shows how to identify Critical Process Parameters, implement intelligent control strategies, and leverage hybrid modeling that reduces experiments by 60-80%. With case studies from Genentech and Amgen, you'll gain the blueprint that turns QbD requirements into competitive advantage.

Part 1 taught you what to build and measure. Part 2 shows you how to control your process to consistently deliver commercial-scale quality.

Topics Discussed:

• The common pitfalls of scaling up manufacturing from bench to production, and why process control must go beyond end-product testing (02:10)
• Overview of the QbD framework: Quality Target Product Profile (QTPP), Critical Quality Attributes (CQAs), and the focus of this episode - Control Strategies for manufacturing (05:00)
• Identifying and monitoring Critical Process Parameters (CPPs) and their impact on quality, with real-world examples from Genentech’s monoclonal antibody platform (08:20)
• Structure of an effective manufacturing control strategy: Input, process, and output controls - including practical details on real-time monitoring and release testing (11:00)
• The role of hybrid modeling and machine learning in accelerating process optimization, and how this approach can dramatically reduce the experimental burden (13:30)
• Real examples of improved outcomes and efficiency through model-based control strategies, and why training and process understanding are essential for team success (16:10)
• A quick, actionable exercise biotech teams can use to map process risks and identify critical control points (16:55)

Whether you’re part of a start-up or a large biotech firm, this episode offers clear, strategic steps for implementing QbD and improving process reliability. Don’t forget to listen to Part 1 for more on QTPP and CQA, and visit www.bruehlmann-consulting.com for additional resources.

Next step:

Book a 20-minute call to help you get started on any questions you may have about bioprocessing analytics: https://bruehlmann-consulting.com/call

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