The Forgotten Variables: Baffles, Ports, and Tank Geometry in Real Fermentors When people talk about fermentation optimization, they usually start with the classics: media composition, pH, temperature, feeding strategy. All of these are valid and should (in my opinion) be considered first. But when you’re scaling up, transferring a process, or trying to debug a…

This is part III of an ongoing DoE series that I would have loved to read when I was first running these types of experiments in the lab.  You can start at the beginning, with part I: a general overview of what DoE is, here. You’re running a fermentation experiment. You want to figure out…

In R&D, it’s easy to collect dozens of process parameters and output variables—but much harder to interpret them all at once. That’s where correlation matrix heat maps come in: they turn overwhelming spreadsheets into intuitive visual patterns. What Is a Correlation Matrix Heat Map? A correlation matrix shows how strongly pairs of variables are related,…

As discussed in my previous post, DoE allows us (hopefully) to extract maximum insight from minimal runs. This post summarizes a two-round DoE strategy used to optimize final titer in a microbial fermentation process using two 12 x 250 mL ambr bioreactor setups across two weeks of experimentation. All data is fabricated and hypothetical. Round…

This is a follow-up for the post: Making Sense of Fermentation Data With Correlation Matrix Heat Maps Correlation matrix heat maps are powerful—but only if you know what you’re looking at. In this follow-up to our post on using heat maps in fermentation, we’re diving into super quick examples of good practices and common misinterpretations.…