Pick Actionable Factors for Multivariate Analysis

Here's you:

• You collect a ton of data from your large-scale cell culture/fermentation process.
• You're going blind alt-tabbing between Excel and JMP.
• You spend waaayyyyyyy too much time pushing around data and not getting answers.

And when you finally have the data the way you want it, your multivariate analysis tells you something like,

Final NH4+ (mmol) and Peak Lactate (g/L) correlate with Volumetric Productivity (mg/L/day).

Scientific curiosities are great for long-term process understanding, but when you're in the middle of a flagging campaign, manufacturing managers want to hear about immediate and short-term actions they can take to meet the campaign goals.

The key to avoiding this career blunder (of presenting irrelevant work to your customers) is to select only actionable parameters for your main effects and interactions when building your multivariate analysis. In JMP, it looks something like:



In the above example, we can control inoculation density (Ini VCD) by extending the previous culture's duration. As well, a biologics license agreement may allow a window for executing pH shifts (VCD at pH Shift) as well when to feed (Cult Dur at Batch Feed). Actions that manufacturing can take by simple scheduling changes are ideal for putting into the multivariate analysis that deliver immediate solutions.

Constructing the main effects of your model by selecting actionable parameters is best for solving REAL manufacturing problems as well as for advancing your career as the person who finds the way to meet campaign goals.