Multivariate Analysis in Biologics Manufacturing
All these tools for data acquisition and trend visualization and search are nice. But at the end of the day, what we really want is process understanding and control of our fermentations, cell cultures and chromatographies.
If a process step performs poorly, we want to know why. If a process step performs well, we want to know why. And if the process is performing within expectation, we want to know. Put very simply, we want to know.
For biological systems, the factors that impact process performance are many and there are often interactions between factors for even simple systems... like viral inactivation of media.
This one time, we were getting clogged filters with white residue when transferring media from the prep tank to the bioreactor. On several occasions, the clogging put the transfer in hold and stopped production.
After studying the data, we found that pH and Temperature were the two main effects that significantly impacted clogging. If the pH was high AND the temperature was high, the solids would precipitate from the media. But the pH or temperature during the viral inactivation was low, the media would transfer without exception.
After identifying the multiple variables and their interactions, we were able to change the process to eliminate clogging as well as simplify the process.
For even more complex systems like production fermentation, multivariate analysis produces results. In 2007, I co-published a paper with Rob Johnson describing how multivariate data analysis can save production campaigns. From the article is the regression pictured below.
You can see that it isn't even that great a fit. Statisticians shrug all the time at RSquares less than 0.90. But from this simple model, we were able to turn around a lagging production campaign and achieve 104% Adherance To Plan (ATP).
The point is not to run into trouble and use these tools & know-how to fix the problem. Ideally, we understand the process ahead of time by designing in process capability and then fine-tune it at large-scale; we are less fortunate in the real world.
My point in all this is if you are buying tools and assembling a team without the destination in mind: process understanding and control, then you won't know which are the right tools or what is the best training. Keeping your eye on the process understanding/multivariate analysis prize will put you in control of your bioprocesses and out of the spotlight of QA or the FDA.
