When performing multivariate analysis, say multiple linear regression, there's typically an objective (like "higher yields" or "troubleshoot campaign titers"). And there's typically a finite set of parameters that are within control of the production group (a.k.a. operators/supervisors/front-line managers).
This finite parameter set is what I call, "actionable factors," or "process knobs." For biologics manufacturing, parameters like
Examples of non-actionable parameters include:
This finite parameter set is what I call, "actionable factors," or "process knobs." For biologics manufacturing, parameters like
- Inoculation density
- pH/temperature setpoint
- Timing of shifts
- Timing of feeds
- Everything your process flow diagram says is important
Examples of non-actionable parameters include:
- Peak cell density
- Peak lactate concentration
- Final ammonium
- etc.
In essence, non-actionable parameters are generally measured and cannot be changed during the course of the process.
Why does this matter to multivariate analysis? I pick on this one study I saw where someone built a model against a commercial CHO process and proved that final NH4+ levels inversely correlates with final titer.
What are we to do now? Reach into the bioreactor with our ammonium-sponge and sop up the extra NH4+ ion?
With the output of this model, I can do absolutely nothing to fix the lagging production campaign. Since NH4+ is evolved as a byproduct of glutamine metabolism, this curious finding may lead you down the path of further examining CHO metabolism and perhaps some media experiments, but there's no immediate action nor medium-term action I can take.
On the other hand, had I discovered that initial cell density of the culture correlates with capacity-based volumetric productivity, I could radio into either the seed train group or scheduling and make higher inoc densities happen.
by Oliver Yu
What are we to do now? Reach into the bioreactor with our ammonium-sponge and sop up the extra NH4+ ion?
With the output of this model, I can do absolutely nothing to fix the lagging production campaign. Since NH4+ is evolved as a byproduct of glutamine metabolism, this curious finding may lead you down the path of further examining CHO metabolism and perhaps some media experiments, but there's no immediate action nor medium-term action I can take.
On the other hand, had I discovered that initial cell density of the culture correlates with capacity-based volumetric productivity, I could radio into either the seed train group or scheduling and make higher inoc densities happen.
by Oliver Yu
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