Batch Scale-Up: can the key to success be found in human weight loss programs?

[Note: I have such a close relationship with batches that I tend to make them seem human. See, for example, previous blogs “If Batches had human rights: Telemedicine” part 1 and part 2.]

I get why it’s hard to lose weight by going on a diet. Suddenly, one day you go “on a diet” and stop eating as much as you want of whatever you want. Instead you start doubly depriving yourself: less quantity and less tasty. That’s hard. Then later, when you’ve reached your target weight, you have to figure out how to stay that way – off the diet. Good luck in successfully maintaining the weight you attained under the regimen. How could this ever work? I suppose if maintenance were easy there wouldn’t be so many competing strategies out there.

Isn’t this like making a new product? One day you bear down and bring all the right things together; you add, stir and heat/cool; you endure. It’s been neither quick, nor easy, but finally you have the formulation that is oh-so-good. Success attained, you now have to go off into the world and keep making this stuff. In fact, you need lots of it … so you go off your formulation path and scale up. Did the formulation prepare you for scale-up? Prepare? No way.

Do either of these first steps prepare you for the second one? Nope.

A while ago I noticed that I had started carrying around a “corporation” under my belt. So, I did what any decent physicist would do when confronted with experimental data that showed a faulty (nutrition) model: changed the model. I put together a different model/procedure – call it a recipe – and tried again. Further, as a physicist, I needed measurements; I weighed myself daily.

Yeah, it took time … I like to say that I lost weight “asymptotically” – but you can say, “slowly”. Anyhow, that was a long time ago. The new recipe worked; I continue to measure daily. One and done.

Can there be something here that applies to batches?

Yes, batches need to be made correctly. They need a procedure – call it a recipe – that meets the needs not only of a formulation, but of a manufactured batch. Think about shelf-life: would shelf-life be an issue for, say, salt water? Of course not; salt water is a solution; and solutions are in thermodynamic equilibrium … they’re forever. But batches come to the world in state of kinetic stability, a nice way of saying they’re degrading right now. If the batch is well made, the degradation is slow; if not well made, the degradation can occur during manufacture. How can you know what is happening to the batch moment-by-moment while you are standing outside the opaque stainless-steel walls of a mixing tank?

Measurements. Just like I used the scale to gauge the progress of weight loss - so too the correct analytical measurements can tell an awful lot about the state of the batch inside the tank. And this rule applies beyond formulation … to scale-up, the equivalent of weight-maintenance. Measure. It’s just as Peter Drucker said about managing anything: “If you can’t measure it, you can’t improve it.”

There’s more. When seeking a new nutrition model, one that’s optimum for me, I tried new things, changes to my recipe such as different foods, exercises, and more. Some worked well, meeting the three critical criteria – weight-control; taste; health. Isn’t it the same for formulations? The criteria are different, but the concept is the same: as you try alternative ingredients/concentrations/agitation/temperature you look for positive results. But why not have the correct measurements and in-process metrics to help objectively judge the effectiveness of your changes?

All this can be done in the formulation stage, leading to a robust product, well-understood. What’s more the same criteria are applicable to the scale-up batches as well.

After all, a scale-up is successful when you offer me two spoonfuls of product, one made in the Formulation Lab and the other in a large tank … and I can’t tell the difference.

Like weight-loss, the risks are too great, the rewards too bountiful to accept a strategy of pain followed by bewilderment. Start right with the correct measurements and an understanding of stability; then scale-up with the same principles.


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