I'm in biotech (as a software engineer/data scientist) and here this stuff is used a lot. Experiments are very hands on and expensive in terms of inputs so you

I'm in biotech (as a software engineer/data scientist) and here this stuff is used a lot. Experiments are very hands on and expensive in terms of inputs so you want to be efficient with your use of them. Bayesian approaches (e.g. optimization with Gaussian processes) tend to be very serial in nature: later sampling points are decided from the information you get earlier on. But these biological experiments can take days or weeks so you want to run them in parallel as much as possible. DoE is excellent for that. I'm speccing out a D-optimal design as we speak (though I'm not sure this is what we will use for the particular project I'm on).