I've been lurking on this question because I'm sure there are likely some stong opinions on this topic. Here's one way to set up a 96 well experiment.
This design does some things that I think are useful.
In the experiment there are continuous factors:
1. Drug, an inhibitor I'm interested in studying
2. Stim, the thing stimulates a response the drug is supposed to inhibit
3. Serum level, grows cells better but increases background of the response
and some categorical factors:
1. Media type
2. Cell line, different cell line for each plate
To make the plate setup reasonable I want to place some restrictions on randomization. If I had lots of time I could program the pipetting robot to fully randomize the entire plate, but if just restrict randomization I can keep concentrations down columns and across rows the same, and plating gets a lot more simple.
First of all, for the scope of this, I essentially have 384 wells to work with, 96 per plate, and 4 plates (one for each cell line.) For the factors I'm working with, I can easily look at 2nd order interactions and quadratic effects for the continuous terms. When I set up the plates I have 12 columns and 32 rows (8 rows for each of the 4 plates.)
In the DOE dialog, I'm going to restrict the randomzation for rows and columns. This means making some factors "hard" to change and some "very hard.", which makes this a split strip plot experiment. Whole plots correspond to hard, and Subplots correspond to very hard to change factors. So if I have 12 subplots, and 32 (8x4) whole plots, then the hard to change things (in this case Drug and Serum) will be constant down the columns and the each indifidual row will be the same across the plate. Let me explain this a little more. Each column has a different concnetration, the concentration is the same down the entire column. (Super handy if you're multichannel pipetting your own plates.)
The last thing to consider is the plate/cell line. What I really need is a three way split plot, so cell line/plate would be "Super Hard to Change", but that's not an option, and It might be better if there was a different subplot pattern for the columns for each plate, but this is pretty good. (realistically, just making 8 whole plots and 12 subplots and using the same plate layout for each of the four cell lines is probably good enough, plus it reduces opportunities for error in the plate layout.)
DOE(
Custom Design,
{Add Response( Maximize, "Y", ., ., . ),
Add Factor( Continuous, 2, 25, "Drug", 1 ),
Add Factor( Continuous, 0.02, 0.1, "Serum", 1 ),
Add Factor( Categorical, {"IMDM", "RPMI", "DMEM"}, "Media", 2 ),
Add Factor( Continuous, 5, 50, "Stim", 2 ),
Add Factor( Categorical, {"L1", "L2", "L3", "L4"}, "Plate Number", 2 ),
Set Random Seed( 550796982 ), Number of Starts( 1 ), Add Term( {1, 0} ),
Add Term( {1, 1} ), Add Term( {2, 1} ), Add Term( {3, 1} ), Add Term( {4, 1} ),
Add Term( {5, 1} ), Add Term( {1, 2} ), Add Term( {1, 1}, {2, 1} ),
Add Term( {2, 2} ), Add Term( {1, 1}, {3, 1} ), Add Term( {2, 1}, {3, 1} ),
Add Term( {1, 1}, {4, 1} ), Add Term( {2, 1}, {4, 1} ),
Add Term( {3, 1}, {4, 1} ), Add Term( {4, 2} ), Add Term( {1, 1}, {5, 1} ),
Add Term( {2, 1}, {5, 1} ), Add Term( {3, 1}, {5, 1} ),
Add Term( {4, 1}, {5, 1} ), Add Term( {1, 3} ), Add Term( {1, 4} ),
Add Term( {4, 3} ), Make Strip Plot Design, Set N Whole Plots( 32 ),
Set N Subplots( 12 ), Set Sample Size( 384 ), Optimality Criterion( 2 )
);
JMP Systems Engineer, Health and Life Sciences (Pharma)