Bioequivalence and Bioavailability Forum

Dear IP,
If you have WinNonlin and you're willing to do a bit of modelling & simulation you can use VIF (Variance Inflation Factor) from your simulation to choose between different study designs.

VIF is the the multiplier of the residual mean square, used in deriving the asymptotic variance of the parameter estimates. Useful in simulations, to find optimal experimental design. [Like AIC] Smaller values are better.

So an example of usage would be to;

1. Fit data from Pilot study (or use data from literature) to get final model parameters.
   
2. Perform simulations using these model parameters of different proposed sampling regimens, (can all be in one source data sheet, just use a variable e.g. Design A, B, C etc. as a the sort variable.
   
3. Identify the Parameters of interest and choose the design that minimises VIF.

Simon.

PS I also like to see plot the Summary Table and Predicted table from my simulations to see visually the difference between my simulation and what I will actually observe with that sample schedule e.g.

and here are the corresponding VIFs for Cmax, note that 1x was 11 samples whereas the other two designs were just 8 samples. Roughly speaking the ratio of VIF is analogous to the ratio in which you would expect CV% to change in the future experiment. So you can see the second "cheap" design is markedly better for Cmax.