The paper illustrates innovative ways of using the CARSO (Computer Aided Response Surface Optimization)
procedure for response surfaces analyses derived by DCM4 experimental designs in
multivariate spaces. Within this method, we show a new feature for optimization studies: the results
of comparing their quadratic and linear models for discussing the best way to compute the
most reliable predictions of future compounds
