Correlation Over Time


I have data regarding the number of blood cells, and the number of a certain protein associated with blood cells, from 15 blood samples at different times. At time 1, I have one blood sample each from 15 subjects, with a measurement of blood cells as well as a measurement of the certain blood-cell-related protein. At time 2, I have the same blood cell and protein measurements again, from the same subjects (in between time 1 and time 2, medicine was given to each subject).

I would like to estimate the correlation between the change in number of blood cells and the change in number of blood-cell-related proteins, and the statistical significance of this correlation (if there truly is one). I know I can't just do simple correlation, because I want to test the correlation of the change over time between the measurements. I looked into R's cross-correlation ("ccf()") function, but that seems to be for many single measurements over multiple time points, while I have many measurements for each time point, but only two time points.

Please let me know of any way to test the correlation between changes in two variables, for just two time points.

Thanks very much,
It's much too simplistic to compute the change between time 1 and time 2 for each measurement -- that is, the change in blood cell numbers, and the change in blood-cell-related protein numbers -- and test correlation of those numbers, isn't it? Since there's only the one change in time (from time 1 to time 2) for each sample for each thing being measured, perhaps this is a possibility? I tried doing it this way but I wasn't able to tell if the answer really meant anything.