Hi sorry for the delat, for each subject you have 2 subject level structural parameters (V and CL) and 3 occasion level parameters (occasions for V). Thus, there are 5 parameters for each subject
Then NLME tries to fit the model using 3 points for each subject. If you look into eta shrinkage sheet, all values tends to be near 1. When ε-shrinkage is large, the individual predictions are of little value for assessing model adequacy because the individual predictions “shrink” back toward the observation, meaning that IPRED ≈ DV (observation).
By the way I don't think you can get observed earlier Volume of distribution with given data.
Trying this analytical solution for 1cmt fo absorption and fo elimination model (steady state) in R
D = 600
V = 1401.54
ka = 0.30643
Cl = 12.7682
tau = 24
t = 22.08
k = Cl/V
C = D/V*ka/(ka-k)*(exp(-k*t)/(1-exp(-tau*k)) - exp(-ka*t)/(1-exp(-ka*tau)))
one can find the predicted value at some time point.
Another way is to create that simple model in Phoenix (about 10 clicks) and use Initial Estimates tab for quick estimations
Please also check again your data since Kel tends to be muc higher than Ka