Hi all,
I am simultaneously fitting PK and PD data using a 2 comp PK oral model and an indirect response PD model with and Imax/IC50 relationship to the PK) The dataset is rich for each subject in both the PK and PD and comes from 100 subjects (~3500 data points in total). My model has 28 parameters that are estimated (including IIV, covariates, correlations and residual errors) and I’m using the QRPEM algorithm. The model runs successfully and fits the data well (after a few hours running…).
I’m now comparing between 2 rival models (the only difference is inter-individual variability in the IC50 parameter, assumed log-normal distributed). The model including the IIV has a significant lower -2LL than the one without it (drop of 83 units in the -2LL). The interesting observation is that IIV in the IC50 is estimated as 210% (with a 19% CV) with a nice distribution of ETAS and acceptable Shrinkage (0.35) Also, the population IC50 is estimated with a 38% CV.
On the rival model (without the IIV in IC50) the estimated population IC50 has similar value but better precision (7% CV). All other parameters have same values and comparable precisions between both models. Also VPC (1000 simulations) showed no difference between both models.
Is it possible in Phoenix to see the individual contribution of each subject to the overall -2LL (I think it might be possible in NONMEM?), I’d like to see if the drop in the -2LL when I include the IIV in the IC50 is mostly driven by 1-2 subjects?
Apologies for the long question for a potentially very short answer…?
Thanks in advance for your help
Pablo