I am having difficulty generating respective VPC plots for my final population PK model.
I would like to have a VPC with a solid line representing the median of the simulated concentrations, with dashed lines representing the 5th and 95th percentiles. Shaded areas should correspond to the 95% confidence intervals for the prediction lines.
In my attached model you will see a PK model for plasma, liver, and kidney, for some reason the VPC is not working for me. Sometimes I can get it to work but only for plasma, not tissues, but even then the shading does not come through.
Is there a fault in this feature, or something I am doing wrong, could you please assist?
Please see the link to my project and images below with the last 2 models for 2 separate compounds,
And here for the first compound, you see the entire confidence interval shading is missing for the 95% quantile, as well as nothing coming up for tissues. For the second compound nothing at all is coming up either for plasma or even any of the tissues.
please look at your XY axes, you are using semilog scale. Now look at PredCheck_ObsQ_SimQCI table. As you can see 5% quantile for 5% predicted quantile is negative!
That’s the answer. PHX couldn’t plot the shaded area for 5% predicted quantile.
regarding VPC for liver and kidney:
PHX fails in binning using K-means here. You can put your own bins or turn off this option
Thank you for explaining these to me. I am not sure why these are giving negative values… Is there anyway around this? Using the default seems easier, but is there a binning method that works best in these cases?
I did turn binning off, but still see the negative values.
I am most interested in obtaining a clear VPC for plasma, not so much tissues (these may be challenging).
Could it be something not right with my model causing these?
there are 2 different issues. First is related to shaded areas for plasma. The second is related to VPC for tissues (binning).
If you turn off binning you do not change the confidence intervals for plasma.
Math doesn’t care what kind of data you are using for building the model, so in case of uncertainty CI can go outside of semilog scale and PHX cannot do anything with it.
By the way I noticed that you are using same residual error CEps for different observations. Compiler does not like it.
currently the binning cannot be specified differently for each type of observation. you can always use your raw simulated data and do whatever binning/predcorrection you need using Phoenix , R or other tools.
The negative concentration need to be investigated more
Samer is right, you may need to investigate the model and change at least the type of residual error. It is sufficiently large for proportional error, that causes the negative values for simulated observations in VPC
Any clue on what type of error structure could be used, additive, multiplicative, mixed?
These should be multiple plasma concentration time profiles capturing multiple absorption distribution, trough and terminal elimination samples (i.e. concentrations differing by over 1 order of magnitude).
Now my model is in custom graphical mode, I do not see a way to change the error structure here, and if I convert back to bulletin all changes will be lost. What is the easiest way to make these adjustments?
Any clue on what type of error structure could be used, additive, multiplicative, mixed?
Any of them, also do not forget log-additive! Please note that the type of residual error could differ for observation types. Welcome to the world of modeling!
You need to investigate diagnostic plots and VPC data to choose the appropriate one (it is not so easy and straightforward!)
Now my model is in custom graphical mode, I do not see a way to change the error structure here, and if I convert back to bulletin all changes will be lost. What is the easiest way to make these adjustments?
click on the green rectangle with observation (say CKidney)
In the structure tab you see the name of observation, name of error variable and its type. You need to change the name of error (CKEps for example), select the type of error you want to explore for this type of observations and the initial value.