Terminal BLQ Values and AUCinf Estimation

Phoenix
1

In a DDI study that included 27 subjects, our analyte was assessed with and without a co-administered drug for 0-120 h. The analyte was not detectable in any subject after 24 h and was detected in only 6–8 subjects at the 24-h time point and in 20 subjects at 12 h. All concentrations after 24 h through 120 h were BLOQ.

I am trying to fit the data to assess the GMR for AUCinf, but I am challenged by the fact that, for most subjects, the percentage of extrapolated AUC exceeds 20%. Can the algorithm in Phoenix impute values based on the observed terminal phase?

Please note that I have tried the imputation methods outlined in this paper. However, the methods described require at least some subjects to have observed values at these time points (24-120) to impute values for the other subjects.

The elimination half-life of our analyte typically ranges from 10 to 20 hours.

2

maybe try building a compartmental model instead if the data is very limited inthat region. You experiment with the BLQ option in the model too, since instead of completely censoring those data, model that it’s somewhere between 0 and the LLOQ.

Handling of LLOQ values in Phoenix

Alternatively Sparse NCA could be an option,an example is detailed inthe help.
Sparse_sampling_NCA_example

Simon.

3

also if you want to share some example data here as a CSV or PHXPROJ we could advise better, or send it in to support@certara.com if it is confidential and we will respond privately from there, Simon.