Looking for your inputs. I have PK data from oral dosing at mulitple dose levels and based on Day 1 AUC and Cmax comparison between Dose levels there is non-linearity observed (increased exposure with dose). However there is no change in the half life also the Tmax is consistant between dose groups. Given this I thought it could be due to difference in bioavailability at each dose, but please suggest what else could be the reason and what type of model should I use to fit the data?
There is additional problem in same data, when I fit Day 1 data and simulate day 13 there is significant underprediction observed (at individual dose level) . Again half life on day 1 and day13 are similar (terminal slopes parallel between Day 1 and Day13), Tmax is also same. Please suggest what type of model should I consider to fit all the data using as population approach.
Hi Nilesh, this is an interesting one and I wonder if it could be an artefact that at the lowest level some of the curve is lost below LoQ? Might be easier to comment on if we know the relative ratios for CMax and AUC, or better yet the data itself.
Thank you for your reply. It is less likely an artifact as all Concentrations are quantifiable at all dose levels. Can you please elaborate what do you refer by relative ratios for Cmax and AUC. Do you mean dose normalized Cmax and AUC here?
Just following up if you can comment on the non-linearity between dose level. Is the slope value of 1.5 something to consider as non-linear or significant to try capturing in the model?
I tried dose dependent bioavailability model to fit the Day 1 PK data and it is comparitively better than linear model, which give some confidence that it is not artifact.
Also, any thoughts on non-linearity between Day1 and Day 13 exposure (higher exposure on Day 13 than predicted using Day1 data) with no change in the thalf/terminal elimination.