Dear Hiba,
What is your complete error model? The information you provide is too
limited to be sure how to help you.
However, assuming you used a proportional error model with an additive
term for M3/BQL, you might get better results with an exponential error
model. For this, you need to use a transform-both-sides approach (TBS)
as explained on page 530 of
https://ascpt.onlinelibrary.wiley.com/doi/pdf/10.1002/psp4.12404, or the
example provided in the tutorial part II, example 2
https://ascpt.onlinelibrary.wiley.com/doi/full/10.1002/psp4.12422 (*)
which has both M3 and TBS included.
The reason is with the exponential-M3 model you can simulate decreasing
concentrations, with residual error, going down beyond the LLOQ - there
is no transition involved as with the proportional+ additive/M3 method.
Hope this helps,
Jeroen
*: Bauer, Robert J. "NONMEM tutorial part II: estimation methods and
advanced examples." /CPT: pharmacometrics & systems pharmacology/ 8.8
(2019): 538-556.
http://pd-value.com
jer...@pd-value.com
@PD_value
+31 6 23118438
-- More value out of your data!
On 19-06-2023 09:47, Hiba Sliem wrote:
Hello everyone
I have a simple question for a simple bicompartmental model where M3
method for estimating bql is used, because of that my predictions are
overly inflated at the tail end of the treatment period (bql levels),
which distorts my simulations.
I used this line to get corrected predictions:
IF(COMACT.EQ.1) PREDI=IPRED
But that doesn't improve my simulated data at low concentrations, is
there a way around it or should I use an other method to handle my bql
values?
Thank you in advance
