Hello all,
I wonder if someone can give me some tips on PPC.
I am working on a midazolam dataset with a pediatric population, and have
decided to use PPC as a model validation technique. The dataset I am modelling
has up to 43 patients, at different ages, different weights, different times of
Paul,
Its not clear to me if you did a VPC (visual predictive check) using
just the final estimates of the parameters) or tried to do a posterior
predictive check (PPC) including uncertainty on the parameter estimates
in the simulation.
I dont have any experience with PPC but I dont think
Dear all,
Could someone please give me some tips coding vomitting event as an
absorption lag and bioavailability decrease?
It's a single dose oral solution with slow absorption. From data I
noticed that the time of vomitting was at least 4 hour after dose.
Some subjects had mutiple vomitting
Hi Gabriel,
Is it possible that you do not need a PK model? Can you use a
nonparametric (connect the dots) approach for the PK and just use that
to drive the PD model? Just a thought.
Susan Willavize, Ph.D.
Pfizer Global Pharmacometrics Group
-Original Message-
From: [EMAIL
Galadriel, could you turn the dose compartment off with an other event (EVID = 2, CMT = -1), then given another dose after that. E.G, with emesis at four hours:#ID TIME CMT AMT EVID IND 1 0 1 100 1 11 4 -1 . 20 1 4 1 100 1 2$PK IF(IND.EQ.1) THEN F1 = THETA(1) ; FRACTION NOT LOST ALAG1 =
Let me revise that, the previous would give the same fraction as lost for any time point after dosing#ID TIME AMT CMT EVID IND1 0 100 1 1 11 4 . -1 2 01 4 100 1 1 2$PK IF(IND.EQ.1) THEN F1 = 1 ; DON'T NEED TO CHANGE THIS, AMT AFTER EMESIS WILL VANISH WITH CMT = -1 ALAG1 = THETA(1) ELSE F1 =
Hi Mark,
This is a good question. I am not aware of any public domain simulation
work in extreme variability scenarios, so my comments are based on the
theory.
The fundamental problem with the standard NONMEM algorithm, where the
fixed effect and random effects are estimated
