Re: PK analysis of data from different occasions
Hi, Havard: I assume the compound is orally administered. A simultaneous modeling is of course a must for data containing three occasions. Here are few my comments without actually looking at data, GOF and knowing your objectives:
1. identify the most robust absorption model;
2. incorporate IIV and IOV on relative bioavailability; or just IOV on F to explain the interoccasion variability in PK 3. obtain the best IIV model for two compartment model since it describe your data at most occasions except 1.
4. explore different residual error models
best,
david
> The data set I'm analyzing consist of concentration-time profiles
> obtained at three different occasions for every subject (n=20).
> Non-compartmental analysis and individual modeling indicate changes in
> CL/F between the occasions, possibly explained by renal function. If I analyze
> the occasions separately, a two-compartment model describes thedata well at
> occasions 2 and 3, but not at occasion 1. At occasion 1
> large inter-individual variation is observed and a one-compartment model
> can to some degree describe the data. If I analyze all occasions
> simultaneously with between-occasion variation, a one-compartment model
> is able to fit the data reasonably well (two-compartment model is not
> considered robust). The parameter estimates are in the right ball park,
> but GOF plots from the simultaneous analysis indicate model
> misspecification typical for a one-compartment model fit of
>
> "two-compartment data".
>
> My question is therefore how I should proceed? Will separate or
> simultaneous modeling be most ideal and what should I consider to get
> most relevant information?
>
> Best regards,
> Havard
>
> Havard Thogersen,
> Master student
> University of Oslo/Cincinnati Children's Hospital Medical Center
>
> Pediatric Pharmacology Research Unit and Laboratory of Applied Pharmacokinetics & TDM
>
> Cincinnati Children's Hospital Medical Center
> 3333 Burnet Avenue, MLC 6018
> Cincinnati, OH 45229-3039
> Phone: (513) 636-9011
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