Sparse sampling [Design Issues]
Dear Dixit!
Are you interested in planning a Population PK study? You have to have access to at least one 'rich' data set. Set up the full model, estimate its parameters and subsequently eliminate data points (=reduced data sets). Estimate parameters of the model for the reduced data sets and assess the outcome based on bias (deviation from full data set's) and CVs. Though there are some strategies available (keywords: D-optimal design, informative block randomized design), the process is iterative and time-consuming. The only 'easy' case is an infusion, one-compartment model: Two time points - end of infusion, tlast.
Some references: D-optimal design, informative block randomized design.
Recommended introduction:
Are you interested in planning a Population PK study? You have to have access to at least one 'rich' data set. Set up the full model, estimate its parameters and subsequently eliminate data points (=reduced data sets). Estimate parameters of the model for the reduced data sets and assess the outcome based on bias (deviation from full data set's) and CVs. Though there are some strategies available (keywords: D-optimal design, informative block randomized design), the process is iterative and time-consuming. The only 'easy' case is an infusion, one-compartment model: Two time points - end of infusion, tlast.

Some references: D-optimal design, informative block randomized design.
Recommended introduction:
Amit Roy and Ene I. Ette
A Pragmatic Approach to the Design of Population Pharmacokinetic Studies
The AAPS Journal 2005, 7(2), E408-E420
free online resource
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Helmut Schütz
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Dif-tor heh smusma 🖖🏼 Довге життя Україна!
![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- Sparse sampling dixit 2011-05-05 07:07
- Sparse samplingHelmut 2011-05-05 14:33
