Chapter 32
Optimal Sampling
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Optimal Sampling
Determining the 'Best' Time to Collect Samples
Student Objectives for this Chapter
- To understand the idea of optimal sampling
- To understand the graphical and analytical methods of determining optimal sampling times
Once we have developed a pharmacokinetic model for a drug and obtained an understanding of the expected parameter values we can start to apply this information to patient care. This information could be applied directly for dosage regimen. This is how various dosage regimen nomograms or other recommendations are developed. For some drugs more control is required and a therapeutic drug monitoring (TDM) approach may be appropriate. During the development of a TDM procedure selecting the best times to sample drug concentration is critical. This is where optimal sampling can play an important role.
Why Optimal Sampling
- Limited samples, minimize sample numbers
- Sampling requiring needle stick, heel stick is painful
- Indwelling cannula may be used but as easy to set-up
- Each sample involves some blood loss
- Sample Collection and Analysis
- Sample organization and time required
- Assay costs
- Despite having limit data we want the Best Estimate of parameter values
Optimal Sampling
Optimal sampling at its most basic provides one best time for each parameter. For example, assuming a one compartment intravenous model when would be the best sample time for determining a value for the elimination rate constant (kel). If the expected value was 0.2 hr-1 the best time to sample can be calculated as 5 hours. According to this approach if you can repeat the sample a second (or third) sample at the same time would be suggested. While repeat samples aren't a bad idea it might not be the best approach if the value for kel is different from the expected value. A range of sample times might be better. For example if we expect the value of kel to be in the range of 0.1 to 0.3 hr-1 we should pick sample times in the range of 3.3 to 10 hours.
How did we get these sample time estimates. There are a number of approaches. Graphical and analytical. This topic will be discussed by considering these techniques that can be used to explore the optimal sampling time for best model parameter estimation.
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