Algorithm (geometric progression) [Design Issues]
Dear Eduardo!
Oh my goodness!
I dug the example out from an unpublished study I’ve done in 1987 (a Monte Carlo-Simulation on the influence of different sampling schedules on BE).
In this study I was referring to a contribution to a book* which is out of print for many years. The algorithm is given there without any further source – although a geometric progression is an obvious solution, at least for a one-compartment model.
The book actually is a collection of presentations from a conference which was held in 1978 (!)
Just to quote the article again:
Sampling strategies
Only unspecific rules based upon general properties of compartmental models can be given if model type discrimination is the purpose of the study. They may be summarized as follows:
Many articles have been published on the topic of optimal sampling for PK parameter estimation, but only little (or even nothing?) for BE.
Up to now, I think choosing the ‘right’ schedule is still mainly a decision coming from the ‘guts’ of an experienced person (with some ethical and financial constraints)…
Just remember the main points:
No, just go on, that’s what the forum is for – if nobody has some time to spare, you simply receive no answers…
❝ Can you please tell me […] what's your source?
Oh my goodness!
I dug the example out from an unpublished study I’ve done in 1987 (a Monte Carlo-Simulation on the influence of different sampling schedules on BE).
In this study I was referring to a contribution to a book* which is out of print for many years. The algorithm is given there without any further source – although a geometric progression is an obvious solution, at least for a one-compartment model.
The book actually is a collection of presentations from a conference which was held in 1978 (!)
Just to quote the article again:
Sampling strategies
Only unspecific rules based upon general properties of compartmental models can be given if model type discrimination is the purpose of the study. They may be summarized as follows:
- take as many samples as possible
- sample as long as there is a signal recognizable above detector background noise
- sample frequently at the beginning and at larger time intervals towards the end of the study.
Many articles have been published on the topic of optimal sampling for PK parameter estimation, but only little (or even nothing?) for BE.
Up to now, I think choosing the ‘right’ schedule is still mainly a decision coming from the ‘guts’ of an experienced person (with some ethical and financial constraints)…
Just remember the main points:
- AUC is an integrative parameter (differences in a cross-over setting easily mean out),
- sample until at least 80% of AUC∞ is covered,
- frequent sampling around your expected peak is very important in order to reduce its variability.
❝ That way I won't be doing so many beginner's questions!
No, just go on, that’s what the forum is for – if nobody has some time to spare, you simply receive no answers…
- Süverkrüp R. Optimization of Sampling Schedules for Pharmacokinetic and Biopharmaceutic Studies. In: Bozler G, van Rossum JM, eds. Pharmacokinetics During Drug Development: Data Analysis and Evaluation Techniques. Stuttgart, New York: G. Fischer; 1982. p. 174–90.
—
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
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- Algorithm (geometric progression) eduardojmorales 2006-10-10 18:23
- Soliloquy? H_Rotter 2006-10-06 13:27
- How to Define Sampling Interval eduardojmorales 2006-10-05 23:16