Response following a single dose
18 important questions on Response following a single dose
What are reasons for the time delay (the gap between the plasma concentration and the response)?
- pharmacodynamics:
- systems in flux: when the site of meassurements is in another compartment than the site of action.
What 2 reasons can be a cause for the delay of the response after the concentration?
By what kind of factors is the time of onset of response govered?
- absorption
- distribution to target site
- Higher grades + faster learning
- Never study anything twice
- 100% sure, 100% understanding
What are the PK variables?
So, there has to be 1 equation with 7 unknown variables.
What is target AUC dosing?
This is not feasible in daily clinical practice because of patient discomfort and costs. So this is not efficient.
What kind of methods can be used to determine optimal sampling?
- Monte Carlo simulations: This requires pharmacokinetic population models.
So what is the step plan in the experimental approach?
2) divide patients into 2 groups: calculate the AUC from the limited samples of the study group and use the other group as validation group for the selecting of optimal sampling times.
What is the classical approach for the study group?
- Calculate the relation between C and AUC by multiple regression analysis. e.g. for 2 data points. repeat this for any combination of data points.
What is the classical approach for the validation group?
-Calculate for each subject the true AUC using all data points
-Calculate for each subject the estimated AUC using the equation for each combination of data points.
- calculate the root mean squared error (RMSE) (measure of precision)
How goes the evaluation according to the classical approach?
- select minimal number of samples needed (so that acceptable precision and minimal sampling times are obtained)
What are limitations and drawbacks of the classical approach?
- The number of data points are limited so a limited accuracy.
- A measurement at exact time point is required what is difficult in practice.
- it is sensitive to outliers so a limited precision
- The true AUC is not exact so a limited accuracy
- there are many calculation so it really takes time.
What are the improvements since the classical approach?
- A replace multiple regression analysis by Bayesian estimation of PK parameters. This means that you have a best estimate of CL, F and AUC.
- Automatic calculation
How is the first step of the Monte Carlo simulation performed? (generation of data)
in between: random noise (interindividual variability)
b) individual PK parameters (for each subject)
in between: PK model, dose, time schedule
c) true plasma concentrations (at time points of measurement)
in between: random noise due to assay error
d)This results into a measured plasma concentration
How is the second step of the monte carlo analysis (analysis of dat) performed?
in between: you perform analysis
b) you have an estimated AUC
in between: you compare the estimated AUC with the true AUC
c) evaluation
Of course you also have a mean error and a root mean squared error which are a measure of bias and a measure of precision, respectively during the evaluation.
How are accuracy and precision defined?
precision: All datapoints are may be wide scattered but the mean value is near to the expected value. It is represented by the RMSE (root mean squared error)
What is the formal definition of accuracy?
bias = lack of accuracy
What is the formal defiinition of precision?
What are the advantages of the Monte Carlo simulation?
- unlimited number of measurements
- exact AUC known
- data of all patients used (for PK population model)
- study design can be chosen freely
The question on the page originate from the summary of the following study material:
- A unique study and practice tool
- Never study anything twice again
- Get the grades you hope for
- 100% sure, 100% understanding