Sample size for PK linearity [Power / Sample Size]

posted by Helmut Homepage – Vienna, Austria, 2009-05-19 15:19 (5829 d 12:42 ago) – Posting: # 3702
Views: 19,853

Dear Kro!

❝ I would like to estimate a sample size for a PK linearity study.


Keep terminology high: since you don’t know the relationship beforehand, you should call it a PK proportionality study. Dose linearity is a subcategory.
  1. Dose linearity
    1. A straight line (PK response v.s. dose) through the origin = no significant (p>0.05) difference of the intercept from zero = 95% confidence interval of the intercept includes zero.
    2. A straight line, but with nonzero intercept.
  2. Dose proportionality
    Any relationship other than linear; generally a power model.
In other words if PK linearity is shown, PK proportionality is also given – but not the other way ’round.

❝ The study design plans to test 4 different doses (10, 20, 30 and 40).

❝ I need to test the bioequivalence for each dose, compared to the reference dose which is 20.


In the most simple case run a 4-way cross-over, normalize PK-responses (10, 30, 40 doses) to the 20 mg dose, and evaluate BE at 80–125%. A Bonferroni-correction of the alpha-level was advised by the German BfArM and was acceptable in a recent MRP in 15 EU member states. Your would perform three comparisons; therefore α/3 = 0.05/3 or 96.6% confidence intervals instead of 90% CIs. The overall patient’s risk is kept at <0.05, since 1 – (1 – 0.05/3)³ = 0.0492. See also this thread and Martin’s suggestions of another approach.

❝ In addition I need to calculate the linear correlation slope for the four doses, a deviation of 20% between doses being acceptable.


I’m not sure what you mean by ‘a deviation of 20% between doses being acceptable’. If you run model I (1 and/or 2) you get a common slope which can have any value (depending on the units of dose and PK response). So a 20% deviation from what?

❝ What is the required methodology and what is the formula to calculate the sample size?


If you opt for the Bonferroni-approach, run a sample size estimation as usual based on the expected T/R-ratio (generally 0.95), CVintra, and α 0.05/3 (instead of 0.05).
Example (T/R 0.95, power 80%), total cross-over sample sizes):
                 α
CV%      0.05000  0.01667
10.0        8       10 
12.5       10       14
15.0       12       16
17.5       16       22
20.0       20       28
22.5       24       34
25.0       28       40
27.5       34       48
30.0       40       56

Sample sizes are larger in order to compensate for simultaneous testing.

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