Randomisation & Sample Size – Clinical BA Study [Power / Sample Size]
Hello everyone,
Firstly I would like to say thankyou to the contributors to this forum – it has been an invaluable resource for me in learning more about BE and other statistical methods.
I am writing about a clinical bioavailability study our research group plan to undertake using a drug that is known to have saturable absorption; we are investigating the effect of co-administering a range of doses of a nutritional supplement (until reaching steady state) with the drug using a crossover design as follows:
A - Drug alone for 5 days
B - Drug + 'x' mL supplement for 5 days
C - Drug + 'x' mL × 2 supplement for 5 days
D - Drug + 'x' mL × 4 supplement for 5 days
Sampling would be carried out on the morning of Day 6 for each treatment (to calculate AUC over the dosing interval). Since the study will be carried out in patients and due to budget limits, we only expect to be able to include around 12 subjects. We expect that the supplement will increase bioavailability.
I have read through some useful threads on the forum (#1368, #1423) and some very helpful lecture slides posted by HS (here and here). From these it seems that a Williams design for a four-treatment, four-period crossover is suitable (as drawn by HS in this post).
This design results in 4 treatment sequences, with 3 patients assigned to each sequence. My question is how would I best calculate power based on this design and sample size? As we expect AUC will differ between treatments, and are not interested in testing Bioequivalence limits between treatments (not a regulatory study - only interested in comparing AUC's between treatments), I am unsure whether I can use sample size calculations intended for BE studies in this context. For reference the CVintra% I estimated using the FARTSSIE spreadsheet for AUC at steady state is 32.19%.
Another question (possibly silly) is would we be better off using only a single treatment sequence (eg. ABCD) for all patients due to the small sample size and accept that a period effect may be present?
Sorry for the long post and thanks in advance for any advice
Kind regards,
Michael
Firstly I would like to say thankyou to the contributors to this forum – it has been an invaluable resource for me in learning more about BE and other statistical methods.
I am writing about a clinical bioavailability study our research group plan to undertake using a drug that is known to have saturable absorption; we are investigating the effect of co-administering a range of doses of a nutritional supplement (until reaching steady state) with the drug using a crossover design as follows:
A - Drug alone for 5 days
B - Drug + 'x' mL supplement for 5 days
C - Drug + 'x' mL × 2 supplement for 5 days
D - Drug + 'x' mL × 4 supplement for 5 days
Sampling would be carried out on the morning of Day 6 for each treatment (to calculate AUC over the dosing interval). Since the study will be carried out in patients and due to budget limits, we only expect to be able to include around 12 subjects. We expect that the supplement will increase bioavailability.
I have read through some useful threads on the forum (#1368, #1423) and some very helpful lecture slides posted by HS (here and here). From these it seems that a Williams design for a four-treatment, four-period crossover is suitable (as drawn by HS in this post).
This design results in 4 treatment sequences, with 3 patients assigned to each sequence. My question is how would I best calculate power based on this design and sample size? As we expect AUC will differ between treatments, and are not interested in testing Bioequivalence limits between treatments (not a regulatory study - only interested in comparing AUC's between treatments), I am unsure whether I can use sample size calculations intended for BE studies in this context. For reference the CVintra% I estimated using the FARTSSIE spreadsheet for AUC at steady state is 32.19%.
Another question (possibly silly) is would we be better off using only a single treatment sequence (eg. ABCD) for all patients due to the small sample size and accept that a period effect may be present?
Sorry for the long post and thanks in advance for any advice

Kind regards,
Michael
Complete thread:
- Randomisation & Sample Size – Clinical BA StudyMike_270 2011-02-01 11:39
- Randomisation & Sample Size – Clinical BA Study ElMaestro 2011-02-01 12:08
- Randomisation & Sample Size – Clinical BA Study Mike_270 2011-02-01 13:18
- Randomisation & Sample Size – Clinical BA Study ElMaestro 2011-02-01 14:24
- Randomisation & Sample Size – Clinical BA Study Mike_270 2011-02-02 00:47
- Randomisation ElMaestro 2011-02-02 08:48
- Randomisation & Sample Size – Clinical BA Study Mike_270 2011-02-02 00:47
- Randomisation & Sample Size – Clinical BA Study ElMaestro 2011-02-01 14:24
- Randomisation & Sample Size – Clinical BA Study Mike_270 2011-02-01 13:18
- Take all you can get d_labes 2011-02-02 10:36
- Take all you can get Mike_270 2011-02-02 11:41
- Budgetary stuff d_labes 2011-02-02 12:13
- Take all you can get Mike_270 2011-02-02 11:41
- Randomisation & Sample Size – Clinical BA Study ElMaestro 2011-02-01 12:08
