Replicate design evaluation [Regulatives / Guidelines]
Dear Sathya,
Congratulation!
The russian revolutionist LENIN has already stated "Learn, learn and once again, learn!" .
Things are not so easy in evaluation of BE for replicate cross-over designs (and not the second learn in Lenin's quotation, after experience with one evaluation of a conventional 2x2 cross-over IMHO).
The evaluation method usually involved (REML = restricted maximum likelihood) is a complicate iterative numeric procedure which cannot practically done by hand (See Helmut's post above in this thread).
Thus the only flow (cook book for chef cooks ) I can give you is:
1. Evaluate your concentration-time curves to get your desired pharmacokinetic parameters (like AUC, Cmax and so on) as usual for each subject in each period.
1.a log-transform the parameters believed to be distributed as log-normal (or are regulated to have been log-transformed).
2. Fire up your software capable of doing mixed effects analysis (SAS, Winnonlin or whatever you have and is convenient to you).
2.a Define your model (fixed, random effects, structure of variance-covariance terms) within that software.
2.b Require 90% confidence intervals for the treatment effect.
3. Look at the results and interpret them with your knowledge acquired up to now. If this is not enough see a statistician (seek for a competent one! ).
If you are dealing with average BE the only essential piece of the software output is the 90% confidence interval, which is used as usual in BE studies, replicate or not.
If you need some data to play with have a look at the FDA sitehttp://www.fda.gov/cder/bioequivdata/ http://www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Biostatistics/ucm081434.htm
Edit: Link corrected for new FDA’s website. [Helmut]
❝ I did only one Bioequivalence project in (2x2 Crossover study) with all your help.
❝ Now I want to develop my capability on Bioequivalence studies. So I tried to learn the Bioequivalence Study - Replicate Cross over.
Congratulation!
The russian revolutionist LENIN has already stated "Learn, learn and once again, learn!" .
❝ ... So please give me complete flow of one replicate design (like ... by Jaime_R, Barcelona ... for Parallel)
Things are not so easy in evaluation of BE for replicate cross-over designs (and not the second learn in Lenin's quotation, after experience with one evaluation of a conventional 2x2 cross-over IMHO).
The evaluation method usually involved (REML = restricted maximum likelihood) is a complicate iterative numeric procedure which cannot practically done by hand (See Helmut's post above in this thread).
Thus the only flow (cook book for chef cooks ) I can give you is:
1. Evaluate your concentration-time curves to get your desired pharmacokinetic parameters (like AUC, Cmax and so on) as usual for each subject in each period.
1.a log-transform the parameters believed to be distributed as log-normal (or are regulated to have been log-transformed).
2. Fire up your software capable of doing mixed effects analysis (SAS, Winnonlin or whatever you have and is convenient to you).
2.a Define your model (fixed, random effects, structure of variance-covariance terms) within that software.
2.b Require 90% confidence intervals for the treatment effect.
3. Look at the results and interpret them with your knowledge acquired up to now. If this is not enough see a statistician (seek for a competent one! ).
If you are dealing with average BE the only essential piece of the software output is the 90% confidence interval, which is used as usual in BE studies, replicate or not.
If you need some data to play with have a look at the FDA site
Edit: Link corrected for new FDA’s website. [Helmut]
—
Regards,
Detlew
Regards,
Detlew
Complete thread:
- random effect, fix effect in the guidance Appendix E LS 2008-02-05 18:53 [Regulatives / Guidelines]
- random effect, fix effect in the guidance Appendix E d_labes 2008-02-06 13:34
- random effect, fix effect in the guidance Appendix E LS 2008-02-06 17:58
- random effect, fix effect in the guidance Appendix E d_labes 2008-02-07 10:14
- random effect, fix effect in the guidance Appendix E SKR 2008-03-06 10:54
- Satterthwaite degrees of freedom Helmut 2008-03-06 13:57
- Satterthwaite degrees of freedom d_labes 2008-03-10 09:59
- Satterthwaite DF; SAS Helmut 2008-03-10 12:24
- Satterthwaite DF; SAS d_labes 2008-03-10 14:50
- Satterthwaite DF; SAS mathews 2008-03-11 07:12
- SAS Proc Mixed coding, replicate design d_labes 2008-03-11 09:43
- SAS Proc Mixed coding, replicate design Sathya 2008-09-17 07:21
- Replicate design evaluationd_labes 2008-09-17 10:49
- Replicate design evaluation Sathya 2008-09-18 06:43
- Replicate design evaluationd_labes 2008-09-17 10:49
- SAS Proc Mixed coding, replicate design Sathya 2008-09-17 07:21
- SAS Proc Mixed coding, replicate design d_labes 2008-03-11 09:43
- Satterthwaite DF; SAS mathews 2008-03-11 07:12
- Satterthwaite DF; SAS d_labes 2008-03-10 14:50
- Satterthwaite DF; SAS Helmut 2008-03-10 12:24
- Satterthwaite degrees of freedom d_labes 2008-03-10 09:59
- Satterthwaite degrees of freedom Helmut 2008-03-06 13:57
- random effect, fix effect in the guidance Appendix E SKR 2008-03-06 10:54
- random effect, fix effect in the guidance Appendix E d_labes 2008-02-07 10:14
- random effect, fix effect in the guidance Appendix E LS 2008-02-06 17:58
- random effect, fix effect in the guidance Appendix E d_labes 2008-02-06 13:34