Bioequivalence and Bioavailability Forum

Hi Wisboy,

❝ ❝ OK, this is one of the often quoted ‘rules of thumb’ which have no statistical background. If it worked in your experience, you have been lucky.

❝ Please explain what you mean by "lucky"? In your experience do you find this not to be true more times than not?

OK, it is quite natural that between-subject variability is larger than with-subject variability (how much larger?). That’s the main reason we opt for cross-over designs. By “lucky” I meant that the “rule of thumb” might be misleading in some cases. If you base your sample size on a fixed ratio between/within you might overpower your Xover study (you pass BE – but waste money) or fail (if the true ratio is lower than assumed).

❝ I will have to take a look at this. R² = 0.5 is not very good. I have worked on well over 500 BE type studies so I have a lot of data.

Hey, that would be interesting. Go for it!

Amazingly last year I reviewed a manuscript submitted to the International Journal of Clinical Pharmacology and Therapeutics. Based on the (univocal) reviewers’ recommendations the editor did not accept the paper for publication. The authors had the balls to submit it to another journal (bad practice) and succeeded…

Ramírez E, Abraira V, Guerra P, Borobia AM, Duque B, López JL, Mosquera B, Lubomirov R, Carcas AJ, and J Frías. A Preliminary Model to Avoid the Overestimation of Sample Size in Bioequivalence Studies. Drug Res. 2013;63(2):98-103. doi:10.1055/s-0032-1333296.

I leave it to you to find out why I consider it to be crap.

Actually I fail to see any underlying physiological processes which would support a dependency of within- and between-subject variability. Imagine the extremes:

• Complete absorption, no metabolization
  Concentration primarily is linked to the volume(s) of distribution, which itself might be linked to anthropometric variables like body weight, surface area, or sex. Clearance is not an issue in BE (might be linked to age and sex).
  
• Incomplete absorption, first-pass and/or presystemic metabolization, genetic polymorphism
  All of the above + both variable absorption/elimination.

Even if you succeed in deriving a model describing intra/inter across different drugs* I expect the confidence intervals of its parameters to be so wide that I seriously doubt its applicability in practice.

❝ ❝ Not necessarily the drug, but it might be the formulation as well. No very uncommon for PPIs.

❝

❝ OK - I guess I should have been more specific and said treatment regimen - to me this means the drug, formulation, whatever else goes along with it. IMO - if the within > between, you have no control over exposure in any given patient and this is bad. Thus, big problems and more than likely, a dead "treatment regimen".

Maybe. Or simply a lousy formulation.

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• Or even worse: Across different formulations within the same drug. For example diclofenac has a very low CV_intra if administered as a solution (<10%), and increases in the order effervescent tablet → oral dispersion → suppositories → IR → enteric coated → topical. I haven’t checked my data, but assume that CV_inter does not increase to the same extent.