Bioequivalence and Bioavailability Forum

Dear Astea et al.,

first of all I fully agree with Mittyri. Instead of “gut feeling” I prefer common sense.

    I try not to think with my gut.
If I’m serious about understanding the world,
thinking with anything besides my brain, as tempting as that might be,
is likely to get me into trouble.
Carl Sagan. The Demon-Haunted World: Science as a Candle in the Dark; Ch. 11: The Dragon in My Garage (1995)

Before we apply any statistical method we have to understand the data generating process. In our field the two most forgotten prerequisites are: Knowing the drug (PK/PD properties) and its formulation (biopharmaceutics). Having information about the clinical setting and bioanalytics is useful as well. Some examples (apart form the ones already given by Mittyri) where pooling is not a good idea:

• Mixing studies in fasting and fed state. In the latter case the CV generally (but not always) is higher than in the former.
  
• Whilst pooling CVs of IR-formulations (say tablets and capsules) generally is not problematic, I would be cautious with MR-formulations of different types (say pellets/capsules and monolithic tablets).
  
• Highly metabolized drugs at a dosage near the limit of saturation. If the GMR is not very close to 1, the CV might be inflated.
  
• Including studies with LC/MS-MS methods at its infancy (protein precipitation without stable-isotope internal standardization). In the early 2000s studies failed because they were planned based on CVs from earlier studies obtained with e.g., fluorescence detection. The matrix effect hit (CV went through the ceiling) and studies were underpowered.

Sample size estimation (as a part of designing the study) should be done in close collaboration of the statistician with the clinical expert(s). Nowadays “push-the-button” specialists are all too common. Obtaining a basic knowledge in PK/PD/biopharmaceutics is a piece of cake for statisticians. Much more difficult for physicians/pharmacists/… (plug in whatever you like) to understand statistics.