Bioequivalence and Bioavailability Forum

Hi MMW,

❝ But it was found that around one-third of the study population did not turn up for 72.00 hours ambulatory sample.

Shit happens. Since AUC₇₂ is a primary PK metric consider hospitalizing subjects in the future. By opting for ambulatory sampling you saved some rupees but risked to substantially loose power.

❝ Is their any impact on calculation of AUC due to number of missed sample? Could these subjects be excluded from statistical analysis? If yes, on what basis we exclude these subjects?

You should have asked yourself these questions before starting the study. It is good practice to expect the unexpected and state a bail-out procedure in the protocol. Whatever you do post hoc might smell fishy.

❝ However, this was not mentioned anywhere in guideline regarding exclusion of such subjects in truncated studies?

Laking statements in guidelines are never an excuse for own judg­ments. Since C_max likely is more variable than AUC, it might that you even pass BE after excluding subjects with missing AUC₇₂ data. But one third is an awful lot…

Not sure whether presenting BE of AUC_t helps. If half lives were really long, maybe. Otherwise you end up with apples-and-oranges statistics.

In my protocols I state to use an estimated value anyway. This not only helps to correct for deviations from scheduled sampling times, but with ‘missings’ as well. In Phoe­nix/WinNonlin you could opt for a partial AUC_0–72. In order to do so, you need a reliable esti­mate of λ_z (at least three data points after t_max).