Bioequivalence and Bioavailability Forum

❝ The results of the BE study (2002) presented in my last message are from this link: […] (The FDA report presented many deficiencies about this study!)

• 100% Caucasians… (“ This guidance recommends that in vivo BE studies be conducted in individuals representative of the general population, taking into account age, sex, and race.”) Wasn’t even commented.
  
• Two subjects dropped out due to non drug-related AEs (on days 72 and 83, respectively). They were excluded by the company (last 6 or 7 samples missing), but FDA requested statistical analysis of AUC and C_max “[…] since samples were collected long enough to properly characterize the absorption phase.”
  The company replied that these subjects were dropped from the evaluation due to SAEs requiring hospitalization and more than 5 consecutive missing samples would result in an inaccurate and biased assessment. Not very clever:
  “The DBE^* calculated AUC_0-1656 and AUC_0-1824 from the reference mean plasma profile which were 85% and 81% of the AUC_0-2856 from the reference mean plasma profile. […] these two subjects will provide accurate values for C_max and therefore the inclusion of these subjects is essential for the statistical analysis of the C_max value. Thus, based on our calculations, the DBE does not believe the inclusion of those subjects would result in an inaccurate and biased assessment of C_max (definitely) and AUC_(0-t), AUC_(0-inf) (possibly).”.
  
• Page 12: “Were there statistically significant sequence or period effects? If so, did these affect the integrity of the study? The reviewer has not run SAS ANOVA pending the firm’s response to the deficiencies.”
  Whilst the questions likely follow FDA’s standard template the reviewer’s answer is funny – this was a parallel design!
  
• Original data set (n=122, n_T 62, n_R 60)
  AUC_t 87–102%, PE 96% (geometric mean of CI 94%)
  AUC_∞ 94–106%, PE 100%
  C_max 82–118%, PE 108% (98%)
  RSEM AUC (Which one? Likely AUC_t) 0.244
  RSEM C_max 0.592
  
• Complete data set (n=124, n_T 62, n_R 62)
  AUC_t 87–101%, PE NA (94%)
  AUC_∞ 92–105%, PE NA (98%)
  C_max 80–115%, PE NA (96%)

• Don’t exclude subjects following stupid SOPs. Luckily the samples were analyzed.
  
• I still think that the original analysis of C_max sucks. Though the PE was reported with 108% the CI is symmetrical (-18%, +18%) around 100%. Smells of Westlake. Maybe the classical interval was outside 80–125% (not reported!) and Barbara didn’t notice it? Since all CIs of the complete data set are not symmetrical around 100% I would trust them more. For C_max we get:
  100*CVfromCI(lower=0.80, upper=1.15, n=124, design="parallel")
[1] 67.08022 (CV_total 67.1%)
  CV2se(0.6708022)
[1] 0.6095463 (RMSE)
  Your samples size would be terrible.
  
• I’m wondering whether the company followed the guidance’s recommendations:
  “For parallel designs […] equal variances should not be assumed.”
  CV_T was 85.8% and CV_R 58.7%. The conventional t-test is liberal; was really Welch’s test applied? Though the t-test is rather robust against violation of variance homogeneity (unequal group sizes are more critical), a lower CL of 80% would ring my alarm bells.

• DBE: Division of Bioequivalence, Office of Generic Drugs