Bioequivalence and Bioavailability Forum

Dear all,

the story continues.

• Draft (2.2.4 Bioequivalence Criteria, page 17)
  For the majority of drug products, the PK parameters to demonstrate BE include C_max and AUC_(0–t).
  For drugs with a long elimination half-life, AUC_(0–72h) may be used in place of AUC_(0–t) (see Section 2.1.8.2). For drugs where it is clinically relevant to assess the early exposure or early onset of action, an additional PK parameter, pAUC, may be used to establish BE (see Section 2.1.8.3).
  The 90% confidence interval for the geometric mean ratio of these PK parameters used to establish BE should lie within a range of 80.00 – 125.00%.
  
• Final (page 13)
  For the majority of drug products, the PK parameters to demonstrate BE include C_max and AUC_(0–t) in single-dose studies and C_maxSS and AUC_(0–tauSS) in multiple-dose studies.
  For drugs with a long elimination half-life, AUC_(0–72h) may be used as AUC_(0–t) (see Section 2.1.8.2).
  The 90% confidence interval for the geometric mean ratio of these PK parameters used to establish BE should lie within a range of 80.00 – 125.00%.
  For drugs where it is clinically relevant to assess the early exposure or early onset of action, an additional PK parameter should be used to establish BE (see Section 2.1.8.3).

Reordered and expanded for multiple dose studies.
Why the weird phrase »AUC_(0–72h) may be used as AUC_(0–t)« and not keep what was stated in the draft or simply “AUC_(0–72h) may be used instead of AUC_(0–t)”?
Contrary to the guidances of the FDA and Health Canada, nothing is stated about rounding of the confidence interval. Based on a clinically relevant difference \(\small{\Delta=20\%}\) we get the BE-limits in the multiplicative model by $$\small{\left\{\theta_1,\theta_2\right\}=\left\{100\left(1-\Delta\right),100\left(1-\Delta\right)^{-1}\right\}=\left\{80\%,125\%\right\}}$$ These limits are exact, i.e., a study with a CI of 79.995 –125.005% would fail. Since the limits are stated as 80.00 – 125.00%, does that imply that we have to round to two decimal places? Then the same study would pass* and – slightly – inflate the Type I Error.

• Draft (2.2.5.1 Multiple Comparator Products, page 17)
  It may be necessary to demonstrate BE between a test product and multiple comparator products to meet requirements from multiple jurisdictions. In such case, including comparator products from different regions in one trial is acceptable to streamline the BE demonstration by conducting one single higher-order crossover BE study with multiple comparator products.
  Although there are multiple comparator products tested, multiplicity correction, i.e., alpha adjustment, is not needed because comparator products are considered independent and region-specific. Decisions will be made independently about a test product relative to a single comparator product within a single jurisdiction. It is preferred for the statistical analysis to only test two at a time and not all at once, making pairwise comparison within the analysis.
  
• Final (page 13–14)
  It may be necessary to demonstrate BE between a test product and multiple comparator products to meet requirements from multiple jurisdictions. Including comparator products from different regions in one trial is acceptable to streamline the BE demonstration by conducting one single higher-order crossover BE study with multiple comparator products.
  In studies with multiple comparator products, multiplicity correction, i.e., alpha adjustment, is not needed because comparator products are considered independent and region-specific. Decisions will be made independently about a test product relative to a single comparator product within a single jurisdiction. It is preferred for the statistical analysis to only test two at a time and not all at once, making pairwise comparison within the analysis.
  

Why on earth was the important last sentence removed‽ Without, I expect that applicants will use of the crappy ‘All at Once’ approach (i.e., analysis of pooled data).^1,2 I got many studies with the wrong method on my desk, although the EMA stated already in its 2010 guideline:

In studies with more than two treatment arms (e.g. a three period study including two references, one from EU and another from USA […]), the analysis for each comparison should be conducted excluding the data from the treatments that are not relevant for the comparison in question.

Very similar recently the FDA:^3,4

In BE studies with more than two reference treatment arms (e.g., a three-period study including two references, one from the European Union (EU) and another from the United States […]), the BE determination should be based on the comparison between the relevant test and reference products, using only the data from those products. The BE analysis for this comparison should be conducted excluding the data from the non-relevant treatment(s) — for example, in a BE study with a T product, an EU reference product, and a U.S. reference product, the comparison of the T product to the U.S. reference product should be based on an analysis excluding the data from the EU reference.

For details see this article, a presentation by David Brown (MHRA),⁵ and the Q&A.⁶

• Draft (3.1 Endogenous Compounds, page 17–18)
  Alternatively, the need for baseline correction may be avoided by enrolling study subjects with low or no production of the endogenous compounds.
  
• Final (page 14–15)
  When considered necessary to ensure adequate separation of treatment-induced concentrations over baseline, a high dose may be administered in BE studies of endogenous compounds if the dose is well tolerated and dose proportionality in PK is maintained. Alternatively, the need for baseline correction may be avoided by enrolling study subjects with low or no production of the en­do­ge­nous compounds.

Only slight rewording in all but the last paragraph.

• Draft (3.2.3 Oral Suspensions, page 20)
  For new intended label use/instructions (not included in the comparator product labelling), the test product should be administered according to its intended labelling and compared with the comparator product administered as per its labelling.
  
• Final (page 16)
  For new intended label use/instructions, e.g., oral suspensions as an extension to another orally administered IR drug product, BE studies may be conducted to determine whether the oral sus­pension is BE to the comparator product. In this scenario, the oral sus­pension product should be administered according to its intended labelling and compared with the comparator product ad­mi­ni­stered as per its labelling

To be continued.

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• By correct (IEEE 754) rounding. Phoenix WinNonlin and bloody Excel use commercial rounding, which is wrong, i.e. 125.005 → 125.01.
  c.round <- function(x, y) { # commercial rounding (wrong)
  sign(x) * trunc(abs(x) * 10^y + 0.5) / 10^y
}
limits <- c(80, 125)
exact  <- c(79.995, 125.005)
t      <- sprintf("exact CI: %.3f – %.3f\n", exact[1], exact[2])
HC     <- sprintf("%.1f", exact)
HC.c   <- sprintf("%.1f", c.round(exact, 1))
FDA    <- sprintf("%.2f", exact)
FDA.c  <- sprintf("%.2f", c.round(exact, 2))
res    <- data.frame(rounding = c("none", rep(c("IEEE 754", "commercial"), 2)),
                     result = c("", rep("HC", 2), rep("FDA", 2)),
                     L = c(sprintf("%.3f", exact[1]),
                           HC[1], HC.c[1], FDA[1], FDA.c[1]),
                     U = c(sprintf("%.3f", exact[2]),
                           HC[2], HC.c[2], FDA[2], FDA.c[2]),
                     BE = "fail")
for (j in 1:nrow(res)) {
  if (as.numeric(res$L[j]) >= limits[1] &
      as.numeric(res$U[j]) <= limits[2]) res$BE[j] <- "pass"
}
cat(t); print(res, row.names = FALSE, right = FALSE)
exact CI: 79.995 – 125.005
 rounding   result L      U       BE 
 none              79.995 125.005 fail
 IEEE 754   HC     80.0   125.0   pass
 commercial HC     80.0   125.0   pass
 IEEE 754   FDA    80.00  125.00  pass
 commercial FDA    80.00  125.01  fail

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1. Schuirmann DJ. Two at a Time? Or All at Once? International Biometric Society, Eastern North American Region, Spring Meeting. Pittsburgh, PA. March 28–31, 2004. Abstract.
   
2. D’Angelo P. Testing for Bioequivalence in Higher‐Order Crossover Designs: Two‐at‐a‐Time Principle Versus Pooled ANOVA. 2^nd Con­fe­rence of the Global Bioequivalence Harmonisation Initiative. Rockville, MD. 15–16 September, 2016.
   
3. FDA (CDER). Draft Guidance for Industry. Statistical Approaches to Establishing Bioequivalence. Silver Spring. December 2022. Re­vi­si­on 1. Download.
   
4. FDA (CDER, OGD). Navigating the First ICH Generic Drug Draft Guideline “M13A Bioequivalence for Immediate-Release Solid Oral Dosage Forms”. SBIA Webinar. May 2, 2023. Online.
   
5. Brown D. Presentation at the 3^rd EGA Symposium on Bioequivalence. London. June 2010. Slides.
   
6. European Generic Medicines Association. Revised EMA Bioequivalence Guideline. Questions & Answers. Brussels. 2010. Online.