Bioequivalence and Bioavailability Forum

Hi John,

these sample sizes are for ABE; Barbara wrote above „As shown in Table I, the number of study subjects needed to show BE increases dramatically for HV drugs.”

CV%  GMR  Davit sampleN.TOST  EFG
30  1.00    18      16         16
    1.05    20      20         20
    1.10    36      34         34
45  1.00    34      34         34
    1.05    42      40         40
    1.10    72      72         72
60  1.00    56      54         54
    1.05    66      66         66
    1.10   118     118        118
75  1.00    80      78         78
    1.05    96      96         96
    1.10   172     170        170

In PowerTOST I got identical sample sizes with the exact method (Owen’s Q), the noncentral t-distribution, and the shifted t-distribution. Same sample sizes like PowerTOST’s in ElMaestro’s EFG. No idea how Barbara got her’s.

This is not what me worries in the paper. Since Detlew coined “FDA’s desired consumer risk model” hocus-pocus, this is the term László uses ever since. Once I had lunch with him and Barbara and she wasn’t able to explain what it actually means. We guess it’s sort of black magic to make to inflation of the TIE in RSABE look better. Let’s see her example on p.922:

library(PowerTOST)
sigma.0  <- se2CV(0.25)    # FDA's switching standard deviation
theta.s  <- log(1.25)/0.25 # FDA's regulatory constant
n        <- 36
design   <- "2x3x3"
CVwR     <- 0.30
sigma.wR <- CV2se(CVwR)
theta2   <- scABEL(CV=CVwR, regulator="FDA")[["upper"]]          # upper implied limit
TIE.1    <- power.RSABE(CV=CVwR, theta0=theta2, n=n, design=design,
                        details=FALSE, nsims=1e6)
theta2   <- ifelse(CVwR <= sigma.0, 1.25, exp(theta.s*sigma.wR)) # the hat-trick!
TIE.2    <- power.RSABE(CV=CVwR, theta0=theta2, n=n, design=design,
                        details=FALSE, nsims=1e6)
cat("TIE at the implied limits           :", TIE.1,
    "\nTIE of 'desired consumer risk model':", TIE.2, "\n")

TIE at the implied limits           : 0.132333
TIE of 'desired consumer risk model': 0.046205

She reported 0.046434. Hocus-pocus – the rabbit is back in the hat. Strong desires can move mountains.

See also:
Muñoz J, Alcaide D, Ocaña J. Consumer's risk in the EMA and FDA regulatory approaches for bioequivalence in highly variable drugs. Stat Med. 2016;35(12):1933–43. doi 10.1002/sim.6834