This function performs the Sample size estimation for the BE decision via FDA method for NTIDs based on simulations. The study design is the full replicate design 2x2x4 or the 3-period replicate design with sequeences TRT|RTR.
sampleN.NTIDFDA(alpha = 0.05, targetpower = 0.8, theta0, theta1, theta2, CV,
design=c("2x2x4", "2x2x3"), nsims = 1e+05, nstart, imax=100,
print = TRUE, details = TRUE, setseed = TRUE)Type I error probability. Per convention mostly set to 0.05.
Power to achieve at least. Must be >0 and <1. Typical values are 0.8 or 0.9.
‘True’ or assumed bioequivalence ratio. Attention! Defaults here to 0.975 if not given explicitly. The value was chosen nearer to 1 because the potency (contents) settings for NTIDs are tightened by the FDA.
Conventional lower ABE limit to be applied in the FDA procedure. Defaults to 0.8 if not given explicitly.
Conventional upper ABE limit to be applied in the FDA procedure. Defaults to 1.25 if not given explicitly.
Coefficient(s) of variation as ratio.
If length(CV) = 1 the same CV is assumed for Test and Reference.
If length(CV) = 2 the CV for Test must be given in CV[1] and for
Reference in CV[2].
Design of the study to be planned.
2x2x4 is the full replicate design with 2 sequences and 4 periods.
2x2x3 is the 3-period replicate design with sequences TRT|RTR.
Defaults to design="2x2x4".
Number of simulations to be performed to obtain the empirical power. Defaults to 100 000 = 1e+5.
Set this to a start value for the sample size if a previous run failed. May be missing.
Maximum number of steps in sample size search. Defaults to 100.
If TRUE (default) the function prints its results.
If FALSE only the resulting dataframe will be returned.
If set to TRUE, the default, the steps during sample size search are shown.
Moreover the details of the method settings are printed.
Simulations are dependent on the starting point of the (pseudo) random number
generator. To avoid differences in power values for different runs a
set.seed(123456) is issued if setseed=TRUE, the default.
Returns a data.frame with the input settings and sample size results. The "Sample size" column contains the total sample size. The "nlast" column contains the last n value. May be useful for re-starting.
For some input constellations the sample size search may be very time
consuming and will eventually also fail since the start values chosen may
not really reasonable for them. This applies especially for theta0 values
near to the implied scaled (tightened/widened) ABE limits according to
exp(+-1.053605*swR).
In case of a failed sample size search you may restart with setting the argument
nstart.
In case of theta0 values outside the implied scaled (tightened/widened) ABE limits
no sample size estimation is possible and the function throws an error
(f.i. CV=0.04, theta0=0.95).
The linearized scaled ABE criterion is calculated according to the SAS code given in the FDA Warfarine guidance. For deciding BE the study must pass that criterion, the conventional ABE test and additional the test that the ratio of sWT/sWR is <= 2.5. The simulations are done via the distributional properties of the statistical quantities necessary for deciding BE based on these method. Details can be found in a document "Implementation_scaledABE_sims" located in the doc subdirectory of the package.
FDA Draft Guidance on Warfarin Sodium Recommended Dec 2012. download
Yu LX et al. Novel bioequivalence approach for narrow therapeutic index drugs Clin Pharmacol Ther. 2015;97(3):286--91. 10.1002/cpt.28
Jiang W et al. A Bioequivalence Approach for Generic Narrow Therapeutic Index Drugs: Evaluation of the Reference-Scaled Approach and Variability Comparison Criterion AAPS J. 2015;17(4):891--901. 10.1208/s12248-015-9753-5
power.NTIDFDA
and power.HVNTID, sampleN.HVNTID for NTIDs with
high variability
# NOT RUN {
sampleN.NTIDFDA(CV=0.04,theta0=0.975)
# should give
# n=54 with an (empirical) power of 0.809590
#
# Test formulation with lower variability
sampleN.NTIDFDA(CV=c(0.04,0.06),theta0=0.975)
# should give
# n=20 with an (empirical) power of 0.0.814610
#
# alternative 3-period design
sampleN.NTIDFDA(CV=0.04,theta0=0.975, design="2x2x3")
# should give
# n=86 with power = 0.80364
# }
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