PowerTOST (version 1.3-5)

sampleN.NTIDFDA: Sample size estimation for BE decision via FDA method for narrow therapeutic index drugs (NTID's)

Description

This function performs the Sample size estimation for the BE decision via FDA method for NTID's based on simulations. The study design is the full replicate design 2x2x4 or the 3-period replicate design with sequeences TRT|RTR.

Usage

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)

Arguments

alpha

Type I error probability. Per convention mostly set to 0.05.

targetpower

Power to achieve at least. Must be >0 and

theta0

'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 NTID's are tightened by the FDA.

theta1

Conventional lower ABE limit to be applied in the FDA procedure. Defaults to 0.8 if not given explicitly.

theta2

Conventional upper ABE limit to be applied in the FDA procedure. Defaults to 1.25 if not given explicitly.

CV

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

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".

nsims

Number of simulations to be performed to obtain the empirical power. Defaults to 100 000 = 1e+5.

nstart

Set this to a start value for the sample size if a previous run failed. May be missing.

imax

Maximum number of steps in sample size search. Defaults to 100.

print

If TRUE (default) the function prints its results. If FALSE only the resulting dataframe will be returned.

details

If set to TRUE, the default, the steps during sample size search are shown. Moreover the details of the method settings are printed.

setseed

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.

Value

• Returns a data.frame with the input 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.

Warning

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).

Details

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

References

FDA "Draft Guidance on Warfarin Sodium" Recommended Dec 2012 http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM201283.pdf LX Yu et al. "Novel bioequivalence approach for narrow therapeutic index drugs" Clin Pharm & Ther Vol 97, Issue 3, pages 286-291, March 2015 First published online: 15 DEC 2014 W Jiang et al. "A Bioequivalence Approach for Generic Narrow Therapeutic Index Drugs: Evaluation of the Reference-Scaled Approach and Variability Comparison Criterion" The AAPS Journal, July 2015, Volume 17, Issue 4, pp 891-901 First published online: 04 April 2015

See Also

power.NTIDFDA and power.HVNTID, sampleN.HVNTID for NTIDs with high variability

Examples

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