HVD sample size [Study As­sess­ment]

posted by d_labes  – Berlin, Germany, 2015-10-09 15:19 (3414 d 17:32 ago) – Posting: # 15543
Views: 7,416

Dear Anand,

❝ Response: Two Crossover design: For considering Cmax ISCV 43.13 sample size required 62 subjects, additionally considered 6 subjects for drop-out & withdrawal. Total 68 subjects.


❝ Partial Replicate: 24 subjects


your recommended sample size is based on the assumption of GMR=1 and using conventional ABE as BE decision.
IMHO GMR =1 is not a reasonable choice even if the pilot study came out with a ratio ~1. Highly variable drugs have the feature that the point estimate "jumps" around if study has small sample size.
Therefore I suggest to plan the pivotal study at least with a GMR = 0.95 or even better as the two Laszlo's*) suggest for HVD's with GMR = 0.9.
With the latter one obtains:
library(PowerTOST)
sampleN.TOST(CV=0.4313, design="2x2x2", theta0=0.9)

+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  2x2 crossover
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins        = 0.8 ... 1.25
Null (true) ratio = 0.9,  CV = 0.4313

Sample size (total)
 n     power
154   0.801296


This sample size may be prohibitive high.
Therefore I suggest to go with scaled ABE. Using the EMA recommended method (assuming that you aim for an European submission), i.e. widening of the BE acceptance range, and planning for the partial replicate design one obtains:
sampleN.scABEL(CV=0.4313, design="2x3x3", theta0=0.9)

+++++++++++ scaled (widened) ABEL +++++++++++
            Sample size estimation
---------------------------------------------
Study design:  2x3x3 (partial replicate)
log-transformed data (multiplicative model)
1e+05 studies for each step simulated.

alpha  = 0.05, target power = 0.8
CVw(T) = 0.4313; CVw(R) = 0.4313
Null (true) ratio = 0.9
ABE limits / PE constraints = 0.8 ... 1.25
Regulatory settings: EMA
- CVswitch =  0.3, cap on scABEL if CVw(R) > 0.5
- Regulatory constant = 0.76

Sample size search
 n     power
36   0.7671
39   0.7979
42   0.8228


Since the EMA doesn't allow widening in case of evaluation of AUC and in the light of the astonishing high variability of AUC(0-inf) with additionally a GMR ~0.9 it may be that this PK metric will drive your sample size estimation:
sampleN.TOST(CV=0.3365, design="2x3x3", theta0=0.9)

+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  partial replicate (2x3x3)
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins        = 0.8 ... 1.25
Null (true) ratio = 0.9,  CV = 0.3365

Sample size (total)
 n     power
75   0.812282



*) Laszlo Tothfalusi and Laszlo Endrenyi
"Sample Sizes for Designing Bioequivalence Studies for Highly Variable Drugs"
J. Pharm. Pharmaceut. Sci. (www.cspsCanada.org) 15(1) 73 - 84, 2011

Regards,

Detlew

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