## Reference-scaling: Don’t use FARTSSIE! [Power / Sample Size]

❝ What BE limits should be taken into consideration while estimating sample size for replicate design studies for USFDA & EMA.

If you want to go with reference-scaling, none! The limits depend on the CV

_{wR}and are estimated in the actual study. Hence, you need simulations, where your assumed CV

_{wR}is the

*average*. Either use the tables provided by the two Lászlós* or package

`PowerTOST`

for **R**. The software is open source and comes free of costs.

❝ Should it be 80-125% ?

No (see above). Only if you don’t want reference-scaling (

*i.e.*, conventional ABE). Actually reference-scaling was introduced to avoid the extreme sample sizes required for ABE.

❝ We normally use FARTSSIE

FARTSSIE cannot perform the necessary simulations and therefore, is not suitable for

*any*of the reference-scaling methods.

❝ For a product with 51% ISCV (from a completed partial replicate study UKMHRA) by using FARTSSIE we arrived at different sample size for EMA

❝

❝ - Sample size estimated = 27 (80% Power, 95-105% T/R, Method C1, BE Limits 69.84 to 143.19%)

❝ - Sample size estimated = 76 (80% Power, 95-105% T/R, No reference Scaled BE Limits-80-125%)

*Do not*assume a T/R of 95% for HVDP(s). The two Lászlós recommend a 10% difference and for good reasons. Therefore, 90% is the default in`PowerTOST`

’s reference-scaling functions.

- If ever possible avoid the partial replicate design. Though the evaluation works for the EMA’s methods, sometimes no convergence is achieved for the FDA’s mixed effects model (if CV
_{wR}<30%) – independent from the software. Study done, no result, you are fired.

Better to opt for full replicate 2-sequence designs: 4-periods (TRTR|RTRT) or – if you are afraid of dropouts and/or want to avoid large sampling volumes – 3-periods (TRT|RTR). In the latter one you need at least twelve eligible subjects in sequence RTR according to the EMA’s Q&A-document (not relevant in practice).

**R**and downloading

`PowerTOST`

, start the R-console, and type `library(PowerTOST)`

. If you want to make yourself familiar with `PowerTOST`

, type `help(package=PowerTOST)`

.Try these examples, where

`"2x2x4"`

denotes the 4-perod full replicate, `"2x2x3"`

the 3-period full replicate, and `"2x3x3"`

the 3-sequence 3-period (partial) replicate.- The EMA’s ABEL

`sampleN.scABEL(CV=0.51, design="2x2x4")`

sampleN.scABEL(CV=0.51, design="2x2x3")

sampleN.scABEL(CV=0.51, design="2x3x3")

- Health Canada’s ABEL

`sampleN.scABEL(CV=0.51, design="2x2x4", regulator="HC")`

sampleN.scABEL(CV=0.51, design="2x2x3", regulator="HC")

sampleN.scABEL(CV=0.51, design="2x3x3", regulator="HC")

- The FDA’s RSABE

`sampleN.RSABE(CV=0.51, design="2x2x4")`

sampleN.RSABE(CV=0.51, design="2x2x3")

sampleN.RSABE(CV=0.51, design="2x3x3")

_{wR}limit for scaling. On the other hand Health Canada’s ABEL sometimes require less subjects than the EMA’s ABEL because the upper cap is 57.38%. If your boss insist in a T/R of 95% add the argument

`theta0=0.95`

to the function calls but don’t blame me if the study fails. If you want 90% power instead of the default 80%, add the argument `targetpower=0.90`

.I suggest to perform a power analysis (recommended by ICH E9) assessing the influence of deviations from assumptions (lower/higher CV

_{wR}, T/R deviating more than expected from 100%, less eligible subjects due to dropouts). Try (with the default partial replicate):

`pa.scABE(CV=0.51, regulator="EMA")`

pa.scABE(CV=0.51, regulator="HC")

pa.scABE(CV=0.51, regulator="FDA")

_{wR}can be as high as ~97% until power drops to 70%, though the sample size is smaller (30) compared to the EMA’s and Health Canada’s (39). With the same sample size 39, the CV

_{wR}can rise to ~76% (Health Canada) and only to ~64% (EMA). This is a consequence of differing upper scaling caps.

- Endrényi L, Tóthfalusi L.
*Sample Sizes for Designing Bioequivalence Studies for Highly Variable Drugs.*J Pharm Pharmaceut Sci. 2011;15(1):73–84. free resource.

*Dif-tor heh smusma*🖖🏼 Довге життя Україна!

_{}

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

### Complete thread:

- Sample Size Estimation -Replicate design- BE limits cakhatri 2017-11-30 09:44 [Power / Sample Size]
- Reference-scaling: Don’t use FARTSSIE!Helmut 2017-11-30 10:58
- Reference-scaling: Don’t use FARTSSIE? Astea 2017-11-30 22:50
- Reference-scaling: Don’t use FARTSSIE! Helmut 2017-12-01 11:42
- Reference-scaling: USE PowerTOST Astea 2017-12-01 14:16
- Reference-scaling: USE PowerTOST cakhatri 2017-12-04 06:00
- Reference-scaling: USE PowerTOST Helmut 2017-12-04 15:07
- Reference-scaling: USE PowerTOST cakhatri 2017-12-05 05:33

- Reference-scaling: USE PowerTOST Helmut 2017-12-04 15:07
- Use PowerTOST d_labes 2017-12-06 09:52
- Use PowerTOST, not Endrényi L, Tóthfalusi L tables mittyri 2017-12-07 16:03
- Precision in Endrényi L, Tóthfalusi L tables d_labes 2017-12-07 18:21
- Precision of PowerTOST mittyri 2017-12-08 22:56
- Precision of PowerTOST Helmut 2017-12-09 17:00
- Precision of PowerTOST mittyri 2017-12-09 21:05
- Precision of PowerTOST Astea 2017-12-10 00:10
- Precision of PowerTOST Helmut 2017-12-10 20:27
- Precision of PowerTOST Astea 2017-12-10 21:13

- Precision of PowerTOST Helmut 2017-12-10 20:27

- Precision of PowerTOST Astea 2017-12-10 00:10

- Precision of PowerTOST mittyri 2017-12-09 21:05

- Precision of PowerTOST Helmut 2017-12-09 17:00

- Precision of PowerTOST mittyri 2017-12-08 22:56

- Precision in Endrényi L, Tóthfalusi L tables d_labes 2017-12-07 18:21

- Use PowerTOST, not Endrényi L, Tóthfalusi L tables mittyri 2017-12-07 16:03

- Reference-scaling: USE PowerTOST cakhatri 2017-12-04 06:00

- Reference-scaling: USE PowerTOST Astea 2017-12-01 14:16

- Reference-scaling: Don’t use FARTSSIE! Helmut 2017-12-01 11:42
- Reference-scaling: Don’t use FARTSSIE! pjs 2018-02-09 13:08
- Reference-scaling: Don’t use FARTSSIE! Helmut 2018-02-09 20:15

- Reference-scaling: Don’t use FARTSSIE? Astea 2017-11-30 22:50

- Reference-scaling: Don’t use FARTSSIE!Helmut 2017-11-30 10:58