## How would you implement it? [BE/BA News]

Hi Helmut and all,

I was a little afraid of this. Thanks a lot for posting.

I am confused. I can see the point in regulating the matter, but I feel there is a lot that's left to be answered.

But let me ask all of you.

Question 1

Do you read this as: You need to be comparable (20% diff) for the median

Question 2:

Whether we like it or not, we have to find a way forward. And this has a lot of degrees of freedom. In a nonparametric universe where we try to resolve it There could be all sorts of debate re. Hodges-Lehman, Kruskal-Wallis, Wilcoxon test, confidence levels, bootstrapping, pairing and what not.

So, kindly allow me to throw this on the table:

Imagine we have these Tmax levels for T and R in a BE trial, units could be hours.

Let us implement something that has the look and feel of a test along the lines of what regulators want.

I am getting a CI of 1.999929-2.500036 (2 to 2.5).

We can compare this with

The test fails. Would that be a way to go?

No? then how about:

I am getting 0.47-0.92. Not within 0.8 to 1.25, test fails.

Shoot me.

How would you prefer to implement the comparability exercise for Tmax? (I am not so much interested in your thoughts on alpha/confidence level, exact T or F, etc. I am mainly interested in a way to make the comparison itself, so please make me happy and focus on that ).

Mind you, the data above might be paired .... or it might not, depends on whether it was from an XO or not. This add complexity, all depending on the implementation.

And, question 3, if the comparability thing also applies to range, how to implement that?

And question 4, sample size calculation is going to get messy for these products, if we have to factor in comparability of Tmax at the 20% level. I am not outright saying I have a bad taste in my mouse, but I am leaning towards thinking this could easy translate into a complete showstopper for sponsors developing the products. What's your gut feeling?

At the end of the day answers to Q1-Q4 above hinge not only on what you think is the right thing to do; of equal importance is what you think regulators will accept.

I was a little afraid of this. Thanks a lot for posting.

❝ Comparable median (≤ 20% difference) and range for T_{max}

I am confused. I can see the point in regulating the matter, but I feel there is a lot that's left to be answered.

But let me ask all of you.

Question 1

Do you read this as: You need to be comparable (20% diff) for the median

**AND**for the range? (i.e. is there also a 20% difference requirement for the range???)❝ Calculating the ratio of values is a questionable procedure.

Question 2:

Whether we like it or not, we have to find a way forward. And this has a lot of degrees of freedom. In a nonparametric universe where we try to resolve it There could be all sorts of debate re. Hodges-Lehman, Kruskal-Wallis, Wilcoxon test, confidence levels, bootstrapping, pairing and what not.

So, kindly allow me to throw this on the table:

Imagine we have these Tmax levels for T and R in a BE trial, units could be hours.

`Tmax.T=c(2.0, 2.5, 2.75, 2.5, 2.0, 2.5, 1.5, 2.0)`

Tmax.R=c(4.0, 3.0, 3.5, 3.75, 1.5, 3.5, 5.5, 4.5)

Let us implement something that has the look and feel of a test along the lines of what regulators want.

`Test1=wilcox.test(Tmax.T, alt ="two.sided", conf.int = T, correct=T, conf.level=.90)`

Test1$conf.int;

I am getting a CI of 1.999929-2.500036 (2 to 2.5).

We can compare this with

`median(Tmax.R)*c(0.8, 1.2)`

The test fails. Would that be a way to go?

No? then how about:

`Test2=wilcox.test(Tmax.T/Tmax.R, alt ="two.sided", conf.int = T, correct=T, conf.level=.90)`

Test2

Test2$conf.int;

I am getting 0.47-0.92. Not within 0.8 to 1.25, test fails.

Shoot me.

How would you prefer to implement the comparability exercise for Tmax? (I am not so much interested in your thoughts on alpha/confidence level, exact T or F, etc. I am mainly interested in a way to make the comparison itself, so please make me happy and focus on that ).

Mind you, the data above might be paired .... or it might not, depends on whether it was from an XO or not. This add complexity, all depending on the implementation.

And, question 3, if the comparability thing also applies to range, how to implement that?

And question 4, sample size calculation is going to get messy for these products, if we have to factor in comparability of Tmax at the 20% level. I am not outright saying I have a bad taste in my mouse, but I am leaning towards thinking this could easy translate into a complete showstopper for sponsors developing the products. What's your gut feeling?

At the end of the day answers to Q1-Q4 above hinge not only on what you think is the right thing to do; of equal importance is what you think regulators will accept.

—

Pass or fail!

ElMaestro

Pass or fail!

ElMaestro

### Complete thread:

- EMA: New product-specific guidances Helmut 2022-04-08 15:17
- How would you implement it?ElMaestro 2022-04-09 11:45
- Confuse a Cat Inc. Helmut 2022-04-09 18:40
- Confuse a Cat Inc. ElMaestro 2022-04-09 21:47
- Confuse a Cat Inc. Ohlbe 2022-04-11 11:29
- Confuse a Cat Inc. Helmut 2022-04-11 13:59

- So many questions, so few answers Helmut 2022-04-11 13:03
- Preliminary simulations Helmut 2022-04-30 14:59
- Preliminary simulations ElMaestro 2022-04-30 19:10
- Preliminary simulations Helmut 2022-05-01 15:56
- Revisions of the PSGLs final Helmut 2023-06-23 13:29
- Revisions of the PSGLs final dshah 2023-06-28 14:43
- EMA: No problems with many sampling time points… Helmut 2023-06-28 15:59
- New simulations & some desultory thoughts Helmut 2023-06-29 11:34
- SCNR. A heretic alternative. Helmut 2023-06-30 11:50

- Revisions of the PSGLs final dshah 2023-06-28 14:43

- Preliminary simulations ElMaestro 2022-04-30 19:10
- Simulated distributions Helmut 2022-05-02 13:43

- Confuse a Cat Inc. Ohlbe 2022-04-11 11:29

- Confuse a Cat Inc. ElMaestro 2022-04-09 21:47

- Confuse a Cat Inc. Helmut 2022-04-09 18:40

- How would you implement it?ElMaestro 2022-04-09 11:45