Bioequivalence and Bioavailability Forum

Helmut
★★★

Vienna, Austria,
2020-10-18 13:09
(1514 d 06:20 ago)

Posting: # 22022
Views: 6,036

FARTSSIE v2.5 [Software]

Thread locked

Dear all,

up to v2.4 of 14 March 2019 FARTSSIE’s Bioequivalence, Replicate-sheet contained two boxes for reference-scaling. The sample size was wrong because no analytical solution for power exists and simulations are required instead.

In v2.5 of 13 October 2020 Dave deleted the boxes and suggests to install PowerTOST. He gives in two boxes the arguments for PowerTOST’s functions sampleN.scABEL() for Average Bioequivalence with Expanding Limts (EMA and many others, Health Canada) and sampleN.NTIDFDA() for the FDA’s reference-scaling for NTIDs.
However, in the former don’t use the argument regulator="FDA" as he suggests, since RSABE ≠ ABEL. Not only that the regulatory constants are different (≈0.8925742 vs 0.760), these are different approaches (upper limit of the linearized criterion ≤0 vs expansion of the BE limits).

library(PowerTOST) # show the regulatory conditions reg_const(regulator = "EMA") EMA regulatory settings - CVswitch = 0.3 - cap on scABEL if CVw(R) > 0.5 - regulatory constant = 0.76 - pe constraint applied reg_const(regulator = "HC") HC regulatory settings - CVswitch = 0.3 - cap on scABEL if CVw(R) > 0.57382 - regulatory constant = 0.76 - pe constraint applied reg_const(regulator = "FDA") FDA regulatory settings - CVswitch = 0.3 - no cap on scABEL - regulatory constant = 0.8925742 - pe constraint applied

Use the function sampleN.RSABE() instead. Examples with comments at the end.

Since in the survey 20% of participants reported to never update their software: Not a good idea.

library(PowerTOST) sampleN.scABEL(CV = 0.6, design = "2x2x4", regulator = "EMA") # correct +++++++++++ scaled (widened) ABEL +++++++++++ Sample size estimation (simulation based on ANOVA evaluation) --------------------------------------------- Study design: 2x2x4 (4 period full replicate) log-transformed data (multiplicative model) 1e+05 studies for each step simulated. alpha = 0.05, target power = 0.8 CVw(T) = 0.6; CVw(R) = 0.6 True ratio = 0.9 ABE limits / PE constraint = 0.8 ... 1.25 EMA regulatory settings - CVswitch = 0.3 - cap on scABEL if CVw(R) > 0.5 - regulatory constant = 0.76 - pe constraint applied Sample size search n power 30 0.7851 32 0.8101 sampleN.scABEL(CV = 0.6, design = "2x2x4", regulator = "HC") # correct +++++++++++ scaled (widened) ABEL +++++++++++ Sample size estimation (simulations based on intra-subject contrasts) ---------------------------------------------- Study design: 2x2x4 (full replicate) log-transformed data (multiplicative model) 1e+05 studies for each step simulated. alpha = 0.05, target power = 0.8 CVw(T) = 0.6; CVw(R) = 0.6 True ratio = 0.9 ABE limits / PE constraint = 0.8 ... 1.25 HC regulatory settings - CVswitch = 0.3 - cap on scABEL if CVw(R) > 0.57382 - regulatory constant = 0.76 - pe constraint applied Sample size search n power 24 0.7505 26 0.7851 28 0.8118 sampleN.scABEL(CV = 0.6, design = "2x2x4", regulator = "FDA") # wrong +++++++++++ scaled (widened) ABEL +++++++++++ Sample size estimation (simulations based on intra-subject contrasts) ---------------------------------------------- Study design: 2x2x4 (full replicate) log-transformed data (multiplicative model) 1e+05 studies for each step simulated. alpha = 0.05, target power = 0.8 CVw(T) = 0.6; CVw(R) = 0.6 True ratio = 0.9 ABE limits / PE constraint = 0.8 ... 1.25 FDA regulatory settings - CVswitch = 0.3 - no cap on scABEL - regulatory constant = 0.8925742 - pe constraint applied Sample size search n power 16 0.7017 18 0.7476 20 0.7813 22 0.8071 sampleN.RSABE(CV = 0.6, design = "2x2x4") # correct ++++++++ Reference scaled ABE crit. +++++++++ Sample size estimation --------------------------------------------- Study design: 2x2x4 (4 period full replicate) log-transformed data (multiplicative model) 1e+05 studies for each step simulated. alpha = 0.05, target power = 0.8 CVw(T) = 0.6; CVw(R) = 0.6 True ratio = 0.9 ABE limits / PE constraints = 0.8 ... 1.25 FDA regulatory settings - CVswitch = 0.3 - regulatory constant = 0.8925742 - pe constraint applied Sample size search n power 16 0.67580 18 0.72735 20 0.76531 22 0.79589 24 0.81947

—
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

ddubins
☆

Toronto,
2021-03-10 17:43
(1371 d 00:47 ago)

(edited on 2021-03-10 18:34)
@ Helmut
Posting: # 22256
Views: 4,831

FARTSSIE v2.7

Dear everyone,

I have updated FARTSSIE to version 2.7, and migrated it (finally) to github:

https://github.com/dndubins/FARTSSIE

It's been a while since I've posted to this forum (oh it has to be years now!) so I thought I would give you a bit of background on where FARTSSIE originated. When I was at Allied Research International Inc., Dr. Richard Moisan trained me as a PK scientist. He was a patient teacher, always with a cigarette in his mouth and a keen eye for science. He was a data purist really, and was passionate in the way he ran and interpreted Phase I and II trials. "If you don't love your job, then get the f**k out" was one of the many phrases he would repeat to us. And by the way, we did love our jobs in the department, especially working for Richard. He would tell us stories about his years at Roche, and about his PhD that took so long because he investigated the effects of aging on pharmacokinetics in rats. "I had to wait until the rats got old", he'd say. When HR left the building, he would smoke inside. He was a character!

One day Richard told me there was a talk he was supposed to give at SoCRA, the Society of Clinical Research Associates. He asked me if I could present in his place. "What would I talk about?" I asked him. I had just come up with a crude Excel spreadsheet to estimate sample size for a 2-way crossover BE trial, so he responded "how about sample size?" I took on the challenge, and adapted the spreadsheet for the talk, presenting it (at the time) as a free alternative to what was available. The talk was fun, and the spreadsheet was born. Richard was amenable to posting it as freeware, although when Cetero Research bought Allied, Murray Ducharme suggested selling it. No, I insisted, this needs to be a free tool, thinking about my students who needed a button to push for their problem sets.

As the regulations changed, along with my role leaving consulting work and teaching full time at UofT, I lost contact with my industry ties. So many good people - Yan Liu, our crazy smart biostatistician, for one. I struggled marginally successfully keeping up with some methods and changes in regulations, but recently finally realized my conception of reference-scaling was at best oversimplified, and not giving proper estimates. Meanwhile, PowerTOST was developed in the language I love, so rather than re-inventing the wheel, I outsourced this method to PowerTOST.

I have received a lot of kind emails about FARTSSIE over the years. If you have a version of it somewhere on your hard drive, please update it to the latest, as I really have made a number of important improvements and corrections. Helmut helped me correct the suggested PowerTOST code.

Richard passed away a while ago now (we all warned him about the chain smoking!). So many stories, so much house wine at the Open Cork restaurant, and so many hysterical conflicts with QA, Richard was without a doubt my favourite mentor. I miss him dearly.

Kind regards,
Dave

—
David Dubins, Ph.D., B.A.Sc.
Associate Professor, Teaching Stream
Director, Pharmaceutical Chemistry Specialist Program
Leslie Dan Faculty of Pharmacy
University of Toronto

144 College Street (room PB802), Toronto, ON M5S 3M2
Tel. +1 416-946-5303; FAX: +1 416 978-8511

dshah ★★ India, 2021-03-11 10:33 (1370 d 07:56 ago) (edited on 2021-03-11 11:53) @ ddubins Posting: # 22257 Views: 4,739	FARTSSIE v2.7
	Greetings Dr. Dubin! Thank you for the wonderful work and contribution in the field. I hope to see more from you in excel. Still struggling with installation of R in organization and because of that I had asked for Sample size for NTI- FDA method in excel. Thank you very much for your contribution. Regards, DShah

Helmut
★★★

Vienna, Austria,
2021-03-11 22:24
(1369 d 20:06 ago)

@ dshah
Posting: # 22260
Views: 4,694

FARTSSIE v2.7

Hi DShah,

❝ Still struggling with installation of R in organization …

It’t high time for your organization to learn that you need the right tools to perform your job.

I suppose it is tempting, if the only tool you have is a hammer,
to treat everything as if it were a nail. Abraham H. Maslow (Toward a Psychology of Being, 1962)

❝ … and because of that I had asked for Sample size for NTI- FDA method in excel.

You would need to simulate 100,000 studies in each iteration (cause you will not hit the target with a lucky punch). I don’t say that’s impossible in Excel. But why the hell would one do that, if PowerTOST can give you the result in less than a second?

library(PowerTOST) system.time(sampleN.NTIDFDA(CV = 0.1)) # use the defaults +++++++++++ FDA method for NTIDs ++++++++++++ Sample size estimation --------------------------------------------- Study design: 2x2x4 (TRTR|RTRT) log-transformed data (multiplicative model) 1e+05 studies for each step simulated. alpha = 0.05, target power = 0.8 CVw(T) = 0.1, CVw(R) = 0.1 True ratio = 0.975 ABE limits = 0.8 ... 1.25 Implied scABEL = 0.8000 ... 1.2500 Regulatory settings: FDA - Regulatory const. = 1.053605 - 'CVcap' = 0.2142 Sample size search n power 14 0.717480 16 0.788690 18 0.841790 user system elapsed 0.15 0.07 0.22

—
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

dshah
★★

India,
2021-03-16 07:22
(1365 d 11:08 ago)

@ Helmut
Posting: # 22267
Views: 4,578

FARTSSIE v2.7

Thank you Helmut, Detlew Labes and Benjamin Lang!

I am really thankful for your PowerTOST package in R. It is fast, accurate and required information limited to study design, ISCV, Power and expected ratio. Because of this I am able to do the sample size estimation after working hours in personal system.
But as of now, my organization's IT system is not allowing me to install R.
And I want to explore bear and ivivc and many other things of R, for which I am banging my head.
Thank you for wonderful PowerTOST and Dave's contribution as well.
Regards,
Dshah

Helmut
★★★

Vienna, Austria,
2021-03-11 22:08
(1369 d 20:22 ago)

@ ddubins
Posting: # 22259
Views: 4,742

FARTSSIE v2.7

Hi Dave,

❝ I have updated FARTSSIE to version 2.7, and migrated it (finally) to github:

❝ https://github.com/dndubins/FARTSSIE

Great!

❝ It's been a while since I've posted to this forum (oh it has to be years now!)…

September 2010…

THX for the moving background-stories! :smoke:

—
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

d_labes ★★★ Berlin, Germany, 2021-03-12 19:29 (1368 d 23:00 ago) @ ddubins Posting: # 22264 Views: 4,676	Richard Moisan
	Dear Dave, thank you so much for your background story. After reading it it was such a pity to me not to know Dr. Richard Moisan. You glad boy, met him and know him. May he rest in peace. All the best — Regards, Detlew

dshah ★★ India, 2021-09-09 17:08 (1188 d 02:21 ago) @ d_labes Posting: # 22561 Views: 4,099	FARTSSIE 2.8
	Dear All! FARTSSIE version 2.8 is now available. Thank you Dave. Regards, Dshah

FARTSSIE v2.5 [Software]

FARTSSIE v2.7

FARTSSIE v2.7

FARTSSIE v2.7

FARTSSIE v2.7

FARTSSIE v2.7

Richard Moisan

FARTSSIE 2.8