Sukalpa Biswas
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India,
2019-08-06 09:15
(edited by Sukalpa Biswas on 2019-08-07 09:07)

Posting: # 20475
Views: 382
 

 NTI drug Bioequivalence study Statistical approach [Study As­sess­ment]

This is regarding NTI drug Bio equivalence study Statistical approach.
As per regulatory,
  1. Primary pharmacokinetic parameter(s) for the 90% confidence interval of the geometric least square means must fall within 80.00% to 125.00% (both inclusive).
  2. Reference Scaled Average Bioequivalence:
    The 95% upper confidence bound for (μT-μR)2-θ*S2WR must be ≤ 0.
    The point estimate of the Test/Reference geometric mean ratio must fall within [0.80, 1.25]
  3. The within-subject standard deviation of test and reference products will be compared, and the upper limit of the 90% confidence interval for the test-to-reference ratio of the within-subject variability should be ≤ 2.5.
Observations during study:

All the above criteria has been met except 90% confidence interval for the test-to-reference ratio of the within-subject variability ≤ 2.5 were not meet the criteria for all PK variables (Cmax, AUCt and inf).

Exercises, Observations and Analysis:
  1. We have taken subjects who have completed at least 2R or 2T in Reference Scaled Average Bio equivalence calculation (existing study).
  2. We have done the exercise who have completed all four treatments and did the statistical calculation- still failing on the same criteria marginally(90% confidence interval for the test-to-reference ratio of the within-subject variability should be ≤ 2.5).
  3. It was observed that if the “SWT” value should be closed to SWR value or lower, then 90% CI for the test-to-reference ratio of the within-subject variability ≤ 2.5 will meet the criteria.
Seeking help on:
  1. Which Reference Scaled Average Bioequivalence approach is acceptable in regulatory?
    Approach 1: Subject completed at least two test product will consider for SWT calculation and subject who completed at least two reference will consider for SWR calculation.
    Approach 2: Subjects who completed four period will be consider for SWR & SWT calculation.
    or both.
  2. which are the factors adding variability to SWT?
  3. Whether same formulation can be taken for the repeat bio-study with some clinical restrictions? If yes then what are the clinical factor to be considered?

Kindly respond.


Edit: Please follow the Forum’s Policy. Category changed; see also this post #1[Helmut]
Helmut
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Vienna, Austria,
2019-08-07 11:09

@ Sukalpa Biswas
Posting: # 20482
Views: 311
 

 Cherry-picking?

Hi Sukalpa,

»

3. The within-subject standard deviation of test and reference products will be compared, and the upper limit of the 90% confidence interval for the test-to-reference ratio of the within-subject variability should be ≤ 2.5.


» […] 90% confidence interval for the test-to-reference ratio of the within-subject variability ≤ 2.5 were not meet the criteria for all PK variables (Cmax, AUCt and inf).

Failed to demonstrate BE due to the higher within-subject variability of the test product. Full stop.

» Exercises, Observations and Analysis:

What do you mean by „Exercises”? Since the study failed are you asking for a recipe to cherry-pick? :cherry picking:
»

1. We have taken subjects who have completed at least 2R or 2T in Reference Scaled Average Bio equivalence calculation (existing study).


That’s my interpretation as well. Although only the calculation of sWR is given in Step 1 of the guidance by analogy the same procedure should be applicable for sWT.
»

2. We have done the exercise who have completed all four treatments and did the statistical calculation- still failing on the same criteria marginally.


Leaving cherry-picking aside: By doing so, you drop available information. One should always use all. The more data you have, the more accurate/precise an estimate will be. Have a look at the formula to calculate the 100(1–α) CI of σWTWR:$$\left(\frac{s_{WT} / s_{WR}}{\sqrt[]{F_{\alpha /2,\nu_1,\nu_2}}},\frac{s_{WT} / s_{WR}}{\sqrt[]{F_{1-\alpha /2,\nu_1,\nu_2}}} \right)$$We have two different degrees of freedom (ν1, ν1), the first associated with sWT and the second with sWR.
»

3. It was observed that if the “SWT” value should be closed to SWR value or lower, then 90% CI for the test-to-reference ratio of the within-subject variability ≤ 2.5 will meet the criteria.


Of course.
»

1. Which Reference Scaled Average Bioequivalence approach is acceptable in regulatory?
» Approach 1: Subject completed at least two test product will consider for SWT calculation and subject who completed at least two reference will consider for SWR calculation.


Yes.
»

Approach 2: Subjects who completed four period will be consider for SWR & SWT calculation.


No.
»

or both.


Which one will you pick at the end if one passes and the other one fails? The passing one, right? The FDA will love that. Be aware that the FDA recalculates every study.
BTW, how would you describe that in the SAP?
»

2. which are the factors adding variability to SWT?


That’s product-related. The idea behind the FDA’s reference-scaling for NTIDs is not only the narrow the limits but also to prevent products with higher variability than the reference’s entering the market.
»

3. Whether same formulation can be taken for the repeat bio-study with some clinical restrictions? If yes then what are the clinical factor to be considered?


As I wrote above, the failure to show BE was product-related. If you introduce clinical restrictions* in order to reduce within-subject variability – due to randomization – both products will be affected in the same way and sWT/sWR be essentially the same like in the failed study.
Reformulate.

PS: I changed the category of your post to Study Assessment yesterday and you to RSABE / ABEL today. Wrong. Don’t test my patience – your problems are definitely study-specific (see the Policy for a description of categories).


  • Which ones are you thinking about? I don’t see how it could be possible to reduce within-subject variability by any means. Given, chaining volunteers to their beds might help.

Cheers,
Helmut Schütz
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Sukalpa Biswas
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India,
2019-08-09 06:11

@ Helmut
Posting: # 20488
Views: 231
 

 digging out the possible reasons of the failure

» Failed to demonstrate BE due to the higher within-subject variability of the test product. Full stop.

Accepted.

» » Exercises, Observations and Analysis:
» What do you mean by „Exercises”?

Since the study has been failed, we wanted to dig out the probable reasons for the study failure. In that process certain statistical exercises have be done officially.

» Although only the calculation of sWR is given in Step 1 of the guidance by analogy the same procedure should be applicable for sWT.

Accepted. Thanks.

» […] you drop available information. One should always use all. […]

Suggestion well accepted. Thanks.

» »

1. Which Reference Scaled Average Bioequivalence approach is acceptable in regulatory?
» » Approach 1: Subject completed at least two test product will consider for SWT calculation and subject who completed at least two reference will consider for SWR calculation.


» Yes.
» »

Approach 2: Subjects who completed four period will be consider for SWR & SWT calculation.


» No.
» »

or both.


» Which one will you pick at the end if one passes and the other one fails? The passing one, right? The FDA will love that. Be aware that the FDA recalculates every study.

Thanks for your suggestion.

» »

2. which are the factors adding variability to SWT?


» That’s product-related. The idea behind the FDA’s reference-scaling for NTIDs is not only the narrow the limits but also to prevent products with higher variability than the reference’s entering the market.

Agreed

» As I wrote above, the failure to show BE was product-related. If you introduce clinical restrictions* in order to reduce within-subject variability – due to randomization – both products will be affected in the same way and sWT/sWR be essentially the same like in the failed study.
» Reformulate.

OK. I would like to mention one thing that, the failed study was fed one, fasting study passed quite comfortably (both ABE and SABE). Is there any possibility that the test formulation is more variable in fed condition? :confused:

» PS: I changed the category of your post […].

Sorry. This is the first time I am posting something in this forum. Bit confused regarding the rules and regulation of this forum. :confused:

»
  • I don’t see how it could be possible to reduce within-subject variability by any means. Given, chaining volunteers to their beds might help.

:-)


Edit: Full quote removed. Please delete everything from the text of the original poster which is not necessary in understanding your answer; see also this post #5[Helmut]
Helmut
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Vienna, Austria,
2019-08-09 12:36

@ Sukalpa Biswas
Posting: # 20489
Views: 199
 

 Fed state: T higher variable than R

Hi Sukalpa,

» » Reformulate.
»
» OK. I would like to mention one thing that, the failed study was fed one, fasting study passed quite comfortably (both ABE and SABE). Is there any possibility that the test formulation is more variable in fed condition? :confused:

That’s quite possible. An extreme example of the past: The first PPIs were monolithic gastric-resistant formulations. Crazy variability, both fasting and fed. Current formulations are capsules with gastric-resistant pellets. Variability still high but way better than the monolithic forms. Of course, when the capsules were introduced, BE studies were performed. All PK metrics passed but by inspecting the profiles you could clearly see the lower variability of the capsules. OK, these are easy drugs (now many are already OTCs). Imagine that they would be NTIDs and the formulation change the other way ‘round (capsule → monolithic). No way ever to pass the swT/swR criterion.

In your case this means again to reformulate. Don’t ask me how (I’m not a formulation chemist). Maybe dissolution testing in the various stinking FeSSIF “biorelevant” media helps.

» This is the first time I am posting something in this forum. Bit confused regarding the rules and regulation of this forum. :confused:

Some hints in the Policy.

Cheers,
Helmut Schütz
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