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Compliance
Regular

India,
2014-03-13 09:43

Posting: # 12612
Views: 10,823
 

 Type of study in modified release formu­lation EMEA [Regulatives / Guidelines]

Dear All,

We would like to submit dossier of generic modified release formulation in Europe and we are not cleared about following statement of guideline.

The European guidance line no. 593 to 595 states as follows:

"A multiple dose study is needed unless a single dose study has been performed with the highest strength which has demonstrated that the mean AUC(0-τ) after the first dose covers more than 90% of mean AUC(0-∞) for both test and reference, and consequently a low extent of accumulation is expected".

In this if you read they are asking to see AUC(0-τ) after single dose which confuse us as after single dose administration how this parameter can be evaluated. I think here to cases are cubed which ultimately resulting into the confusion.

with addition to this the entire section is not delivering correct understanding to me hence if possible can any one make it simple it to get optimum understanding.

regards,

Compliance


Edit: In 2005 (!) EMEA (European Agency for the Evaluation of Medicinal Products) was renamed to EMA (European Medicines Agency). ;-) [Helmut]
nobody
Senior

2014-03-13 09:52

@ Compliance
Posting: # 12613
Views: 10,018
 

 Type of study in modified release formu­lation EMEA

...don't see any problems in calculating AUCtau, could you specify your problem a little more in detail?!

Kindest regards, nobody
fno
Junior
Homepage
Belgium,
2014-03-13 11:16

@ Compliance
Posting: # 12615
Views: 9,923
 

 Type of study in modified release formu­lation EMEA

» "A multiple dose study is needed unless a single dose study has been performed with the highest strength which has demonstrated that the mean AUC(0-τ) after the first dose covers more than 90% of mean AUC(0-∞) for both test and reference, and consequently a low extent of accumulation is expected".

This does not seem so cryptic anyway...

Let's assume a once daily dosing is the standard regimen for the originator (reference) product.
You have to perform a BE single dose study with both test and reference formulations at the highest registered strength and compute AUC0-24h and AUC0-inf. If this study demonstrate that AUC0-24h > 0.9 × AUC0-inf for both test and reference, it is not necessary to perform a MD BE study.

Hope this helps.

Kind regards,
Fabrice
kumarnaidu
Regular

Mumbai, India,
2014-11-27 11:02
(edited by kumarnaidu on 2014-11-27 12:00)

@ fno
Posting: # 13928
Views: 9,505
 

 Type of study in modified release formu­lation EMEA

Dear All,
We did BE studies (single dose fast and fed,multiple dose fed) for metformin ER tablets 1000 mg and want to ask-
Can steady state studies marginally failing at Cτ,ss 80.19 (72.8 to 88.34) with ISCV=23.1) be clinically justified for regulatory acceptance if the single dose fast and fed studies are passing for all the parameters including pAUCs?

Kumar Naidu
nobody
Senior

2014-11-27 11:37

@ kumarnaidu
Posting: # 13929
Views: 9,410
 

 Type of study in modified release formu­lation EMEA

The guideline allows widening for Ctau,ss as for highly variable drugs. Did you go for that in the protocol? Otherwise...

Kindest regards, nobody
kumarnaidu
Regular

Mumbai, India,
2014-11-27 12:53

@ nobody
Posting: # 13930
Views: 9,444
 

 Type of study in modified release formu­lation EMEA

» The guideline allows widening for Ctau,ss as for highly variable drugs. Did you go for that in the protocol?

Ok thanks for the reply. But I think for applying widening criteria we need to show CV>30% for reference product and the study should be reference replicate (3way or 4way).
Can we use Pre-dose concentration and Ctau of steady state to show variability?:confused:

Kumar Naidu
Helmut
Hero
avatar
Homepage
Vienna, Austria,
2014-11-27 13:47

@ kumarnaidu
Posting: # 13932
Views: 9,516
 

 Scaling of Cmin

Hi Kumar,

» But I think for applying widening criteria we need to show CV>30% for reference product and the study should be reference replicate (3way or 4way).

Correct. I wouldn’t be too optimistic with the CVintra of 23.1% you reported.

» Can we use Pre-dose concentration and Ctau of steady state to show variability?:confused:

This idea was discussed in Bonn last year. Members of EMA’s PKWP seemed to be happy with it. I guess the MR-GL was adopted at EMA’s CHMP-meeting last week. Let’s wait for it (and the comments). The analysis is a little bit tricky* because the replicates originate from the same period.


  • Liu J-P. Use of the Repeated Crossover Design in Assessing Bioequivalence. Stat Med. 1995;14(9–10):1067–78. doi:10.1002/sim.4780140926

Edit: The MR-GL was adopted indeed. See here.

Edit: GL, Section 6.8.2.2:

Any widening of the acceptance criteria for Cmax should follow the recom­men­da­tions on highly variable drug products in the Guideline on the Investigation of Bio­equivalence (CPMP/EWP/QWP/1401/98).
A similar approach can be used for widening the acceptance criteria for Cmax,ss, Cτ,ss, and partialAUC. Calculation of the intra-subject variability in multiple dose studies can be based on two consecutive administrations of the same product after reaching steady state.


Cheers,
Helmut Schütz
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Science Quotes
kumarnaidu
Regular

Mumbai, India,
2014-11-27 15:12

@ Helmut
Posting: # 13937
Views: 9,365
 

 Scaling of Cmin

Thanks Helmut for your valuable comment.

Kumar Naidu
kumarnaidu
Regular

Mumbai, India,
2014-12-05 06:03

@ Helmut
Posting: # 13979
Views: 9,227
 

 Scaling of Cmin

Hi Helmut thanks for the comment.

» Calculation of the intra-subject variability in multiple dose studies can be based on two consecutive administrations of the same product after reaching steady state.

That means we have to use the 4 way (Fully replicate) method here but with a different sequence RRTT or TTRR

Kumar Naidu
kumarnaidu
Regular

Mumbai, India,
2014-12-10 11:15

@ kumarnaidu
Posting: # 14044
Views: 8,936
 

 Steady state

Hi All,
I am little bit confused with this statement.
In all other cases, where accumulation is likely (AUC(0-τ) after the first dose covers less than 90% of mean AUC(0-∞)) a multiple dose study is required. Generally, steady-state studies should be performed under the conditions concerning concomitant food intake recommended in the SmPC for the originator product.

If for any drug concomittant food intake is reccomended and it shows no accumulation (AUC(0-τ) after the first dose covers less than 90% of mean AUC(0-∞)) then in that case should we go for steady state or not?:confused:

Kumar Naidu
nobody
Senior

2014-12-10 17:04

@ kumarnaidu
Posting: # 14048
Views: 8,951
 

 Steady state

Hi! Read the red sentence again, and again, and again... You will understand it... Otherwise show it to a colleague...

Kindest regards, nobody
Dr_Dan
Senior

2014-12-10 17:21

@ kumarnaidu
Posting: # 14049
Views: 9,004
 

 Scaling of Cmin

Dear kumarnaidu

» That means we have to use the 4 way (Fully replicate) method here but with a different sequence RRTT or TTRR

No, you do not need to use a 4 period replicate design: You will have 2 periods and 2 sequences, you just need to dose until you reach steady state, take then the PK profile for the dosing interval and after an afreshed dosing for the consecutive interval.

e.g.:
1st dosing drug1
2nd dosing drug1
3rd dosing drug1
4th dosing drug1
5th dosing drug1 -> PK Profile
6th dosing drug1 -> PK Profile
1st dosing drug2
2nd dosing drug2
3rd dosing drug2
4th dosing drug2
5th dosing drug2 -> PK Profile
6th dosing drug2 -> PK Profile


Kind regards
Dr_Dan

Kind regards and have a nice day
Dr_Dan
Helmut
Hero
avatar
Homepage
Vienna, Austria,
2014-12-10 18:40

@ Dr_Dan
Posting: # 14051
Views: 8,967
 

 Scaling of Cmin

Dear Dan,

I think that your example is a fully replicate design (i.e., RRTT|TTRR) indeed. Just substitute drug1 with R and drug2 with T and you’ll get the first of the two sequences from above. Of course you have to modify the code given in EMA’s Q&A (for RTRT|TRTR) accordingly. But that’s an easy task.
This concept would work for all PK metrics. Coming back to the subject line (and which was discussed in Bonn): Scaling only Cmin without the need of sampling four full profiles.

treatment dose
    R       1
    R       …
    R       n profile
    T       1
    T       …
    T       n profile


On profile days you have two values of Cmin. One prior to dosing and another one at τ. Now the stats become interesting. You would need to introduce an additional code (e.g., “replicate”) to distinguish these two values because they are sampled from the same period(s). I’m working on it. EMA’s preference of an all-fixed model is nasty. My current setup is: Sequence+Subject(Sequence)+Treatment+Replicate+Treatment(Replicate)+Period

PS @Anders: Sorry for the nesting. I know, I know.

Cheers,
Helmut Schütz
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d_labes
Hero

Berlin, Germany,
2014-12-11 13:09

@ Helmut
Posting: # 14053
Views: 8,849
 

 Scaling of Cmin

Dear Helmut,

» ... I’m working on it. EMA’s preference of an all-fixed model is nasty. My current setup is: Sequence+Subject(Sequence)+Treatment+Replicate+Treatment(Replicate)+Period

That's weird. Two times Treatment in the model :confused:.

Regards,

Detlew
Helmut
Hero
avatar
Homepage
Vienna, Austria,
2014-12-11 14:53

@ d_labes
Posting: # 14056
Views: 8,865
 

 Scaling of Cmin

Dear Detlew,

» » ... I’m working on it. EMA’s preference of an all-fixed model is nasty. My current setup is: Sequence+Subject(Sequence)+Treatment+Replicate+Treatment(Replicate)+Period
»
» That's weird. Two times Treatment in the model :confused:.

Dammit! I’m not sure how to reproduce Liu’s results anyhow. :confused: Work in progress.

Cheers,
Helmut Schütz
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Science Quotes
VStus
Regular

Poland,
2017-02-03 13:04
(edited by VStus on 2017-02-03 15:50)

@ Helmut
Posting: # 17005
Views: 6,442
 

 Scaling of Cmin

Dear Helmut,

Have you solved this puzzle?

I must confess that Liu's article is too hard for me. I understand that the idea of scaling is based on assessment of within-subject variability after the administration of only Reference formulation.

But article is targeting repeated crossover studies (RRTT|TTRR) for assessment of population/individual bioequivalence. Due to this, a more complicated statistical model was proposed and justified. But we are not interested in population bioequivalence now.

Would it be correct to analyze only a reference subset of data to estimate the variability of reference PK parameter only? Let's assume I'm interested only in possibility of widening of acceptance limits for Ctau_ss, do I need test formulation data at all?

We will not have different formulations in resulting subset, just factors of period + sequence + subject + repetition.

I have reduced Liu's dataset to have:
subject - 20 levels (1-20)
sequence - 2 levels (RT and TR)
period - 2 levels (1 or 2)
repetition - 2 levels (1 or 2)
AUC for Reference formulation.

Which gives me:
anova(lm(log(AUC) ~ prd + seq + rep + subj:seq, data=data, na.action=na.exclude))
## Residuals 19 0.60602 0.031896
100*sqrt(exp(0.031896)-1)
## [1] 18.00281


Residual MS is higher than reported by Lui for Reference formulation ('MS(R) = 0.03094'), thus it seems that I'm overestimating the variability of the Reference in this simplified model.

Thank you very much in advance!

Regards, VStus

Sorry for confusion: this is not a replicate design
zizou
Regular

Plzeň, Czech Republic,
2017-02-03 13:49
(edited by zizou on 2017-02-03 18:47)

@ VStus
Posting: # 17006
Views: 6,414
 

 Scaling of Cmin

Dear VStus,
it looks like you reduced it too much.


» I have reduced Liu's dataset to have:
» subject - 20 levels (1-20)
» sequence - 2 levels (RT and TR)
» period - 2 levels (1 or 2)
» replication - 2 levels (1 or 2)
» AUC for Reference formulation.


When you reduce period for 2 levels - I think the change makes period to be equal to replication.
Period should still have 4 levels (1 or 2 or 3 or 4). If I am not mistaken.

Edit1: My mistake I don't have a data/reference and I thought the data was from 4 periods. After repeated reading I noticed that there were two periods only with created "repetition" term. I am sorry, I was too fast with replaying and I lacked the quality.

Edit2: If I get it right (I hope so) there is something like this scheme:
  period: 1    2
seq 1: ---TT---RR
seq 2: ---RR---TT

When we are interested only in R (per1+seq1 and per2+seq2 are not used at all). So in evaluation of only R data, Period 1 is equal to Sequence 2 (in the term of categorizing data) and Period 2 is equal to Sequence 1, so it's also known from subject No, when the data was obtaind (period 1 or 2). So period doesn't have any new information (the information is provided in other terms).
You may try:
anova(lm(log(AUC) ~ seq + rep + subj:seq, data=data, na.action=na.exclude))
(I'm curious if the results differ against the results with period in.)


Best regards,
zizou
VStus
Regular

Poland,
2017-02-03 15:37

@ zizou
Posting: # 17008
Views: 6,394
 

 Scaling of Cmin

Dear zizou,

Thank you very much for the feedback!

I've tried 4 periods instead of 2 and got even higher variation, which seems to be an overestimation:
summary(data)
##       subj    seq     prd    drug   rep          AUC       
##  1      : 2   RT:20   1:10   R:40   R1:20   Min.   : 439.0 
##  2      : 2   TR:20   2:10          R2:20   1st Qu.: 656.5 
##  3      : 2           3:10                  Median : 781.5 
##  4      : 2           4:10                  Mean   : 795.6 
##  5      : 2                                 3rd Qu.: 929.8 
##  6      : 2                                 Max.   :1297.0 
##  (Other):28
anovadata <- lm(log(AUC) ~ seq + subj:seq + rep + prd, data=data, na.action=na.exclude)
anova(anovadata)
## Analysis of Variance Table
##
## Response: log(AUC)
##           Df  Sum Sq  Mean Sq F value  Pr(>F) 
## seq        1 0.20989 0.209885  6.2514 0.02230 *
## rep        1 0.00507 0.005067  0.1509 0.70222 
## prd        1 0.00169 0.001689  0.0503 0.82505 
## seq:subj  18 1.55131 0.086184  2.5670 0.02631 *
## Residuals 18 0.60433 0.033574                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
100*sqrt(exp(0.033574)-1)
## [1] 18.47812


Removing replication from the model does not change residual MS :)

Regards, VStus
VStus
Regular

Poland,
2017-02-06 08:55

@ zizou
Posting: # 17017
Views: 6,249
 

 Scaling of Cmin

Dear zizou,

No change in residual variance if I remove 'period' from the model.

anovadata <- lm(log(AUC) ~ prd + seq + rep + subj:seq, data=data, na.action=na.exclude)
anova(anovadata)

## Analysis of Variance Table
##
## Response: log(AUC)
##           Df  Sum Sq  Mean Sq F value  Pr(>F) 
## prd        1 0.20989 0.209885  6.5803 0.01894 *
## rep        1 0.00507 0.005067  0.1589 0.69466 
## seq:subj  18 1.55131 0.086184  2.7020 0.01873 *
## Residuals 19 0.60602 0.031896                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

MSE       <- anova(anovadata)["Residuals","Mean Sq"] 100*sqrt(exp(MSE)-1)

## [1] 18.00281

anovadata <- lm(log(AUC) ~ seq + rep + subj:seq, data=data, na.action=na.exclude)
anova(anovadata)
## Analysis of Variance Table
##
## Response: log(AUC)
##           Df  Sum Sq  Mean Sq F value  Pr(>F) 
## seq        1 0.20989 0.209885  6.5803 0.01894 *
## rep        1 0.00507 0.005067  0.1589 0.69466 
## seq:subj  18 1.55131 0.086184  2.7020 0.01873 *
## Residuals 19 0.60602 0.031896                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Maybe MIXED procedure should be used?

Regards, VStus
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