martin
★★  

Austria,
2012-05-17 17:10
(5138 d 02:49 ago)

Posting: # 8580
Views: 6,951
 

 In-vitro equivalence [General Sta­tis­tics]

dear all!

I have a questions regarding testing for equivalence and acceptance criteria for lot releases. In these kind of studies several lots (test) and one reference lot are investigated in-vitro each with replicated measurements (typically 3 replicates per lot are available).

For an overall statement (i.e. combined lots) the R package mratios may be used to model the lot and potential day and/or operator effects assuming normal distribution and independent replicates and use corresponding contrasts to get the ratio and corresponding CIs for an overall statement. However, I do not really understand the comparison of individual lots with the reference lot. In statistics, CIs are used get an idea regarding the population average. By comparing individual lots with the reference lot the statistical unit reflects only the assay variability.

I would be happy if you can help me in answering the following questions:
  1. Is anyone aware of acceptance criteria for these kind of evaluations (I think the scaled average approach may be also applicable as the CV of the assay is known and a parallel group design is adequate).
  2. What is the interpretation (i.e. statement regarding the population) when equivalence is shown (for a given acceptance criteria) for a specific test lot compared to the reference lot.
best regards

martin
ElMaestro
★★★

Denmark,
2012-05-19 03:35
(5136 d 16:24 ago)

@ martin
Posting: # 8587
Views: 6,099
 

 In-vitro equivalence

Hi Martin,

which of the following questions are you trying to answer:
1. Can this lot I just produced be released?
2. Is the production process stable?

Without being fully sure I get the idea that your situation isn't classical (batch release is based on floating criteria?) and that you are perhaps entering the world of GMP, Six Sigma, DoE and QbD and then it quickly gets extremely complex. Could you provide a bit more context?

Pass or fail!
ElMaestro
martin
★★  

Austria,
2012-05-19 12:28
(5136 d 07:30 ago)

@ ElMaestro
Posting: # 8589
Views: 6,099
 

 In-vitro equivalence

Dear ElMaestro!

We were asked by a regulator to examine a random sample of k>25 lots produced (including also already formally "released" lots) each evaluated with at least 3 replicates. The information that I have is that we have to show (whatever that means) that the lots are "comparable" to the reference lot (i.e. kind of standard) and superior to the negative control lot (also a kind of standard without biological activity).

I would be really glad to get some ideas and suggestions!

best regards

martin

PS.: I do not like the word comparable: apple and oranges

PPS.: it's a biologic - QbD :smoke:
ElMaestro
★★★

Denmark,
2012-05-19 15:55
(5136 d 04:03 ago)

@ martin
Posting: # 8590
Views: 6,125
 

 In-vitro equivalence

Hi Martin,

❝ I would be really glad to get some ideas and suggestions!

❝ PPS.: it's a biologic - QbD :smoke:


OK. On basis of the info provided I am guessing that you could make a CI for the Test batches -each of them- and show that each CI spans over the PE for the single ref batch. You can plot CI limits and test's PE's as function of batch number (or better time of production?) and add a horizontal line depicting the ref.'s PE. The alphas prolly need qualification so that regulators know that you do not just chose the one that ensures that all CI's span across the ref's PE.

Pass or fail!
ElMaestro
Alex
☆    

Austria,
2012-05-22 13:10
(5133 d 06:48 ago)

@ ElMaestro
Posting: # 8598
Views: 5,994
 

 In-vitro equivalence

Dear ElMaestro!

❝ OK. On basis of the info provided I am guessing that you could make a CI for the Test batches -each of them- and show that each CI spans over the PE for the single ref batch.


Wouldn't that ignore the variability of the reference batch? It would be identical to an one-sample t-test to the reference PE for each batch. What if the focus is more on testing for equivalence than on testing for difference?

Thanks!
Best regards,
Alex
ElMaestro
★★★

Denmark,
2012-05-22 16:08
(5133 d 03:50 ago)

@ Alex
Posting: # 8600
Views: 6,001
 

 In-vitro equivalence

Hi Alex,

❝ Wouldn't that ignore the variability of the reference batch? It would be identical to an one-sample t-test to the reference PE for each batch. What if the focus is more on testing for equivalence than on testing for difference?


Absolutely correct re. the ignorance of ref. variability. However I am not sure in the context of this question that within-batch variability is the concern, given Martin's question "assuming normal distribution and independent replicates". In fact, when we look at between-batches (which I think is the likely aim for this QbD exercise) then the replicates within batches can certainly not be said to be independent or uncorrelated. In such situations, I think the theoretical way out is to use a mixed model. But it all depends on the purpose.
But as always I could be wrong, so...
Martin, do you wish to characterise the process performace within-batch or between-batch?

Pass or fail!
ElMaestro
martin
★★  

Austria,
2012-05-22 19:00
(5133 d 00:59 ago)

@ ElMaestro
Posting: # 8604
Views: 5,938
 

 In-vitro equivalence

Dear ElMaestro!

First of all – thank you very much for your input. Here is the „situation“ in more detail. There are k test lots, one reference and one negative control lot. From each lot k>3 samples are drawn (i.e. 3 vials) each analyzed seperately with a specific assay. For this reason, I assume that the replicates independent within each lot.

I suppose that the focus is on individual lots (i.e. „showing“ that each lot is „comparable“ to the reference lot and that each lot is superior to the negative control lot).

Based on your suggestions I think that here only PE estimates may be used. What do you think about a figure showing ratios of means for individual lots relative to the mean of the negative control for “showing” superiority and another figure showing ratios of means for individual lots relative to the reference for “showing equivalence” similar like forest plot in meta analysis (y-axis = lots; x-axis = ratio of means).

For an overall statement (i.e. all lots combined) a CI for the ratio (package mratios) can be calculated using an ANOVA model that models the lot effect (i.e. replicates within each lot) with a contrast matrix that gives the estimated mean over all lots versus the estimated mean of the reference lot. In this model, the potential day effect can be included to adjust for a potential day effect.

What do you think?

Best regards

Martin

PS.: here is an example code for the overall statement

library(mratios)

# specify parameters for data generation #
n <- 3 # number of replicates
mue <- 5 # expected value within each lot
cv <- 0.1 # expcect assay variability
sd <- mue*cv

# generate example data set using random numbers #
lot <- c('T01', 'T02', 'T03', 'T04', 'T05', 'T06', 'T07', 'T08', 'T09', 'T10', 'R')
data <- data.frame(lot=sort(rep(lot, n)))
data$value <- rnorm(nrow(data), mean=mue, sd=sd)
data$lot <- factor(data$lot)
xq <- tapply(data$value, data$lot, mean)
sd <- tapply(data$value, data$lot, sd)
print(xq)
print(sd)
print(sd/xq*100)

# estimation of ratio #
X <- model.matrix(value~ 0 + lot, data=data)
Y <- data[,"value"]
coef <- lm(Y ~ 0 + X)
print(coef)
Num.Contrast <- matrix(c(0,1/10,1/10,1/10,1/10,1/10,1/10,1/10,1/10,1/10,1/10),nrow=1,byrow=TRUE)
Den.Contrast <- matrix(c(1,0,0,0,0,0,0,0,0,0,0),nrow=1,byrow=TRUE)
print(Num.Contrast)
print(Den.Contrast)
sci.ratio.gen(Y=Y, X=X, Num.Contrast=Num.Contrast, Den.Contrast=Den.Contrast, method='Unadj', conf.level=0.90)
ElMaestro
★★★

Denmark,
2012-05-22 20:36
(5132 d 23:22 ago)

@ martin
Posting: # 8606
Views: 5,958
 

 In-vitro equivalence

Hi Martin,

❝ First of all – thank you very much for your input. Here is the „situation“ in more detail. There are k test lots, one reference and one negative control lot. From each lot k>3 samples are drawn (i.e. 3 vials) each analyzed seperately with a specific assay. For this reason, I assume that the replicates independent within each lot.


I agree, proper sampling this way can be considered independent within each lot.

❝ I suppose that the focus is on individual lots (i.e. „showing“ that each lot is „comparable“ to the reference lot and that each lot is superior to the negative control lot).


Comparative lots: Sounds to me just like standard parallel bioequivalence then. R's simple t.test with a 90% CI comes to mind here. Might need to omit the log step depending on residual considerations. And I am sure Helmut will chirp in with a comment about Welch-Satterthwaite.
But on the other hand, with three replicates per lot a CI-approach seems quite meaningless.

❝ Based on your suggestions I think that here only PE estimates may be used. What do you think about a figure showing ratios of means for individual lots relative to the mean of the negative control for “showing” superiority and another figure showing ratios of means for individual lots relative to the reference for “showing equivalence” similar like forest plot in meta analysis (y-axis = lots; x-axis = ratio of means).


Sounds completely fine and intuitive to me.

❝ For an overall statement (i.e. all lots combined) a CI for the ratio (package mratios) can be calculated using an ANOVA model that models the lot effect (i.e. replicates within each lot) with a contrast matrix that gives the estimated mean over all lots versus the estimated mean of the reference lot. In this model, the potential day effect can be included to adjust for a potential day effect.


❝ What do you think?


Apart from my comment above, I am afraid I can only produce completely flat brain waves here. I am unfortunately unfamiliar with mratios. A closer look at your code is needed and I feel neither competent nor worthy. It does, however, not sound readily intuitive to me if you say the lot effect is the replicates of units within lots. But that's probably just a matter of semantics.

Pass or fail!
ElMaestro
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