unique_one
☆    

India,
2015-10-09 08:44
(3093 d 14:39 ago)

Posting: # 15536
Views: 6,979
 

 Pilot Results and Pivotal Design [Study As­sess­ment]

Dear All,

Kindly find the brief summary of below mentioned results for one of the pilot studies conducted. n=16, 2 way 2 period 2 treatment single dose crossover.

Parameter     Ratios  CI 90_L  CI 90_U  Power   IS CV (%)
Ln(Cmax)      98.58   77.47   128.41    0.4194  43.13
Ln(AUC last)  93.86   82.05   110.32    0.8307  22.51
Ln(AUC INF)   89.75   72.47   111.56    0.5223  33.65


As per the literature the molecule does not have iscv above 30% and therefore we need to design our pivotal study accordingly.

Can you let us know your feedback on the below mentioned:
  1. Can we proceed with the pivotal study by considering the above results of pilot study?

  2. Cmax and AUC inf are showing ISCV above 30%. Therefore what could be the conclusion for same?

  3. As per the ratios of test/reference, are their any evaluations required with respect to formulation.

  4. There are 2 subjects data out of 14 in which the concentration data is quite anomalous and not matching with the rest of the 14 subjects data. Would this be the reason for higher ISCV of Cmax and AUC Inf?

  5. If we go by considering the above results for pivotal, what could be the design and an approximate sample size?
Thanks & Regards,
unique_one.


Edit: Category changed. [Helmut]
Anand
☆    

India,
2015-10-09 11:04
(3093 d 12:19 ago)

@ unique_one
Posting: # 15540
Views: 5,842
 

 Pilot Results and Pivotal Design

Dear Unique One,

Please find below response for your reference.

❝ 1. Can we proceed with the pivotal study by considering the above results of pilot study?


Response: Yes, you can proceed for Pivotal BE study.

❝ 2. Cmax and AUC inf are showing ISCV above 30%. Therefore what could be the conclusion for same?


Response: It depends not limited to Physiological conditions to subjects, formulation excipients, in-vitro release, nature of drug etc...

❝ 3. As per the ratios of test/reference, are their any evaluations required with respect to formulation.


Response: Two Crossover design: For considering Cmax ISCV 43.13 sample size required 62 subjects, additionally considered 6 subjects for drop-out & withdrawal. Total 68 subjects.

Partial Replicate: 24 subjects

❝ 4. There are 2 subjects data out of 14 in which the concentration data is quite anomalous and not matching with the rest of the 14 subjects data. Would this be the reason for higher ISCV of Cmax and AUC Inf?


Response: May be.. you can exclude these 2 subjects and run the data & find T/R Ratio, ISCV. Based on that you can conclude.

❝ 5. If we go by considering the above results for pivotal, what could be the design and an approximate sample size?


Response: Please refer Question 3 Response.

Let me know further clarification required,
Regards,
A.Anand,
Asst.Manager,
Bio-Pharmaceutics & Pharmacokinetics(Bio-PK/CPPK)
India


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! [Ohlbe]
pjs
★    

India,
2015-10-09 11:57
(3093 d 11:26 ago)

@ Anand
Posting: # 15541
Views: 5,864
 

 Pilot Results and Pivotal Design

Dear unique_one,

I will slightly disagree with Mr. Anand.

As the published literature suggest cv less than 30% and anomalous data are found in your study for 2 subjects. Try evaluating the data excluding this two subjects.

For which regulatory the submission is intended. If it is for USFDA you should consider AUCinf for the sample size estimation based on your presented data (required n=102). Do a literature search if your drug undergo enterohepatic circulation or not? Is the drug product IR formulation and truncation is possible? Is OGD available? Are you talking about deviating from OGD and intend to conduct RASBE study from the data of pilot study?

Based on the presented data GMR of Cmax is close to unity and AUCt is about 93. I don’t think your formulation team may consider reformulating the drug product.

Kindly provide data excluding two subject and reported intraCV in literature for further consideration.

Hope this helps.

Regards,
pjs
d_labes
★★★

Berlin, Germany,
2015-10-09 15:19
(3093 d 08:04 ago)

@ Anand
Posting: # 15543
Views: 6,487
 

 HVD sample size

Dear Anand,

❝ Response: Two Crossover design: For considering Cmax ISCV 43.13 sample size required 62 subjects, additionally considered 6 subjects for drop-out & withdrawal. Total 68 subjects.


❝ Partial Replicate: 24 subjects


your recommended sample size is based on the assumption of GMR=1 and using conventional ABE as BE decision.
IMHO GMR =1 is not a reasonable choice even if the pilot study came out with a ratio ~1. Highly variable drugs have the feature that the point estimate "jumps" around if study has small sample size.
Therefore I suggest to plan the pivotal study at least with a GMR = 0.95 or even better as the two Laszlo's*) suggest for HVD's with GMR = 0.9.
With the latter one obtains:
library(PowerTOST)
sampleN.TOST(CV=0.4313, design="2x2x2", theta0=0.9)

+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  2x2 crossover
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins        = 0.8 ... 1.25
Null (true) ratio = 0.9,  CV = 0.4313

Sample size (total)
 n     power
154   0.801296


This sample size may be prohibitive high.
Therefore I suggest to go with scaled ABE. Using the EMA recommended method (assuming that you aim for an European submission), i.e. widening of the BE acceptance range, and planning for the partial replicate design one obtains:
sampleN.scABEL(CV=0.4313, design="2x3x3", theta0=0.9)

+++++++++++ scaled (widened) ABEL +++++++++++
            Sample size estimation
---------------------------------------------
Study design:  2x3x3 (partial replicate)
log-transformed data (multiplicative model)
1e+05 studies for each step simulated.

alpha  = 0.05, target power = 0.8
CVw(T) = 0.4313; CVw(R) = 0.4313
Null (true) ratio = 0.9
ABE limits / PE constraints = 0.8 ... 1.25
Regulatory settings: EMA
- CVswitch =  0.3, cap on scABEL if CVw(R) > 0.5
- Regulatory constant = 0.76

Sample size search
 n     power
36   0.7671
39   0.7979
42   0.8228


Since the EMA doesn't allow widening in case of evaluation of AUC and in the light of the astonishing high variability of AUC(0-inf) with additionally a GMR ~0.9 it may be that this PK metric will drive your sample size estimation:
sampleN.TOST(CV=0.3365, design="2x3x3", theta0=0.9)

+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  partial replicate (2x3x3)
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins        = 0.8 ... 1.25
Null (true) ratio = 0.9,  CV = 0.3365

Sample size (total)
 n     power
75   0.812282



*) Laszlo Tothfalusi and Laszlo Endrenyi
"Sample Sizes for Designing Bioequivalence Studies for Highly Variable Drugs"
J. Pharm. Pharmaceut. Sci. (www.cspsCanada.org) 15(1) 73 - 84, 2011

Regards,

Detlew
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