Bioequivalence and Bioavailability Forum • Inter-subject variability in Full replicate design

MGR
★

India,
2021-09-30 09:35
(932 d 00:33 ago)

Posting: # 22605
Views: 2,436

Inter-subject variability in Full replicate design [RSABE / ABEL]

Dear All,

Need help on formula/procedure to find out the Intersubject Variability for a Full replicate design using SAS.

Based on the Program given in the progesterone guideline below:

PROC MIXED

 data=pk;

 CLASSES SEQ SUBJ PER TRT;

 MODEL LAUCT = SEQ PER TRT/ DDFM=SATTERTH;

 RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G;

 REPEATED/GRP=TRT SUB=SUBJ;

 ESTIMATE 'T vs. R' TRT 1 -1/CL ALPHA=0.1;

 ods output Estimates=unsc1;

 title1 'unscaled BE 90% CI - guidance version';

 title2 'AUCt';

As there is no subj(seq) in the random statement, I am not able to calculate the inter-subject variabilities for test and reference treatments. Please help me with this calculation.

But when I use the proc varcomp procedure in SAS, I am able to generate the Variabilities (Inter and Intra) for test and reference treatments. My doubt is that whether it is acceptable by FDA regulatory?

Thanks in Advance,

—
Regards,
MGR

ElMaestro ★★★ Denmark, 2021-09-30 16:04 (931 d 18:04 ago) @ MGR Posting: # 22606 Views: 2,129	Inter-subject variability in Full replicate design Post reply
	Hi MGR, ❝ RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G; Once you've run the model, the G matrix holds your between-subject variability. I am not a SAS user, so the syntax for printing and processing G is outside my area of competence (like pretty much anything is). — Pass or fail! ElMaestro

Helmut
★★★

Vienna, Austria,
2021-09-30 17:25
(931 d 16:43 ago)

@ MGR
Posting: # 22607
Views: 2,238

Inter-subject variability in Full replicate design

Post reply

Hi MGR,

like ElMaestro I’m not a SASian and my knowledge is limited.

❝ […] I am not able to calculate the inter-subject variabilities for test and reference treatments. Please help me with this calculation.

With the EMA’s example ‘Data set I’ (download CSV) you should get sumfink like:

Covariance Parameter Estimates Cov Parm Subject Group Estimate FA(1,1) SUBJ 0.8530 FA(2,1) SUBJ 0.8284 FA(2,2) SUBJ 8.339e-07 Residual SUBJ TRT R 0.2021 Residual SUBJ TRT T 0.1174

In Phoenix/WinNonlin slightly different terms.

Final variance parameter estimates: lambda(1,1)_11 0.852995 lambda(1,2)_11 0.828407 lambda(2,2)_11 8.33919e-007 Var(PER*TRT*SUBJ)_21 0.202118 Var(PER*TRT*SUBJ)_22 0.117394

The first two lines give \(\small{\widehat{s_\textrm{bR}^2}}\) and \(\small{\widehat{s_\textrm{bT}^2}}\) and the last two \(\small{\widehat{s_\textrm{wR}^2}}\) and \(\small{\widehat{s_\textrm{wT}^2}}\). Ignore the third, which is the Subject-by-Formulation Interaction. Then as usual \(\small{100\sqrt{\exp \left ( \widehat{s_{\ldots}^2} \right )-1}}\).
Here \(\small{CV_\textrm{bR}=116.0\%,\;CV_\textrm{bT}=113.6\%,\;CV_\textrm{wR}=47.3\%,\;CV_\textrm{wT}=35.3\%}\).

As ElMaestro wrote, you can get the estimated between-subject variances also from Col1 of the estimated G matrix, where the 1^st Row is for R and 2^nd for T.

❝ But when I use the proc varcomp procedure in SAS, I am able to generate the Variabilities (Inter and Intra) for test and reference treatments.

Out of curiosity: Do they are agree with the results of Proc Mixed as outlined above?

❝ My doubt is that whether it is acceptable by FDA regulatory?

The between-subject variabilities are not required for RSABE (in the FDA’s Summary Table 3B you have to give only the within-subject variance and standard deviation of the reference).

[image]

For ABE (Table 3A) variances are not required at all.

Post 22,000… :-D

—
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