Shuanghe Regular Spain, 20160307 18:04 Posting: # 16070 Views: 5,137 

Hi All, I was trying to produce sample size plots of full replicate BE for EMA regulation for my colleague, similar to those in this post, that would cover ISCV from 0.1 to 1, GMR from 0.9 to 1, using Helmut's code. I noticed that at certain combinations PowerTOST would produce errors. e.g., with the following values
sampleN.scABEL(alpha = 0.05, targetpower = 0.8, theta0 = 0.91, would produce error Error in if (pwr <= targetpower) cat(n, " ", formatC(pwr, digits = pd, : These error only appear when CV is extremely low so in practice it doesn't matter since no one will use 2x2x4 replicate study for product with ISCV of 10%. I guess that's the reason I never noticed it before. So just for education purpose, can anyone tell me what's going on here? Maybe it's apparent for R gurus but as R novice I have no idea what the message says. According to Detlew, it's not a bug for sure. Edit: Category changed. [Helmut] — All the best, Shuanghe 
Helmut Hero Vienna, Austria, 20160307 18:56 @ Shuanghe Posting: # 16071 Views: 4,377 

Hi Shuanghe, » I noticed that at certain combinations PowerTOST would produce errors. e.g., with the following values »
» sampleN.scABEL(alpha = 0.05, targetpower = 0.8, theta0 = 0.91, » would produce error » Error in if (pwr <= targetpower) cat(n, " ", formatC(pwr, digits = pd, :
» missing value where TRUE/FALSE needed Confirmed. » These error only appear when CV is extremely low so in practice it doesn't matter since no one will use 2x2x4 replicate study for product with ISCV of 10%. Right. » […] can anyone tell me what's going on here? Maybe it's apparent for R gurus but as R novice I have no idea what the message says. At such a low CV you could use sampleN.TOST() to get a first idea:library(PowerTOST) Looking at the source (type sampleN.scABEL in the console) we findnmin < 6 so I guess it could be possible. Needs some additional errortrapping. Detlew? — All the best, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
yjlee168 Senior Kaohsiung, Taiwan, 20160307 20:15 (edited by yjlee168 on 20160307 20:32) @ Shuanghe Posting: # 16072 Views: 4,353 

Hi Shuanghe, » would produce error » Error in if (pwr <= targetpower) cat(n, " ", formatC(pwr, digits = pd, :
» missing value where TRUE/FALSE needed The error messages implied that pwr is not a number at all. Maybe it is due to failing to compute. The other parameter targetpower has been given by user (which is 0.8 in your code). So it should not be the cause of the error. But we still need to wait for Detlew's response.— All the best, Yungjin Lee bear v2.8.3: created by Hsinya Lee & Yungjin Lee Kaohsiung, Taiwan http://pkpd.kmu.edu.tw/bear Download link (updated) > here 
d_labes Hero Berlin, Germany, 20160308 08:50 (edited by d_labes on 20160308 10:23) @ Shuanghe Posting: # 16074 Views: 4,254 

Hi All, » I noticed that at certain combinations PowerTOST would produce errors. e.g., with the following values » sampleN.scABEL(alpha = 0.05, targetpower = 0.8, theta0 = 0.91,
» CV = 0.1, design = "2x2x4", regulator = "EMA") » » would produce error » Error in if (pwr <= targetpower) cat(n, " ", formatC(pwr, digits = pd, :
» missing value where TRUE/FALSE needed Confirmed. My suggestion: Contact the maintainer of that ugly R package and throw the code back in his face . All jokes aside: Thank you all for bug hunting. The reason identified was a too low starting value n0=2 which leaves no degrees of freedom for the CI. Exactly what Helmut suspected. Will be corrected in the next version, coming soon. I promise . BTW: All other scaled ABE sample size functions also suffer from the same potential bug . Shit. — Regards, Detlew 
d_labes Hero Berlin, Germany, 20160309 18:43 @ Shuanghe Posting: # 16081 Views: 4,139 

Dear Shuanghe, dear All! Bug correction is on the way via CRAN. Should be available next days . — Regards, Detlew 
Astea Regular Russia, 20160324 19:34 @ Shuanghe Posting: # 16135 Views: 3,437 

Dear all! I've noted that sample size, estimated with the help of PowerTOST's scABEL, depends on the difference between CV_T and CV_R. Suppose we have a HVD with unknown CV (or CV is known in literature but it ranges widely through the studies). There could be a situation when CV_T and CV_R do not coincides. For example, CV_R=0.3 and CV_T=0.4. Then basing on the sampleN.scABEL for theta0=0.9 we need 48 subjects. But if we plan replicate study on the basis of CV=0.3 we get only 34 subjects. Moreover planing replicate study without scaling (sampleN.TOST) we get only 40 subjects. Here I post the graph for illustration purposes (scABEL2 denotes sampleN.scABEL(CV=c(CV_T, 0.3), theta0=0.9, design="2x2x4")) Do I undestand correctly? If it so then there are always exist a miserable possibility that calculated by scABEL with CV_T=CV_R sample size would be insufficient? 
Helmut Hero Vienna, Austria, 20160325 14:23 @ Astea Posting: # 16139 Views: 3,423 

Hi Astea, » I've noted that sample size, estimated with the help of PowerTOST's scABEL, depends on the difference between CV_T and CV_R. Correct. » Suppose we have a HVD with unknown CV (or CV is known in literature but it ranges widely through the studies). There could be a situation when CV_T and CV_R do not coincides. Correct as well. » Do I undestand correctly? If it so then there are always exist a miserable possibility that calculated by scABEL with CV_T=CV_R sample size would be insufficient? Yes. Shit might happen.
Note that ABE is bijective (more about that later): If T = R → R = T ∧ if T ≠ R → R ≠ T. The original idea of referencescaling goes back to a proposal by Boddy et al.^{1} for the 2×2×2 design and at a workshop^{2} dedicated to HVD(P)s two recommendations were given, namely For some highly variable drugs and drug products, the bioequivalence standard should be modified by changing the bioequivalence limits while maintaining the current confidence interval at 90% These suggestions lead to the referencescaling model: ln(0.80) / σ_{w0} ≤ [ln(μ_{T}) – ln(μ_{R})] / σ_{wR} ≤ ln(1.25) / σ_{w0} where the switching variability σ_{w0} is a fixed constant (specific for the agency).Note that RSABE is not bijective like ABE. There is nothing like “testscaled” ABE. Only if σ_{wT} ≡ σ_{wR}, you could switch from to [ln(μ_{T}) – ln(μ_{R})] to [ln(μ_{R}) – ln(μ_{T})] and get the same outcome. Statistically dissatisfying but it still makes sense: Only the Reference product has a documented history of safety and efficacy (phase III/IV). Seen and Grieve^{3} argued that is not reasonable to assume heterogenicity in bioequivalence: Why would an investigator plan a trial with the object of proving equality of two formulations if the variances were believed different? I’m not so sure. Sometimes the originator is well aware that changing the manufacturing process would require a very expensive BEstudy (even by applying RSABE; see this post for an example) and prefers to keep the manufacturing line “alive” as long as possible (“If it ain't broke, don't fix it”). Generic companies for ages are facing the problem to manufacture a product which is “equally bad” as the reference. Generally they don’t have last century’s machinery. Remember some PPIs (omeprazole, pantoprazole, lansoprazole)? The enteric coating of the originators’ products was lousy; some ABEstudies with extreme sample sized passed only by luck (subjects after R with very low concentrations and erratic profiles → extremely high CVi_{ntra} → inflated CI), many studies failed, some companies simply gave up.Coming back to your question:
— All the best, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
Astea Regular Russia, 20160327 21:07 @ Helmut Posting: # 16144 Views: 3,227 

Dear Helmut! I am very grateful for your detailed answer! » Whenever you assume a CV_{wR} keep the (maybe counterintuitive) behavior of power in ABEL in mind. Are there some general sound advices how to plan the study with SCABE? As an example, on the basis of literature data CV of some drug ranges from 32 % to 46 %. If we plan sample size basing on the highest value we would get the less number! What should we prefer? 
Helmut Hero Vienna, Austria, 20160328 00:42 @ Astea Posting: # 16147 Views: 3,236 

Hi Astea, » I am very grateful for your detailed answer! And I’m grateful for interesting questions! (see my signature) » » Whenever you assume a CV_{wR} keep the (maybe counterintuitive) behavior of power in ABEL in mind. » » Are there some general sound advices how to plan the study with SCABE? By counterintuitive I meant power curves for different CVs (while keeping the the T/Rratio and sample size constant) in ABEL. In ABE it is straightforward: Higher CV → wider CI → lower power → increase the sample size to keep power. Hence, if you want to be on the safe side, assume a higher CV (or the upper CL of an estimated CV). I will explore your example for ABEL below. » As an example, on the basis of literature data CV of some drug ranges from 32 % to 46 %. If we plan sample size basing on the highest value we would get the less number! Let’s assume CV 32%, T/R 0.9, target power 80%, 4period full replicate for the EMA’s ABEL: If the CV decreases, power increases. That’s similar to ABE. But if the CV increases, power increases as well because the acceptance range will be wider and a smaller sample size would be sufficient (yes, you are right!). This increase ends at 50% because the scaling ends here. Any higher CV will decrease power again. Starting here, ABEL – apart from the additional PErestriction – behaves like ABE. Now let’s assume CV 46%: With lower CVs we will loose power for the given sample size. Whether such a loss is acceptable is another story (at 32%: 73.5%). » What should we prefer? I would say for any CV the rule for ABE given above reverses: If you want to be on the safe side, assume a lower CV (or the lower CL of an estimated CV). If you have good reasons that the CV will not drop much below 50%, use the ABErule again. — All the best, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
mittyri Senior Russia, 20160328 21:54 (edited by mittyri on 20160328 22:26) @ Helmut Posting: # 16149 Views: 3,577 

Hi Helmut and Astea, "Dear volunteers of the sequence 2 (TRTR), please take some grapefruit juice before dosing on period 4" Assumptions: Power: at least 90% Alpha: 0.025% CVWR: as low as possible CVWT: as much as possible GMR: no better than 90% And you don't have any profit from ABEL! — Kind regards, Mittyri 