Helmut ★★★ Vienna, Austria, 20240731 15:16 (104 d 18:03 ago) Posting: # 24112 Views: 4,483 

Dear all, M13A Bioequivalence for ImmediateRelease Solid Oral Dosage Forms was adopted on 23 July 2024 and is thus, in Step 4 (final). It was published today. The draft (Step 2 of 20 December 2022) is no more linked on the ICH’s website but is – as of today – still available.I suggest that we discuss what has changed (the supporting Q&A document might give hints why) and the impact on future studies. I start with my favorite, the dreadful GroupbyTreatment interaction.
In a singlesite study, dosing subjects in groups may be unavoidable for logistic reasons. The following measures should be considered to minimize group effects:
Assign an equal sample size to each group when feasible, e.g., when healthy subjects are enrolled. A clear improvement. However, in a metaanalysis of more than 320 studies we found an average loss of ≈6% power by using this model compared to the conventional one (without groupterms).* In the meantime I collected data of more studies (see this post). Although I’m not happy with the last sentence of this section, we will have to live with it. I’m not sure what is meant by »calculation of descriptive statistics by group«. Geometric means of PK metrics (irrespective of treatment), separate for treatments, or point estimates by the conventional model? Post hoc analyses regularly lead to endless and – quite often fruitless – discussions. Be prepared for them in ≈5% of your studies (i.e., at the level \(\small{\alpha}\) of the \(\small{G\times T}\)test; see this article).
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Helmut ★★★ Vienna, Austria, 20240731 16:19 (104 d 17:00 ago) @ Helmut Posting: # 24115 Views: 4,182 

Dear all, some more changes I [sic] think being relevant.
I guess the 800 kcal in the draft were introduced by someone numerically handicapped. Posture control is applied for ages anyhow.
The requirement of \(\small{AUC_{{0}\text{t}}\ge 80\%\,AUC_{0\infty}}\) appeared out of blue skies in the APV guideline 37 (‼) years ago without any justification.^{1} Copy & paste in guidelines (EMA, WHO, Health Canada, ANVISA, Japan, and this one)? It was never required by the FDA. This requirement is questionable because at \(\small{24\times t_\text{max}}\) absorption is practically complete^{3,4} (depending on the half life we have at \(\small{2\times t_\text{max}\text{:}\approx97.5\%}\) absorbed, at \(\small{3\times t_\text{max}\text{:}\approx99.6\%}\), and at \(\small{4\times t_\text{max}\text{:}\approx99.9\%}\)). After that we see only elimination (and distribution in a two compartment model), which is (are) drugspecific and thus, simply not relevant for the comparison of formulations. It can be shown that the ≥80% requirement translates to \(\small{>4\times t_\text{max}\to\,>99.99\%}\), which is extremely conservative, and, IMHO, not justified for IR products. Example: Absorption t_{½} 1 h, elimination t_{½} 4 h, sampling according to the guideline four times the elimination half life. In a nutshell: A »reliable estimate of the extent of exposure« could readily be »ensured« if the sampling would end (much) earlier. For a given number of sampling times points it would be better to have more around t_{max}…
t_{max} was required by e.g., the EMA, the WHO, and in Australia.
The method of calculating \(\small{AUC_{0\infty}}\) is nowhere given. Should it be the simple \(\small{AUC_{0\text{t}}+C_\text{t}/\lambda_\text{z}}\) or can it be based on the estimated last concentration, i.e., \(\small{AUC_{0\text{t}}+\widehat{C_\text{t}}/\lambda_\text{z}}\) – as recommended in the Canadian guidance, publications, and textbooks (see this article)? IMHO, it should unambiguously stated in the protocol. What’s the purpose of reporting the arithmetic mean for PK metrics (C_{max}, AUC, pAUC) following a lognormal distribution? At least the linear trapezoidal method is only given as an example. The linearup logarithmicdown trapezoidal method is less biased, especially if there are deviations from the sampling schedule and/or concentrations are missing (see this article). IMHO, the method should not only be reported but already stated in the protocol. If in a subject t_{last} is not the same after all treatments, the T/Rratio of AUC_{(0–t)} will unavoidably be biased. Alas, an unbiased approach^{5} did not make it to the GL. The swing \(\small{100\frac{C_\text{max}C_\text{min}}{C_\text{min}}}\) is a terrible PK metric with extreme variability (esp. in case of low accumulation).^{6} Given, only to be reported. But for what purpose? »[…] applicants should […] demonstrate the attainment of steadystate.« Regrettably it is not stated how that should be done. For the problems see this article. Concentrations < LLOQ ⇒ 0. I beg your pardon? After a dose we know only one thing for sure: The concentration is not zero.^{7} »Values below the LLOQ are to be omitted from the calculation of k_{el} and t_{1/2}.« What else? Try a loglinear regression with a ‘zero concentration’. Good luck.
Testing for the effects is ridiculous. AFAIK, currently required only by Health Canada – including an ‘explanation’ of significant ones. The outcome of a comparative BA study is dichotomous. Either it passed (BE) or not… The sequence and formulation effects are not relevant and the period effects cancel out.
I miss a statement that equal variances must not be assumed (i.e., that the confidence interval has to be calculated by the Welchtest instead of by the ttest). In case of unequal variances and/or group sizes the latter is liberal (anticonservative). To be continued… Feel free to chime in.
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
mittyri ★★ Russia, 20240805 23:08 (99 d 10:11 ago) @ Helmut Posting: # 24136 Views: 3,716 

Dear Helmut, ❝ – Final (page 11) ❝ For singledose studies, the following PK parameters should be tabulated for each subjectformulation combination: 1) primary parameters for BE analysis: AUC_{(0–t)}, C_{max}, and, where applicable, early exposure parameters (see Section 2.1.8.3), and 2) additional parameters for analysis to assess the acceptability of the bioequivalence study: AUC_{(0–inf)}, AUC_{(0–t)}/AUC_{(0–inf)}, t_{max}, k_{el}, and t_{1/2}. For singledose studies, AUC_{(0–t)} should cover at least 80% of AUC_{(0–inf)}. If the AUC_{(0–t)}/AUC_{(0–inf)} percentage is less than 80% in more than 20% of the observations, then the validity of the study may need to be discussed in the submission. ICH group was copying many things from EMA BE Guideline (and this is good). But what prompted the ICH group to replace the Residual Area term with Ratio ? Was there some kind of dissatisfaction with the 80% coverage criterion and the ambiguity surrounding Residual Area? I was always wondering about this kind of discussion. One more theme for sensitivity analysis? — Kind regards, Mittyri 
Helmut ★★★ Vienna, Austria, 20240806 00:13 (99 d 09:06 ago) @ mittyri Posting: # 24137 Views: 3,693 

Hi Mittyri, ❝ ICH group was copying many things from EMA BE Guideline (and this is good). ❝ But what prompted the ICH group to replace the Edit 1: Perhaps the members were not familiar with what is given in the output of PK software (Phoenix WinNonlin, PKanalix, PKNCA (), ncappc (), NonCompart (), ncar (), Pumas (Julia), …):
Since the ‘percentage covered’ (\(\small{100\times AUC_{{0}\text{t}}/AUC_{0\infty}}\)) is not part of the output, we have to set up any of these transformations (terminology used by the first three goodies above):
AUC_%Covered_obs and AUC_%Covered_pred we have to live with it.An example of the setup in Phoenix WinNonlin (at the bottom the Edit 2: I realized that the guideline does not require a breakdown by treatment but »… 20% of the observations …« Therefore: — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
BEQool ★ 20240909 07:48 (65 d 01:31 ago) @ Helmut Posting: # 24191 Views: 2,069 

Hello all, ❝ – Final (page 12) ❝ Randomised, nonreplicate, crossover design studies should be analysed using an appropriate parametric method, e.g., general linear model (GLM) or mixed model. ❝ […] The mixed model likely was a concession made to the FDA and Health Canada, the only agencies currently requiring it. So we can either put subject as a fixed or random effect? But then the following text comes up: "The primary statistical analyses should include all data for all subjects who provide evaluable data for both the test and comparator products." And also in Q&A document: In a 2way crossover design, if data from one period are excluded, the subject should not be included in the statistical analysis […] I am confused, if I understand well, we should all treat subject as a fixed effect? Regards BEQool 
Helmut ★★★ Vienna, Austria, 20240909 09:04 (65 d 00:15 ago) @ BEQool Posting: # 24192 Views: 2,074 

Hi BEQool, ❝ I am confused, if I understand well, we should all treat subject as a fixed effect? In a 2×2×2 crossover with subject(s) missing in one period you get (apart from a slight difference in the n^{th} figure, which is not relevant) the same result for a mixed effects model with all subject(s) and a fixed effects model excluding the subject(s) with missings. If you exclude the subject(s) with missings, a mixed effects model will given you essentially the same result than a fixed effects model. Quite often the differences are at the numerical resolution of the software. Since the EMA implemented ICH M13A already (effective 25 January 2025; see this post), you could use any. However, I would still use a mixed effects model for the FDA and Health Canada and a fixed effects model for all other agencies. We don’t want to confuse assessors who are used to what they required for ages. There is one advantage of a mixed effects model: Apart from the withinsubject subject CV you get additionally the betweensubject subject CV. At least nice to know. A simulation (mixed effects models in are a beast). I give the point estimate and confidence interval in percent with five decimal places for comparison. If rounded to two decimal places, differences for the balanced and imbalanced cases will disappear (note that ICH M13A is silent about rounding).
Residual (in R and Phoenix/WinNonlin) is equivalent to DDFM = CONTAIN and containment , respectively.Lengthy script for simulating a 2×2×2 crossover. Defaults: alpha 0.05 (90% CI), BElimits 0.8–1.25, T/Rratio 0.95. power ≥ 0.8. Optionally specification of period and/or carryovereffects.
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
BEQool ★ 20240909 12:18 (64 d 21:01 ago) @ Helmut Posting: # 24193 Views: 2,043 

Hello Helmut, thank you for a wellexplained answer with specific examples. ❝ In a 2×2×2 crossover with subject(s) missing one period you get (apart from a slight difference in the n^{th} figure, which is not relevant) the same result for a mixed effects model with all subject(s) and a fixed effects model excluding the subject(s) with missings. If I am not wrong and if I understand correctly, based on your examples with incomplete data (periods missing), the difference between subject as a fixed effect and subject as a mixed effect is more than a slight difference (instead the difference is observed in the 1st decimal place)?❝ However, I would still use a mixed effects model for the FDA and Health Canada and a fixed effects model for all other agencies. We don’t want to confuse assessors who are used to what they required for ages. ❝ There are differences for incomplete data (period missing) – not only for the CI but also the PE. However, in such a case the subject should be excluded according to M13A and its Q&A anyway. Yes I was most interested in these incomplete data . So basically if you have incomplete data set (just periods missing) you should exclude the subject from the analysis and then the result (PI and 90%CI) would be almost the same (regardless of subject as a fixed or mixed effect)? Furthermore, this result would again be almost the same as if we wouldnt exclude the subject from the analysis and just used subject as a fixed effect? 
Helmut ★★★ Vienna, Austria, 20240909 13:13 (64 d 20:06 ago) @ BEQool Posting: # 24194 Views: 2,011 

Hi BEQool, ❝ thank you for a wellexplained answer with specific examples. Welcome. No big deal because I had the simulationscript already. ❝ Doesnt a model with subject as a fixed effect automatically exlude subjects with missing periods (in 2x2x2 design) from the analysis? Or am I wrong? Of course, you are right. ❝ If I am not wrong and if I understand correctly, based on your examples with Yes. That’s why I wrote: ❝ ❝ There are differences for incomplete data (period missing) – not only for the CI but also the PE. ❝ Yes I was most interested in these Yep. P.S.: I modified the script in such a way that you can specify the number of dropouts and subjects with missings. Try this:
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
BEQool ★ 20240910 09:35 (63 d 23:44 ago) @ Helmut Posting: # 24196 Views: 1,929 

Hello Helmut, thank you for the answers. I just wanted to point out that, if I understand correctly, in ICH M13A basically nothing changes (PE and 90%CI) compared to EMA guideline on how to perform an analysis when periods are missing (because subject is a fixed factor) but compared to FDA guideline (subject as a random factor) PE and 90% CI change a little because now subjects with missing periods have to be excluded from the analysis (and according to FDA guideline you shouldnt exclude them)? ❝ P.S.: I modified the script in such a way that you can specify the number of dropouts and subjects with missings. Try this: ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ Interesting, isn’t it? Thanks, interesting indeed Regards BEQool 
Helmut ★★★ Vienna, Austria, 20240910 10:12 (63 d 23:07 ago) @ Helmut Posting: # 24197 Views: 1,930 

Hi BEQool, partly updated script (change below # aggregate results ). Then:
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Helmut ★★★ Vienna, Austria, 20240805 14:53 (99 d 18:26 ago) @ Helmut Posting: # 24132 Views: 3,823 

Dear all, the story continues.
Why the weird phrase »AUC_{(0–72h)} may be used as AUC_{(0–t)}« and not keep what was stated in the draft or simply “AUC_{(0–72h)} may be used instead of AUC_{(0–t)}”? Contrary to the guidances of the FDA and Health Canada, nothing is stated about rounding of the confidence interval. Based on a clinically relevant difference \(\small{\Delta=20\%}\) we get the BElimits in the multiplicative model by $$\small{\left\{\theta_1,\theta_2\right\}=\left\{100\left(1\Delta\right),100\left(1\Delta\right)^{1}\right\}=\left\{80\%,125\%\right\}}$$ These limits are exact, i.e., a study with a CI of 79.995 –125.005% would fail. Since the limits are stated as 80.00 – 125.00%, does that imply that we have to round to two decimal places? Then the same study would pass* and – slightly – inflate the Type I Error.
In studies with more than two treatment arms (e.g. a three period study including two references, one from EU and another from USA […]), the analysis for each comparison should be conducted excluding the data from the treatments that are not relevant for the comparison in question. Very similar recently the FDA:^{3,4}In BE studies with more than two reference treatment arms (e.g., a threeperiod study including two references, one from the European Union (EU) and another from the United States […]), the BE determination should be based on the comparison between the relevant test and reference products, using only the data from those products. The BE analysis for this comparison should be conducted excluding the data from the nonrelevant treatment(s) — for example, in a BE study with a T product, an EU reference product, and a U.S. reference product, the comparison of the T product to the U.S. reference product should be based on an analysis excluding the data from the EU reference. For details see this article, a presentation by David Brown (MHRA),^{5} and the Q&A.^{6}
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
mittyri ★★ Russia, 20240805 22:42 (99 d 10:37 ago) @ Helmut Posting: # 24135 Views: 3,732 

Dear Helmut, ❝ BE should be determined based on the overall treatment effect in the whole study population. The statistical model should take into account the multigroup nature of the BE study, e.g., by using a model including terms for group, sequence, sequence × group, subject within sequence × group, period within group and formulation. The group × treatment interaction term should not be included in the model. However, applicants should evaluate potential for heterogeneity of treatment effect across groups and discuss its potential impact on the study data, e.g., by investigation of group × treatment interaction in a supportive analysis and calculation of descriptive statistics by group. "France lost the battle but she has not lost the war!" I hope that we can see other improvements in the future. By the way
— Kind regards, Mittyri 
Helmut ★★★ Vienna, Austria, 20240806 00:29 (99 d 08:50 ago) @ mittyri Posting: # 24138 Views: 3,696 

Hi Mittyri, ❝ ❝ The statistical model should take into account the multigroup nature of the BE study, e.g., by using a model including terms for group, sequence, sequence × group, subject within sequence × group, period within group and formulation. The group × treatment interaction term should not be included in the model. However, applicants should evaluate potential for heterogeneity of treatment effect across groups and discuss its potential impact on the study data, e.g., by investigation of group × treatment interaction in a supportive analysis and calculation of descriptive statistics by group. ❝ ❝ I hope that we can see other improvements in the future. Unlikely. ICH guidelines regularly are not updated for 20+ years (e.g., E3 of 1995, E8 of 1997, E9 of 1998). ❝ – do you know the reason to include period within group and formulation? As far as I remember, Model I and Model II included Period(Group) factor only. Models as stated by the FDA and used by the usual suspects (see this post):
I don’t understand what is meant by »investigation of group × treatment interaction in a supportive analysis«. Assess for BE by Model II and then the \(\small{G\times T}\) interaction by Model I? We will find a significant interaction in ≈ 5% of studies (i.e., at the level \(\small{\alpha}\) of the test). Lengthy and fruitless discussions expected. ❝ – What kind of descriptive statistics is expected? Everything above BE section stratified by group? I think so. ❝ What are the consequences of this evaluation of heterogeneity? Is it possible that assessor will be unhappy with the statistics of some group comparing to others? Since no tests are suggested (eyeball desc stat by group comparison?), … Even if an assessor would calculate the confidence interval of groups separately, likely they would overlap due to the limited sample sizes. So what? A recent example (4 period full replicate design): ❝ … any evidence provided post hoc are weak arguments Even not acceptable: Section 2.2.3.1 (page 11)
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Helmut ★★★ Vienna, Austria, 20240808 13:57 (96 d 19:22 ago) @ Helmut Posting: # 24142 Views: 3,414 

Dear all, although the ICH’s website states that M13A is in Step 5 (Implementation), this is not exactly correct. The guideline is in Step 4 (Final) and its implementation will take some time and differ between regions. There is no deadline and no obligation for an agency to implement it at all. As an example the status of M10 Bioanalytical Method Validation and Study Sample Analysis (Step 4 on 24 May 2022) as of today: $$\small{\begin{array}{llcll} \phantom{000000}\textsf{Ageny} & \phantom{00000}\textsf{Region} & \textsf{Step} & \phantom{0000000}\textsf{Status}& \phantom{000000i}\Delta_\text{t}\\\hline \textbf{ANVISA} & \text{Brazil} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) & \text{Implementation process} & \phantom{0000000}\\ \textbf{COFEPRIS} & \text{Mexico} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) &\text{Not yet implemented} & \phantom{0000000}\\ \textbf{EC} & \text{Europe} & \color{Green}5 &\text{21 January 2023} & \text{8 months, 29 days}\\ \textbf{EDA} & \text{Egypt} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) &\text{Implementation process} & \phantom{0000000}\\ \textbf{FDA} & \text{United States} & \color{Green}5 &\text{7 November 2022} & \text{6 months, 15 days}\\ \textbf{HSA} & \text{Singapore} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) & \text{Implementation process} & \phantom{0000000}\\ \textbf{HC} & \text{Canada} & \color{Green}5 & \text{20 January 2023} & \text{8 months, 28 days}\\ \textbf{MFDS} & \text{Republic of Korea} & \color{Green}5 &\text{26 October 2023} & \text{1 year, 6 months, 3 days}\\ \textbf{MHLW/PMDA} & \text{Japan} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) & \text{Not yet implemented} & \phantom{0000000}\\ \textbf{MHRA} & \text{UK} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) & \text{Implementation process} & \phantom{0000000}\\ \textbf{NMPA} & \text{China} & \color{Green}5 & \text{29 July 2023} & \text{1 year, 3 months, 3 days}\\ \textbf{SFDA} & \text{Saudi Arabia} & (\color{Red}4\color{Black}\to \color{Green}5\color{Black}) & \text{Not yet implemented} & \phantom{0000000}\\ \textbf{Swissmedic} & \text{Switzerland} & \color{Green}5 & \text{25 May 2022} & \text{1 month, 1 day}\\ \textbf{TFFA} & \text{Chinese Taipei} & \color{Green}5 & \text{30 May 2023} & \text{1 year, 1 month, 5 days}\\ \end{array}}$$ In seven of the 14 regions the guideline is implemented, in four the implementation process is ongoing, and in three it has not even started – after more than two years. It might even be that Mexico, Japan, and Saudia Arabia decided against implementation… If you have nothing better to do, check the status of M9 Biopharmaceutics Classification Systembased Biowaivers (Step 4 on 20 November 2019). — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Helmut ★★★ Vienna, Austria, 20240809 11:45 (95 d 21:35 ago) @ Helmut Posting: # 24145 Views: 3,289 

Dear all, what I wrote above is wrong. According to the ICH:
Although a guideline is in implementation, it is not necessarily implemented in all regions. Even in regions where a guideline was implemented, it might lead into trouble. If one uses the link to the EMA’s BMV guideline of 2011, it states unambiguously that it has been superseded by the ICH’s M10. However, the FDA’s guidance of 2018 is still accessible and the M10 implemented guidance of 2022 is somewhere else. That’s a trap. Edit: M13A was adopted by the EMA’s CHMP on 25 July 2024 and will be effective with 25 January 2025 (see this post for details). — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Helmut ★★★ Vienna, Austria, 20240906 10:04 (67 d 23:15 ago) @ Helmut Posting: # 24188 Views: 2,235 

Dear all, a tricky part.
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 