narra1813 ☆ India, 20190810 11:21 (1667 d 16:20 ago) Posting: # 20491 Views: 4,728 

Dear All, By using the only power and sample size how we can calculate the N for NTI molecules. what about the other parameters. Calculating the probability of passing (power) and the sample size (to meet a desired power target) are just two sides of the same coin. One determines the power at a fixed value of n (number of subjects) and the other determines n for a fixed value of power. FDA published a paper that gives the results of the correct simulations; Jiang W, et al, A Bioequivalence Approach for Generic Narrow Therapeutic Index Drugs: Evaluation of the ReferenceScaled Approach and Variability Comparison Criterion, The AAPS Journal, 17(4), 2015. Please provide your valuable suggestion on the same, for my understanding the same. Edit: I deleted another post with identical text. Please follow the Forum’s Policy. I activated the PMfunction and edited your profile. [Helmut] — Regards Narra Narendra Babu 
Helmut ★★★ Vienna, Austria, 20190810 13:23 (1667 d 14:17 ago) @ narra1813 Posting: # 20492 Views: 4,218 

Hi Narra, ❝ By using the only power and sample size how we can calculate the N for NTI molecules. what about the other parameters. As with any other referencescaling method we have to use simulations. The conditions for BE of NTIDs are summarized in this post and the statistical method is given in the FDA’s warfaringuidance. Sample size estimations are implemented in function sampleN.NTIDFDA() of the package PowerTOST since 2013. Example: CV_{wT} = CV_{wR} = 10%, expected T/Rratio 97.5%, desired (target) power 80%.
Let’s explore what happens if T has a higher variability (15%) than R (10%). Abbreviated output.
Note that the FDA wants a 4period full replicate. If you are concerned about blood loss and/or dropouts you may consider a 3period full replicate (TRTRTR). Since that deviates from the guidance, I recommend to initiate a controlled correspondence with the OGD first. Like the first example but for 90% power:
We can also explore deviations from our assumptions (only equal CVs implemented). For the first example, minimum acceptable power 70% (default of the function):
Note the interesting behavior of power with various CVs. If the CV gets smaller, limits get tighter and power drops. On the other hand, if the CV increases, we have wider limits and gain power. If the CV_{wR} >21.42% the additional criterion “must pass 80–125%” becomes increasingly important and power drops. We can also explore which of the three criteria are most important. Again the first example and the estimated sample size 18:
The second example where CV_{wT} > CV_{wR}:
❝ FDA published a paper* … ❝ Please provide your valuable suggestion on the same, for my understanding the same. Hope the above helps.
— 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 
Mahmoud ★ Jordan, 20240206 12:45 (26 d 13:55 ago) @ Helmut Posting: # 23858 Views: 412 

Dear Helmut ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ ❝ what do mean about 'CVcap' = 0.2142 Thank you Mahmoud 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 #5! [Helmut] 
Helmut ★★★ Vienna, Austria, 20240206 14:51 (26 d 11:49 ago) @ Mahmoud Posting: # 23859 Views: 407 

Hi Mahmoud, ❝ what do mean about If the CV_{wR} >21.42% the additional criterion “must pass 80–125%” becomes increasingly important and power drops. It’s not explicitly stated in the FDA’s guidances (therefore, we give it in quotes) but can be easily derived with a little algebra. In a nutshell: Limits are scaled based on \(\small{CV_\text{wR}}\) with the FDA’s regulatory constant \(\small{\theta_0}\) in the first place. But for any \(\small{CV_\text{wR}>21.42\%}\) that would result in implied limits \(\small{\left\{L,U\right\}}\), which are wider than 80.00 – 125.00%. That’s not we want for an NTID.$$\eqalign{ \Delta&=1/0.9\approx 1.11111\\ \sigma_\text{w0}&=0.10\\ \theta_0&=\frac{\log_e\Delta}{\sigma_\text{w0}}\approx1.053595\\ s_\text{wR}&=\sqrt{\log_e(CV_\text{wR}^2+1)}\\ \left\{L,U\right\}&=100\exp(\mp\theta_0\cdot s_\text{wR}) }$$Practically the limits are scaled indeed, but if the study would have passed, additionally inclusion within the conventional 80.00 – 125.00% limits is assessed as well. That’s numerically the same as if scaling would be ‘capped’ at \(\small{CV_\text{wR}=21.42\%}\). If algebra is not your thing, 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 
d_labes ★★★ Berlin, Germany, 20240226 11:54 (6 d 14:46 ago) @ Helmut Posting: # 23882 Views: 145 

Hi Helmut, Hi Mahmoud, please take into consideration that funtions dealing with the FDA method for NTID's have now aliases without FDA in their names. That was implemented since the evaluation methods requested by the FDA are also required by China CDE. The aliases are power.NTID(), sampleN.NTID() , and pa.NTID() .The functions power.NTIDFDA(), sampleN.NTIDFDA() , and pa.NTIDFDA() are deprecated and will be removed in the next release.— Regards, Detlew 