at best half baked [BE/BA News]
Hi John,
You used the wrong emoticon. Correct:
Replicate designs are generally acceptable for HC:
After last June’s meeting László wrote to me “One step ahead, three steps back!”
Some thoughts:
At least no SAS-code is given. Hence, nothing speaks against using
I expect an inflation of the Type I Error very similar to the EMA’s ABEL in the critical region around CVwR 30%. Well done! Papers1,2 published in US-journals ignored out of principle? OK, maybe only Canadian ones count? The two Lászlós reported3 for CVwR 30% a Type I Error of 6.98% already back in 2009…
❝ So they allow a partial replicate as well? The Same as FDA
You used the wrong emoticon. Correct:

Replicate designs are generally acceptable for HC:
Replicated cross-over designs may also be used, where the formulations are tested more than once in the same subjects.
After last June’s meeting László wrote to me “One step ahead, three steps back!”
![[image]](img/uploaded/image388.png)
- The EMA’s upper cap at CVwR 50% (i.e., scaling ends at expanded limits of 69.84 – 143.19%) is arbitrary but at least we have some empiric evidence that it “works” since an acceptance range of 70 – 143% for Cmax (only!) was used in the EU in the 1990s. I don’t think that such an AR was ever acceptable for AUC (very rarely 75 – 133%).
- Where does HC’s upper cap at CVwR 57.40% come from? In the June 2015 proposal it was 50%. A yellow compromise somewhere in between the EMA’s and the FDA’s “implied BE limits” of 62.11 – 161.01% to get “nice” numbers for the expanded limits of 66.7 – 150.0%?
round(100*exp(c(-1, +1)*0.76*sqrt(log(0.574^2+1))), 1)
- I don’t like HC’s strategy of less significant digits than other agencies use. Remember NTIDs? Everywhere else the AR is 90.00 – 111.11% but in Canada (for “critical dose drugs”) it is 90.0 – 112.0% (Eric Ormsby: “More convenient and easier to remember”).
Same here: 100/0.667 ≠ 150.0.
- Hip hip hooray, a mixed effects model! Splendid, I like it.
- By definition the cross-over design is a mixed effects model with fixed and random effects. […] If the mixed model approach is used, parameter constraints should be defined in the protocol. Higher order models must be analysed with the mixed model approach in order to estimate random effects properly.
At least no SAS-code is given. Hence, nothing speaks against using
FA0(1)
. However, I still hold that the partial replicate is a lousy design.- Wonnemann M, Frömke C, Koch A. Inflation of the Type I Error: Investigations on Regulatory Recommendations for Bioequivalence of Highly Variable Drugs. Pharm Res. 2015;32(1):135–43. doi:10.1007/s11095-014-1450-z.
- Muñoz J, Alcaide D, Ocaña J. Consumer's risk in the EMA and FDA regulatory approaches for bioequivalence in highly variable drugs. Stat Med. (early view 28 Dec 2015). doi:10.1002/sim.6834.
- Endrényi L, Tóthfalusi L. Regulatory Conditions for the Determination of Bioequivalence of Highly Variable Drugs. J Pharm Pharmaceut Sci. 2009;12(1):138–49.
free resource.
—
Dif-tor heh smusma 🖖🏼 Довге життя Україна!![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
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Dif-tor heh smusma 🖖🏼 Довге життя Україна!
![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
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- Canada HVDS update jag009 2016-04-20 21:22
- at best half bakedHelmut 2016-04-21 00:43
- Canada HVDS update jag009 2016-04-20 21:22