BE: study populations [Dissolution / BCS / IVIVC]
Dear Jaime!
Just a few comments. IMHO it's no good idea to stratify groups for the phenotype, because drop-outs will change the SM (slow metabolizers) / FM (fast metabolizers)-ratio in such a way, that the treatment effect (which is based on group's means) will be biased.
Expanding your example:
Parallel design (2 groups of 30 subjects each; 24 FM (80%) and 6 SM (20%) in each group), responses (FM = 1, SM = 10)
Complete data set: GMT 1.58, GMR 1.58, GMR 100%
1 Drop out (Reference group, SM): GMT 1.58, GMR 1.49, GMR 1.07%
1 Drop out (Reference group, FM): GMT 1.58, GMR 1.61, GMR 0.98%
Therefore IMHO mixed groups should be avoided; only FM should be studied instead.
If stratified groups are to be used (i.e., due to a regulatory requirement), I would suggest laying down a procedure in the SAP excluding a subject of the same phenotype of the repective other group in a predefined blinded manner in order to keep the SM/FM ratio balanced. However, such a method is suboptimal.
❝ If the drug is subjected to polymorphism, a BE study should be performed
❝ in geno-/phenotyped subjects, if:
❝ - a parallel design is used (e.g., for drugs with a long half-life);
❝ groups should be stratified for the respective geno-/phenotype.
❝ Example: if 20% of the population are slow/poor metabolisers and 80%
❝ fast/extensive ones, both groups (treated with either test or reference)
❝ should consist of the same percentage of SMs/FMs. Otherwise it would be
❝ impossible to calculate the treatment effect properly.
Just a few comments. IMHO it's no good idea to stratify groups for the phenotype, because drop-outs will change the SM (slow metabolizers) / FM (fast metabolizers)-ratio in such a way, that the treatment effect (which is based on group's means) will be biased.
Expanding your example:
Parallel design (2 groups of 30 subjects each; 24 FM (80%) and 6 SM (20%) in each group), responses (FM = 1, SM = 10)
Complete data set: GMT 1.58, GMR 1.58, GMR 100%
1 Drop out (Reference group, SM): GMT 1.58, GMR 1.49, GMR 1.07%
1 Drop out (Reference group, FM): GMT 1.58, GMR 1.61, GMR 0.98%
Therefore IMHO mixed groups should be avoided; only FM should be studied instead.
If stratified groups are to be used (i.e., due to a regulatory requirement), I would suggest laying down a procedure in the SAP excluding a subject of the same phenotype of the repective other group in a predefined blinded manner in order to keep the SM/FM ratio balanced. However, such a method is suboptimal.
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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:
- biological variation, IVIVC satya 2007-08-16 22:24
- biological variation, IVIVC Jaime_R 2007-08-17 13:17
- biological variation, IVIVC satya 2007-08-17 16:07
- BE: study populations Jaime_R 2007-08-17 17:37
- BE: study populationsHelmut 2007-11-22 14:44
- BE: study populations Jaime_R 2007-08-17 17:37
- biological variation, IVIVC satya 2007-08-17 16:07
- biological variation, IVIVC Jaime_R 2007-08-17 13:17