Essar ● 20060112 05:47 (6844 d 07:24 ago) Posting: # 50 Views: 29,272 

I want to know abt the basic BE designs...can you suggest me some reference (preferably something on the net). i'm pretty much confused...2way crossover, 2 period, 2 sequence, replicate, parallel...could not understand a word. Suggest me some reference. The only thing I can understand is fed and fasting (this must give you an idea abt my illeteracy level) 
Helmut ★★★ Vienna, Austria, 20060112 19:38 (6843 d 17:33 ago) @ Essar Posting: # 51 Views: 26,967 

Hello Essar, at least the basics of bioequivalence are not that complicated ❝ I want to know abt the basic BE designs...can you suggest me some reference (preferably something on the net). i'm pretty much confused...2way crossover, 2 period, 2 sequence, replicate, parallel...could not understand a word... Ok, BE gives us information about the performance (generally extent [AUC] and rate [C_{max}/t_{max}] of bioavailability of a test treatment (e.g., a new formulation of an innovator, a generic drug...) compared to a reference treatment (e.g., an approved formulation of an innovator...). If we accept some assumptions (i.e., constant clearances in crossover designs, clinical meaningful validity of a chosen acceptance range...] and a formulation was shown to be bioequivalent, we conclude that clinical data used in the registration process for the 'old' formulation is also valid for the 'new' one. In other words bioequivalence is an accepted surrogate for clinical equivalence. Since generally the intrasubject variability CV_{intra} (the variability of a given PK parameter in a given group of subjects if measured on at least two occasions) is lower than intersubject variability CV_{inter} (the variability between different subjects), crossover designs (where both test and reference treatments are given to the same subject) are preferable to parallel designs (where one group of subjects is treated with the test, and another group with the reference) in terms of statistical power. In other words you will need (much) less subjects in a crossover study compared to a paralled study. The most simple crossover design is the 2×2×2 (2 treatment, 2 period, 2 sequence) design: Half of the subjects are treated in the first period with test, the other half with reference; in the second period the first half is treated with reference, and the second half with test. Therefore we have two sequences (or groups): TR for the first half of subjects, and RT for the second half. Subjects are randomized between these two sequences. In a parallel design half of the subjects will be treated with test, the other half with reference (only one study period). In the BE setting parallel designs are only rarely used (e.g., for drugs with very long halflives, or studies in patients). Before starting the study you have to perform a proper samplesize estimation. You will need the following information beforehand: The acceptance range and confidence level (mainly given by a regulatory authority, e.g., 80% – 125% and 5%), the producer's risk (e.g., 20%), the variability of any PK metrics, and the anticipated deviation of test from reference (e.g., ±5%). In more statistical terms: The error type I (alpharisk, patient's risk of being treated with a product which was erroneously claimed bioequivalent) is set to 5%. Since there is a 5% chance of the bioavailability in a particular patient being either lower or higher than expected, the risk for the entire population of patients is 2×alpha=10% (therefore the confidence interval is set to 90%). The error type II (betarisk, producer's risk of getting a formulation rejected, although it is 'bioequivalent') generally is set to 10% – 20%. Since statistical power is 1beta, 80% or 90% are used. Lower or higher values may raise ethical issues. Information on variability may come from previous studies, a (not too small!) pilot study, or literature. The reliability decreases in the given order, therefore you should add some 'safety margin'. The same applies to the expected deviation from the reference. After analyzing our biosamples we calculate PK metrics from individual plasma profiles, which subsequently may be subjected to an appropriate statistical method, in order to get point estimates (e.g., 103% of the reference) and a 90% confidence interval (e.g., 93% – 113% of the reference). For any particular PK metric an acceptance range must be defined in the protocol (e.g., 80%125% for AUC). If your confidence interval is entirely included in the acceptance range, you may claim your formulation to be bioequivalent. The chosen statistical method depends on the assumed distribution of the PK metrics, i.e., ANOVA on logtransformed AUC/C_{max}data and a nonparametric method on untransformed t_{max}data. The acceptance ranges should be based on clinical grounds, but since generally no 'hard data' supporting such a range exist for the majority of drugs, 80%125% is used in many legislations for AUC and C_{max}. You must check your local guidelines, since exceptions exist (e.g., in some countries these 'goalpost' may be narrower or wider, or even 95% confidence intervals instead of 90% CIs should be used for some drugs). — 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 
Essar ● 20060113 05:40 (6843 d 07:31 ago) @ Helmut Posting: # 52 Views: 26,075 

Thanks, Helmut...things are much more clearer now. Would get back with more questions. Essar 
Essar ● 20060116 14:20 (6839 d 22:51 ago) @ Helmut Posting: # 53 Views: 26,216 

❝ The most simple crossover design is the 2×2×2 (2 treatment, 2 period, 2 sequence): ❝ Half of the subjects are treated in the first period with test, the other half with reference; in the second period the first half is treated with reference, and the second half with test. ❝ Therefore we have two sequences (or groups): TR for the first half of subjects, and RT for the second half. Dear Helmut, Taking your explanations ahead, I have tried to prepare a study design for a three treatment BE study, i.e., a BE study comparing:
To evaluate, which of the two formulations (T1 or T2), prepared by a generic company is close to the reference product R, in a single BEstudy So, first onethird of the patients (Gp A) are treated in the first period with Test T1, the next onethird (Gp B) with Test T2 and the last onethird with Reference R (Gp C). In period 2, first onethird of the patients (Gp A) are treated in the first period with Test T2, the next onethird (Gp B) with Reference R and the last onethird with Test T1 (Gp C). In Period 3, first onethird of the patients (Gp A) are treated in the first period with Reference R, the next onethird with (Gp B) Test T1 and the last onethird with Test T2 (Gp C). The above periods are summarized in the table below: Group A B C Period 1 T1 T2 R Period 2 T2 R T1 Period 3 R T1 T2 Now, please let me know whether my design is right? Is it approprirate to name this study as "3treatment, 3period, 3sequence crossover Bioequivalence study"? Can there be other designs to compare T1 and T2 with R in a single BE study? Also, please let me know how you calculate the no of subjects required for this type of a study. Looking forward to your reply. Regards, Essar 
Helmut ★★★ Vienna, Austria, 20060116 16:39 (6839 d 20:32 ago) @ Essar Posting: # 54 Views: 27,664 

Dear Essar, in order to continue with the nomenclature generally used in BE studies I have rearanged your table. Periods (P1P3) in columns, and Sequences/Groups (S1S3) in rows: ┌────┬────────────┐ ❝ Now, please let me know whether my design is right? Is it approprirate to name this study as "3treatment, 3period, 3sequence crossover Bioequivalence study"? Question #1: no Question #2: yes ❝ Can there be other designs to compare T1 and T2 with R in a single BE study? Yes, explanations following: Your design is not balanced in respect to all effects in the model, in other words, 3 combinations of treatments are missing. The chance of regulatory acceptance of a 3×3 is close to zero. The plainest design you may apply is a Williams' design (3treatment, 3period, 6sequence): ┌────┬────────────┐ If you want to extract paired comparisons (e.g., for the nonparametric method) you will fail with your design (3×3), but succeed with the given one (6×3). Since we are leaving the novice's level now, I would suggest you some further reading (not cheap, but every cent worth):
❝ Also, please let me know how you calculate the no of subjects required for this type of a study. Have a look at
Good Luck! 
Essar ● 20060117 05:53 (6839 d 07:18 ago) @ Helmut Posting: # 55 Views: 26,058 

❝ Your design is not balanced in respect to all effects in the model, in other words, 3 combinations of treatments are missing. The chance of regulatory acceptance of a 3×3 is close to zero. ❝ The simplest design you may apply is a Williams’ design (3treatment, 3period, 6sequence): Dear Helmut, Thanks once again for taking the time out. When you say that chance of regulatory acceptance of 3x3 is close to zero, you mean specifically for 3x3x3, or it is applicable to 3x3x6 design also? Also, can you please let me know the reason for the same. Now, I will start hunting for the references you have given me. Regards, Essar 
Helmut ★★★ Vienna, Austria, 20060117 10:27 (6839 d 02:44 ago) @ Essar Posting: # 56 Views: 26,841 

❝ When you say that chance of regulatory acceptance of 3x3 is close to zero, you mean specifically for 3x3x3, or it is applicable to 3x3x6 design also? You are right, I was not precise: 3×3×6 is acceptable, whereas 3×3×3 is not. ❝ Also, can you please let me know the reason for the same. The 3×3×3 does not give us unbiased estimates. Since we are interested in at least two pairwise comparisons (T_{1} vs. R, T_{2} vs. R), it is desirable to get estimates with the same degree of precision. However, to achieve this goal, the design must be balanced. A design is said to be balanced, if (acc. to Jones & Kenward):
Unfortunately for three treatments your sample size has to be a multiple of six, which may be inconvenient in terms of practicability. — 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 
nguyenvo ● 20060430 23:40 (6735 d 14:31 ago) @ Helmut Posting: # 98 Views: 26,134 

Dear Dr. Helmut, ❝ RP Qu ❝ Sample Size and Power Calculation for High Order Crossover Design ❝ Bio/Pharma Quarterly 9(1), 914 (March 2003) ❝ which is available online (277kB PDF). I am trying to access the link but there is something wrong. It is no longer valid. Could you please check it again? Thank you for your help. Best regards, Nguyen 
Helmut ★★★ Vienna, Austria, 20060501 13:59 (6735 d 00:12 ago) @ nguyenvo Posting: # 99 Views: 26,127 

— 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 
olacy ☆ Hungary, 20060623 11:28 (6682 d 02:44 ago) @ nguyenvo Posting: # 155 Views: 25,914 

Dear Nguyen, you can download this article via http://www.biopharm.us/htm. Click the quaterly directory then March_2003 and download the sample size.pdf. Best regards, Laci 
Helmut ★★★ Vienna, Austria, 20060624 14:45 (6680 d 23:26 ago) @ olacy Posting: # 156 Views: 26,152 

Dear Laci, thanks for your correction (most likely I did not edit the link correctly). Here is the working link to the 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 
shiv ● 20060125 07:46 (6831 d 05:26 ago) @ Helmut Posting: # 61 Views: 26,485 

Hello Helmut I am shiv. I quite impressed for your inputs on study design. I would like to update on ANVISA approval process. Initially ANVISA approval is for the facility and after approval only we have to conduct the studies. Please update us the current process is it pre approval or post study approval. Regards shiv prasad 
Helmut ★★★ Vienna, Austria, 20060125 14:37 (6830 d 22:34 ago) @ shiv Posting: # 63 Views: 26,062 

Hi shiv! ❝ Initially ANVISA approval is for the facility and after approval only we have to conduct the studies. Please update us the current process is it pre approval or post study approval. I do not get your question What do you mean with 'the current process' ? — 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 