vezz ☆ Erba (CO), Italy, 2011-10-06 14:45 (4756 d 22:42 ago) Posting: # 7430 Views: 9,990 |
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Dear All, in a recent study we observed few profiles with no measurable concentrations (i.e., all the concentrations were below the lower limit of quantification). I would like to ask you how these profiles are usually handled in the statistical analysis in your experience. Someone suggested not to calculate the PK parameters (e.g., AUC Cmax, etc.) based on these profiles, but to consider these concentrations only in the calculation of the descriptive statistics by time point in order to determine the mean profiles. I wonder if this approach may be reasonable. I found that this issue was discussed by the Health Canada Scientific Advisory Committee on Bioavailability and Bioequivalence in a workshop held in 2004. The record of proceeding is available here and the relevant part is reported below. "Issue discussed: What is an inadequate concentration versus time profile? Conclusion: If there are no measurable concentrations or just one concentration, that profile is not adequate. If two consecutive measurable concentrations are observed and the second is lower than the first, it is possible to compute a Cmax and AUCT. Although these estimates of Cmax and AUCT may be somewhat inadequate, the profile should nevertheless be included in the analysis. No consensus was reached on treatment of inadequate profiles, i.e., on whether these profiles may be simply dropped from the analysis." Thank you in advance for your help. — Kind regards, Stefano |
Dr_Dan ★★ Germany, 2011-10-06 16:22 (4756 d 21:05 ago) @ vezz Posting: # 7431 Views: 8,329 |
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Dear Stefano first of all before discussing how to calculate PK parameters I would suggest to find out the reason for obtaining profiles with no measurable concentrations.
Kind regards Dan — Kind regards and have a nice day Dr_Dan |
ElMaestro ★★★ Denmark, 2011-10-06 19:45 (4756 d 17:42 ago) @ Dr_Dan Posting: # 7437 Views: 8,384 |
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Dear all, I have a lot of sympathy for Dr_Dan's post here: Do we really want to try to conclude a lot about product performances when this happens? Or should we rather stop for a second and start thinking and focus on trial performance instead? If a subject's PK is just a row of BLQ's then something very basic, whatever it is, went badly wrong (yeah right, he/she could be a supergiga-metaboliser. Not). For me personally, I would not think primarily of product failure (as in a tablet with zero API) - I think other reasons come more realistically to mind, but that's just me and it is said with reference to the rather strict GMP and release criteria in EU. I know I am going to extremes here but considering eg. ICH E6 2.2 ('Before a trial is initiated, foreseeable risks and inconveniences should be weighed against the anticipated benefit for the individual trial subject and society. A trial should be initiated and continued only if the anticipated benefits justify the risks.') or 2.5 ('Clinical trials should be scientifically sound, and described in a clear, detailed protocol.'), if a trial has a subset subjects having just BLQ's would lead me to think the following:
— Pass or fail! ElMaestro |
d_labes ★★★ Berlin, Germany, 2011-10-06 17:24 (4756 d 20:03 ago) @ vezz Posting: # 7433 Views: 8,518 |
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Dear vezz, ❝ in a recent study we observed few profiles with no measurable concentrations (i.e., all the concentrations were below the lower limit of quantification). I would like to ask you how these profiles are usually handled in the statistical analysis in your experience. The EMA guidance states (page 14) "Exclusion of data cannot be accepted on the basis of statistical analysis or for pharmacokinetic reasons alone, because it is impossible to distinguish the formulation effects from other effects influencing the pharmacokinetics. The exceptions to this are: 1) A subject with lack of any measurable concentrations or only very low plasma concentrations for reference medicinal product. A subject is considered to have very low plasma concentrations if its AUC is less than 5% of reference medicinal product geometric mean AUC (which should be calculated without inclusion of data from the outlying subject). The exclusion of data due to this reason will only be accepted in exceptional cases and may question the validity of the trial ..." A little bit curious for me is the underlined sentence. Taken literally it would not allow to exclude such profiles for the Test formulation . ❝ Someone suggested not to calculate the PK parameters (e.g., AUC Cmax, etc.) based on these profiles, but to consider these concentrations only in the calculation of the descriptive statistics by time point in order to determine the mean profiles. I wonder if this approach may be reasonable. The EMA guidance is not specific in respect to this. I personally would calculate the PK metrics for such profiles as far as possible but drop them in the statistical analysis. I would drop these profiles also from the mean curves. — Regards, Detlew |
Ohlbe ★★★ France, 2011-10-06 18:31 (4756 d 18:56 ago) @ d_labes Posting: # 7436 Views: 8,519 |
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Dear D. Labes, ❝ A little bit curious for me is the underlined sentence. Taken literally it would not allow to exclude such profiles for the Test formulation . My understanding is that this is precisely the idea ! Basically, if no concentration is measured after the reference product, EU regulators are ready to assume that the subject did not swallow the product. The reference formulation is considered to be reliable If the same situation happens after the test product, they consider that they cannot make the difference between a non-compliant subject and a deficient tablet. They will not take any chance. Regards Ohlbe — Regards Ohlbe |
Helmut ★★★ Vienna, Austria, 2011-10-06 21:14 (4756 d 16:13 ago) @ vezz Posting: # 7439 Views: 8,341 |
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Dear vezz & all! The never-ending story. It took EMA quite a while to accept the fact that shit happens. Interesting is the beginning of the section D. Labes quoted. Reasons for exclusion I agree with Ohlbe’s interpretation. In other words, treatments are not to be treated [sic!] equally. R: Innocent until proven guilty T: Guilty until proven innocent All animals are equal, but some animals are more equal than others. George Orwell (Animal Farm, 1945) — Dif-tor heh smusma 🖖🏼 Довге життя Україна! Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes |