Bioequivalence and Bioavailability Forum

OT: TTT subtleties [PK / PD]

posted by yjlee168  – Kaohsiung, Taiwan, 2013-07-20 21:44 (3926 d 09:32 ago) – Posting: # 11027
Views: 20,747

Dear Detlew,

❝ How could this be? How is AUC0-t influenced by the estimate of lamdaZ. IMHO in no way!

Oops! Sorry, my mistake. It should be "...but λz and AUC_t-∞ (the extrapolated AUC) could be significantly different."

❝ This is a misunderstanding. We talked in this thread about models, especially obtaining k01. And in a model other than a one-compartment model you can't get k01 by log-linear regression

I see. Sorry about my misunderstanding.

❝ IMHO the TTT rule in it's strict sense - use all points after two-times-tmax for log-linear regression - is indeed only appropriate for concentration-time curve shapes which resemble those from a one-compartment model. And yes it has to do with the second inflection point of the curve after which the linear part of log(C) versus time begins in an one-compartment model.

Very happy to know these.

❝ But as a tool to restrict the upper number of points to consider in the terminal phase it may be also used for other shapes. Hopefully the fit criterion you use (adjR2, AIC or whatever you prefer) will pick the linear part. In that sense I have used the TTT rule and found it giving reasonable results.

Perfect and crystal. Yes, it should be picking linear part only. Since when it approaches "nonlinear" part, adjR² will start decreasing or AIC will increase in that case (theoretically?). However, could you please give us an example to explain how to tell we get the "reasonable results" from TTT when comparing to others? If possible, I wish I can add this into bear.

❝ To be detailed for my method:

❝ [...]

OK.

❝ The TTT is using ideas derived from models, but itself is not a model-dependent algo because it doesn't use any model. Beside the assumption of a log-linear part of the concentration-time curves of course, which is in itself a model conception.

❝ Thus don't worry to much .

Sounds contradictory but it really makes sense to me. Thanks for your time.

Complete thread:

• 1 compartment model with lag time jag009 2013-07-17 15:58 [PK / PD] 
  • solve for k01? Helmut 2013-07-17 16:08
    • solve for k01? jag009 2013-07-17 16:19
      • solve for k01? ElMaestro 2013-07-17 17:09
      • no closed form Helmut 2013-07-17 23:01
  • 1 compartment model with lag time yjlee168 2013-07-17 20:57
  • Package-free solution ElMaestro 2013-07-17 21:53
    • Package-free solution yjlee168 2013-07-17 22:11
      • Package-free solution ElMaestro 2013-07-17 22:27
        • Package-free solution yjlee168 2013-07-17 22:42
    • Package-free solution ElMaestro 2013-07-17 23:21
      • A new R-King was born d_labes 2013-07-18 08:45
        • Brent ElMaestro 2013-07-18 09:07
        • A new R-King was born yjlee168 2013-07-18 10:21
          • OT: TTT in bear Helmut 2013-07-18 20:28
            • OT: TTT in bear yjlee168 2013-07-18 22:17
              • OT: TTT subtleties d_labes 2013-07-19 09:47
                • OT: TTT subtletiesyjlee168 2013-07-20 19:44
                  • OT: beyond TTT? Helmut 2013-07-21 00:08
                    • OT: beyond TTT? yjlee168 2013-07-22 13:45
                      • OT: keep TTT! Helmut 2013-07-22 14:21
                        • OT: keep TTT! yjlee168 2013-07-22 23:42
                          • OT: EOD (here) Helmut 2013-07-23 01:06
      • Package-free solution yjlee168 2013-07-18 10:27
        • Thank you guys! jag009 2013-07-18 16:37
          • Thank you guys! ElMaestro 2013-07-18 18:57
            • Thank you guys! jag009 2013-07-19 20:40