## AUC0-τ estimation with time deviations [NCA / SHAM]

Dear Smart People!

I'd like to understand the correct method to calculate AUC

Suppose we have to calculate NCA parameters for multiple dose during n-th dose period of 24 hours.

We have these concentations and time deviation -1 min in the first sample and 0,5 hours in the last:

Aiming to calculate concentration at t=0, Phoenix use the minimum observed during the dose interval (from dose time to dose time+tau) for extravascular and infusion data (while for IV bolus data it performs a log-linear regression).

That is for extravascular or infusion data in the listed dataset first point (time=0) would be replaced by 20, so that AUC

There are also some more questions about AUC

Interval of dosing (τ, 24 hour) is always a constant for all subjects not depending for the actual dose period, isn't it?

What is the best way to handle with BLQ in the end of the dosing period for steady-state?

I'd like to understand the correct method to calculate AUC

_{0-τ}in the case of time deviations in the first sample point (actually I think that we always have deviations in the first point cause it is impossible to "eat" drug and "give" blood at the same time).Suppose we have to calculate NCA parameters for multiple dose during n-th dose period of 24 hours.

We have these concentations and time deviation -1 min in the first sample and 0,5 hours in the last:

`Data set 3`

Time Conc

-0.017 1

1 60

2 80

3 100

4 130

5 160

6 130

7 100

8 90

10 70

12 40

14 30

18 20

24.5 2

Aiming to calculate concentration at t=0, Phoenix use the minimum observed during the dose interval (from dose time to dose time+tau) for extravascular and infusion data (while for IV bolus data it performs a log-linear regression).

That is for extravascular or infusion data in the listed dataset first point (time=0) would be replaced by 20, so that AUC

_{0-τ}equals 1325 while if we will not include 1-minute time deviation it would be 1316. May be this example is not so demonstrative but I was slightly suprised that a difference in one minute should totally change the input data: in fact we throw pre-dose concentration to the bin. Are there another methdos for handling AUC_{0-τ}in such cases (linear extrapolation for example)?There are also some more questions about AUC

_{0-τ}:Interval of dosing (τ, 24 hour) is always a constant for all subjects not depending for the actual dose period, isn't it?

What is the best way to handle with BLQ in the end of the dosing period for steady-state?

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### Complete thread:

- AUC0-tau at steady state BNR 2016-03-31 22:46 [NCA / SHAM]
- AUC0-tau at steady state jag009 2016-03-31 23:05
- AUC0-tau at steady state BNR 2016-03-31 23:43
- RTFM Helmut 2016-04-01 00:59
- RTFM BNR 2016-04-01 02:05
- AUC0-τ estimation with time deviationsAstea 2019-02-10 16:38
- AUC0-τ estimation with time deviations Helmut 2019-02-10 19:32
- Cτ for lin and lin-up/log-down Astea 2019-02-10 20:50
- Cτ by lin-/lin, lin-up/log-down, and λz Helmut 2019-02-11 01:45
- inter- vs extra- Astea 2019-02-11 19:46
- inter- vs extra- Helmut 2019-02-12 02:20
- No rule fits all mittyri 2019-02-14 12:55
- one size fits all vs goal posts Astea 2019-02-16 08:33
- one size fits all vs goal posts ElMaestro 2019-02-16 13:33
- Bias etc. Helmut 2019-02-16 14:26

- software: NCA not validated Helmut 2019-02-16 13:59
- no way out for NCA validation? mittyri 2019-02-20 21:22

- Default rules mittyri 2019-02-20 21:40

- one size fits all vs goal posts ElMaestro 2019-02-16 13:33

- one size fits all vs goal posts Astea 2019-02-16 08:33

- inter- vs extra- Astea 2019-02-11 19:46

- Cτ by lin-/lin, lin-up/log-down, and λz Helmut 2019-02-11 01:45

- Cτ for lin and lin-up/log-down Astea 2019-02-10 20:50

- AUC0-τ estimation with time deviations Helmut 2019-02-10 19:32

- RTFM Helmut 2016-04-01 00:59

- AUC0-tau at steady state BNR 2016-03-31 23:43

- AUC0-tau at steady state jag009 2016-03-31 23:05