Don’t include tmax [NCA / SHAM]
Hi Raman,
Let’s consider a one-compartment model with an absorption half life of 1 h, an elimination half life of 4 h, and last sampling at 24 h. The true \(\small{t_\text{max}=2.67\phantom{0}\text{h}}\). Now we estimate \(\small{\lambda_\text{z}}\) increasing with time.
$$\small{\begin{matrix}
t_\text{start} & \text{abs}\phantom{0}(\%) & \widehat{\lambda}_\text{z} & \widehat{t}_\text{el} & \text{bias}\phantom{0}(\%)\cr\hline
\hfil t_\text{max} & \sim84.29 & 0.1630 & 4.253 & +6.31\\
2\times t_\text{max} & \sim97.53 & 0.1715 & 4.041 & +1.02\cr
3\times t_\text{max} & \sim99.61 & 0.1727 & 4.013 & +0.32\cr
4\times t_\text{max} & \sim99.94 & 0.1731 & 4.004 & +0.11
\end{matrix}}$$It’s clear that if we would start at \(\small{t_\text{max}}\), the estimate would be biased because absorption is still ongoing. On the other hand, at \(\small{\geq2\times t_\text{max}}\), absorption is practically complete and the bias negligible. That’s the idea of the TTT-method1 (search the forum for details and examples).
If you have a tight sampling schedule (in order to ‘catch’ Cmax), even starting with the one after tmax might still be too early. Say, you sampled every 20 minutes and the automatic algo (in WinNonlin’s lingo ‘Best Fit’) suggests to start at 3 h. Then 12.5% are not absorbed yet and the estimate is ‘contaminated’ (bias +5.45%). Hence, visual inspection of fits is mandatory and manual selection of time points necessary. In simulations of two-compartment models visual inspection outperformed automatic methods.2
<terminology>
❝ For AUC(0 to inf) for determination of Kel (elimination rate constant), shall we include Tmax point also for lambda _z lower.
❝ Is there any specific guidance is there to fix lambda z lower or not to take Tmax point
Let’s consider a one-compartment model with an absorption half life of 1 h, an elimination half life of 4 h, and last sampling at 24 h. The true \(\small{t_\text{max}=2.67\phantom{0}\text{h}}\). Now we estimate \(\small{\lambda_\text{z}}\) increasing with time.
$$\small{\begin{matrix}
t_\text{start} & \text{abs}\phantom{0}(\%) & \widehat{\lambda}_\text{z} & \widehat{t}_\text{el} & \text{bias}\phantom{0}(\%)\cr\hline
\hfil t_\text{max} & \sim84.29 & 0.1630 & 4.253 & +6.31\\
2\times t_\text{max} & \sim97.53 & 0.1715 & 4.041 & +1.02\cr
3\times t_\text{max} & \sim99.61 & 0.1727 & 4.013 & +0.32\cr
4\times t_\text{max} & \sim99.94 & 0.1731 & 4.004 & +0.11
\end{matrix}}$$It’s clear that if we would start at \(\small{t_\text{max}}\), the estimate would be biased because absorption is still ongoing. On the other hand, at \(\small{\geq2\times t_\text{max}}\), absorption is practically complete and the bias negligible. That’s the idea of the TTT-method1 (search the forum for details and examples).
If you have a tight sampling schedule (in order to ‘catch’ Cmax), even starting with the one after tmax might still be too early. Say, you sampled every 20 minutes and the automatic algo (in WinNonlin’s lingo ‘Best Fit’) suggests to start at 3 h. Then 12.5% are not absorbed yet and the estimate is ‘contaminated’ (bias +5.45%). Hence, visual inspection of fits is mandatory and manual selection of time points necessary. In simulations of two-compartment models visual inspection outperformed automatic methods.2
❝ If Tmax point is included for 20 % subjects, will there be any query from regulators.
❝ Both Cmax and AUC(0 to t) are passed.
<terminology>
T is the SI abbreviation of the absolute temperature and t the one for time. Hence, we should use tmax instead of Tmax.
</terminology>- Scheerans C, Derendorf H, Kloft C. Proposal for a Standardised Identification of the Mono-Exponential Terminal Phase for Orally Administered Drugs. Biopharm Drug Dispos. 2008; 29(3): 145–57. doi:10.1002/bdd.596.
- Noe DA. Performance characteristics of the adjusted r2 algorithm for determining the start of the terminal disposition phase and comparison with a simple r2 algorithm and a visual inspection method. Pharmaceut Stat. 2019; 1–13. doi:10.1002/pst.1979.
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Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
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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
Complete thread:
- Selection of points for Elimination rate constant ryraman2661 2023-12-23 08:41 [NCA / SHAM]
- Don’t include tmaxHelmut 2023-12-23 11:46
- Don’t include tmax ryraman2661 2023-12-26 08:40
- Don’t include tmaxHelmut 2023-12-23 11:46