## Difference between actual and published PK parameters [Study Assessment]

Hi Loky do,

» […] I have a question regarding dapoxetine biphasic half-life; the initial and terminal half-life (the initial half-life which is 1.3-1.5 hours and the terminal half-life which is 15-19 hours) does this biphasic nature affect the practical obtained half life of the drug?

I don’t understand what you mean by ‘practical obtained half life’. Do you mean the apparent terminal half life estimated from a lin/log-regression? Let’s explore the fasted study of Yan

Here we see a straight line starting at 12 hours. Therefore, we can reliably estimate \(\small{\lambda_\textrm{z}}\).

Since you wrote in your original post

» » » the drug was detected […] for only 24 hours in most of the volunteers.

it might well be that distribution was not complete ≤ 12 hours and hence, the estimated elimination contaminated. When I make a rough estimation from the concentrations in the figure between 8 and 24 hours, I get a half life of ~9.6 hours. Not exactly yours, but close.

Possibly you see such patterns (+ – +) in the fits:

Of course, what ElMaestro wrote might be another explanation.

However, in BE we are interested in detecting potential differences in the

» and is this nature could affect the drug variability?

In BE we make the – rather strong – assumption that clearance is constant (background). If this is not the case (likely…), it will negatively affect the residual variability.

In a two-compartment system, we have

\overset{k_\textrm{a}}{\longrightarrow} & \boxed{V_1} & \overset{k_{12}}{\underset{k_{21}}{\rightleftharpoons}} & \;\;\boxed{V_2}\\

& \phantom{0}\downarrow \tiny{k_\textrm{e}} & &

\end{matrix}$$ In simple terms: We can expect that in a multicompartment system the between-occasion variability to be larger than in a one-compartment system.

» […] I have a question regarding dapoxetine biphasic half-life; the initial and terminal half-life (the initial half-life which is 1.3-1.5 hours and the terminal half-life which is 15-19 hours) does this biphasic nature affect the practical obtained half life of the drug?

I don’t understand what you mean by ‘practical obtained half life’. Do you mean the apparent terminal half life estimated from a lin/log-regression? Let’s explore the fasted study of Yan

*et al.*:Here we see a straight line starting at 12 hours. Therefore, we can reliably estimate \(\small{\lambda_\textrm{z}}\).

Since you wrote in your original post

» » » the drug was detected […] for only 24 hours in most of the volunteers.

it might well be that distribution was not complete ≤ 12 hours and hence, the estimated elimination contaminated. When I make a rough estimation from the concentrations in the figure between 8 and 24 hours, I get a half life of ~9.6 hours. Not exactly yours, but close.

Possibly you see such patterns (+ – +) in the fits:

Of course, what ElMaestro wrote might be another explanation.

However, in BE we are interested in detecting potential differences in the

*absorption*of formulations. Once absorption is complete,* anything else is a property of the drug and should not be a regulatory concern.» and is this nature could affect the drug variability?

In BE we make the – rather strong – assumption that clearance is constant (background). If this is not the case (likely…), it will negatively affect the residual variability.

In a two-compartment system, we have

*three*clearances: The total body clearance (associated with elimination) and two inter-compartment clearances (associated with distribution). If you are in church of volumes of distribution / rate-constants:$$\begin{matrix}\overset{k_\textrm{a}}{\longrightarrow} & \boxed{V_1} & \overset{k_{12}}{\underset{k_{21}}{\rightleftharpoons}} & \;\;\boxed{V_2}\\

& \phantom{0}\downarrow \tiny{k_\textrm{e}} & &

\end{matrix}$$ In simple terms: We can expect that in a multicompartment system the between-occasion variability to be larger than in a one-compartment system.

- Speaking of IR formulations. Once we are crossing the Rubicon of flip-flop PK (\(\small{k_\textrm{a}\leq k_\textrm{e}}\) is common for prolonged release formulations), we have to follow the profile much longer.

—

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

*Dif-tor heh smusma*🖖_{}Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

### Complete thread:

- Difference between actual and published PK parameters Loky do 2022-02-14 16:06 [Study Assessment]
- Difference between actual and published PK parameters Helmut 2022-02-14 17:30
- Difference between actual and published PK parameters Loky do 2022-02-15 13:20
- Difference between actual and published PK parameters dshah 2022-02-15 15:26
- Difference between actual and published PK parameters Loky do 2022-02-15 15:48

- Difference between actual and published PK parametersHelmut 2022-02-15 15:56

- Difference between actual and published PK parameters dshah 2022-02-15 15:26

- Difference between actual and published PK parameters Loky do 2022-02-15 13:20
- Difference between actual and published PK parameters dshah 2022-02-14 18:39
- Difference between actual and published PK parameters ElMaestro 2022-02-14 23:09

- Difference between actual and published PK parameters Helmut 2022-02-14 17:30