RE: backward integration from t-a to t
Hi Pavel,
You mentioned that the effect compartment did not help, and the model I
suggested is identical to the effect compartment. May be try something like
transit compartment model:
DADT(2)=C-K0*A(2)
DADT(3)=K0*A(2)-K0*A(3)
...
DADT(X)=K0*A(X-1)-K0*A(X)
AUCapprox=A(2)+...+A(X)
This will prolong the shape of AUCapprox(t). It could be a bit simpler and
smoother than tlag implementation
Leonid
Original email:
-----------------
Quoted reply history
From: Pavel Belo [email protected]
Date: Thu, 16 Jan 2014 13:05:54 -0500 (EST)
To: [email protected], [email protected]
Subject: RE: [NMusers] backward integration from t-a to t
Hello Leonid,
Thank you bein helpful. You got the main point. AUC is a better
predictor than concentration, but it has to disppear very slowly but
surely.
A potential challenge is biological meaning of this approach. It will
be necessary to explain it to the biologists, who ask question like "Why
do you use 2 compartment in PK model while human body has so many
compartments?".
We will see!
Thanks,
Pavel
On Wed, Jan 15, 2014 at 01:19 AM, [email protected] wrote:
> Pavel,
> I think one can use equation
> DADT(2)=C-K0*A(2)
>
> where C is the drug concentration. When K0=0, A2 is cumulative AUC.
> When
> k0>0, A2 would represent something like AUC for the interval prior to
> the current
> time
> The length of the interval would be proportional to 1/K0 (and equal to
> infinity when k0=0). Conceptually, K0 is the rate of "AUC elimination"
> from the
> system. PD then can be made dependent on A2, and the model would
> select optimal
> value of K0. One interesting case to understand the concept is when C
> is constant.
> Then A2=C/K0 while AUC over some interval TAU is AUC=C*TAU. So
> roughly, A2 can
> be interpreted as AUC over the interval of 1/K0. Leonid
>
>
> Original email:
> -----------------
> From: Pavel Belo [email protected]
> Date: Tue, 14 Jan 2014 13:45:18 -0500 (EST)
> To: [email protected], [email protected]
> Subject: [NMusers] backward integration from t-a to t
>
>
>
>
>
> Dear Robert,
>
>
>
>
> Ã
>
> Efficacy isà frequently considered aà function of AUC.à (AUC is just
> an integral. It is obvious how to calculate AUC any software which can
> solve ODE.)à A disadvantage of this model of efficacyà is that the
> effect is irreversable becauseà AUC of concentration can only
> increase;Ã it cannot decrease.Ã In many cases, a more meaningful model
> is a model where AUC is calculated form time tà -a to t (kind of
> "moving average"), where t is timeà in the system of differential
> equations (variable T in NONMEM).Ã Ã There are 2 obvious ways to
> calculate AUC(t-a, t).Ã The first is to do backward integration, which
> looks like a hard and resource consuming way for NONMEM.Ã The second
> one is to keep in memory AUC for all time pointsà usedà during theÃ
> integrationà and calculate AUC(t-a,t) as AUC(t) - AUC(t-a), there
> AUC(t-a) can be interpolated using two closest time points below and
> above t-a.Ã
>
> Ã
>
> Is there a way toà access AUC forà the past time points (> integration
> routine?à It seems like an easyà thing to do.à à Ã
>
> Ã
>
> Kind regards,
>
>
> Pavelà Ã
>
>
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