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 non...@optonline.net
Date: Tue, 14 Jan 2014 13:45:18 -0500 (EST)
To: robert.ba...@iconplc.com, nmusers@globomaxnm.com
Subject: [NMusers] backward integration from t-a to t





Dear Robert,




 


Efficacy is frequently considered a function of AUC.  (AUC is just an 
integral. It is obvious how to calculate AUC any software which can 
solve ODE.)  A disadvantage of this model of efficacy is that the effect 
is irreversable because AUC of concentration can only increase; it 
cannot decrease.  In many cases, a more meaningful model is a model 
where AUC is calculated form time t -a to t (kind of "moving average"), 
where t is time in the system of differential equations (variable T in 
NONMEM).   There are 2 obvious ways to calculate AUC(t-a, t).  The first 
is to do backward integration, which looks like a hard and resource 
consuming way for NONMEM.  The second one is to keep in memory AUC for 
all time points used during the integration 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. 


 


Is there a way to access AUC for the past time points (<t) from the 
integration routine? It seems like an easy thing to do.    


 


Kind regards,


Pavel  



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