Dear NMusers,
I have a question I would like your help. The data I have is only the dynamic
data since we didn't give dose to the animal. I am trying to capture the nature
of disease progression. And the PD decrease with time. I have seen people
model only the PD data use $PRED subroutine but they use the explicit
equation.But I want to use a differential equation like dA/dt=
kin(1-dis)-kout*A while A0=kin/kout.
When I ran the control stream, the gradient for most of the parameters are 0.
And the only parameter estimation I got is the sigma. The output of Y is 0. I
guess it's because I don't have dose to compartment(PDK) but I don't know how
should I fix the problem.
Any suggestion is appreciated!
The control stream I wrote is:
$PROB Demo for turn over PD model
$INPUT ID TIME AMT PDK=DV EVID
$DATA demo.csv IGNORE=#
$ESTIM MAXEVAL=3000 NOABORT PRINT=1
METHOD=COND INTERACTION SIG=5 MSFO=save.msf
$COV MATRIX=S SLOW
$SUBROUTINE ADVAN6 TOL=5
$MODEL
COMP=(PDK)
$PK
KIN=THETA(1)*EXP(ETA(1))
KOUT=THETA(2)
DIS=THETA(3)*EXP(ETA(2))
$DES
DADT(1)=KIN*(1-DIS)-KOUT*A(1)
$ERROR
Y = F + ERR(1)
; Fixed effects
$THETA 174 FIX ; KIN
$THETA 77 FIX ; KOUT
$THETA (0,0.28,1) ; AGE_EFFECT_PDK
; Random effects
$OMEGA 0 FIX; BSVKIN_PDK
$OMEGA 0 FIX; BSVDIS_PDK
$SIGMA 0.1
$TABLE ID TIME PDK Y
NOPRINT ONEHEADER FILE=DEMO.fit
And my data looks like:
#ID TIME AMT PDK EVID
101 4 . 1.49 0
102 4 . 1.58 0
61 8 . 0.57 0
62 8 . 2.03 0
63 8 . 1.58 0
64 8 . 1.52 0
109 12 . 0.71 0
110 12 . 1.18 0
21 12 . 1.25 0
-Jing
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