integrated parent-metabolite PK model from sequential iv and oral doses of parent drug
Dear fellow NMusers,
I'm trying to develop an integrated parent-metabolite PK model based on the
plasma concentrations obtained from 40 subjects after sequential iv and oral
administrations of the parent drug. The iv bolus was injected at time = 0
while the oral dose was administered at time = 4h. The most stable model so
far is a two-compartment model for the parent drug (with first-order
absorption) linked to a one-compartment metabolite model. However, in order to
obtain reasonable parameter estimates and adequate goodness-of-fit plots, I
needed to specify a "switch" in rate constant values and scaling factors at
time = 4h (oral administration time), as defined in the control stream below.
Without, this "switch", there was a very poor match between the measured and
predicted metabolite concentration values.
May I ask if my code below is correct for modelling the data at hand (assuming
the abovementioned structural model)? If not, would you be able to suggest
possible areas of model improvement?
Thank you and best wishes,
Kok-Yong SENG, PhD
DSO National Laboratories
Singapore
______________________
$PROB RUN# 1 parent-met data (nmol/L vs h)
$INPUT ID NTIM TIME DV AMT ORAL CMT EVID MDV
$DATA DATA.CSV IGNORE=C
$SUBROUTINE ADVAN5
$MODEL
NCOMP=4
COMP=(DEPOT)
COMP=(CENTRAL, DEFDOSE)
COMP=(METAB1)
COMP=(PERIPM)
$PK
IIVCL = ETA(1)
IIVF1 = ETA(2)
IIVKA = ETA(3)
IIVCL1 = ETA(4)
IIVV3 = ETA(5)
KA = THETA(1)*EXP(IIVKA)
CL = THETA(2)*EXP(IIVCL)
V2 = THETA(3)
Q = THETA(4)
V4 = THETA(5)
F1 = THETA(6)*EXP(IIVF1)
FMET = 0.6
CL1 = THETA(7)*EXP(IIVCL1)
V3 = THETA(8)*EXP(IIVV3)
IF (TIME.LE.4) THEN
S2 = V2
S3 = V3
K12 = KA
K20 = (1-FMET)*(CL/V2)
K23 = FMET*(CL/V2)
K24 = Q/V2
K42 = Q/V4
K30 = CL1/V3
ELSE
S2 = V2/F1
S3 = V3
K12 = KA
K20 = (1-FMET)*((CL/F1)/(V2/F1))
K23 = FMET*((CL/F1)/(V2/F1))
K24 = (Q/F1)/(V2/F1)
K42 = (Q/F1)/(V4/F1)
K30 = CL1/V3
ENDIF
$ERROR ;ONLY OBSERVATIONS)
IF (AMT.GT.0) TDOS=TIME
TAD=TIME-TDOS
IF (F.EQ.0) THEN
IPRED=0
ELSE
IPRED=LOG(F)
ENDIF
IRES=DV-IPRED
IF(CMT.EQ.2) W2 = SQRT(THETA(9)**2 )
IF(CMT.EQ.3) W3 = SQRT(THETA(10)**2 )
IF(CMT.EQ.2) IWRES=IRES/W2
IF(CMT.EQ.3) IWRES=IRES/W3
IF(CMT.EQ.2) Y = IPRED + (W2)*EPS(1) ;
IF(CMT.EQ.3) Y = IPRED + (W3)*EPS(2)
$THETA
$OMEGA
$SIGMA
1 FIX
1 FIX
$EST METHOD=1 INTER MAXEVAL=9999 PRINT=1 POSTHOC NOABORT MSFO=1.MSF SIGL=9
NSIG=3
$COV UNCONDITIONAL PRINT=E
:::::DATA.csv::::: (for first two subjects)
C Data Desc: parent-met data (dose in nmoles; time in hr; conc in nmol/L)
CID NTIM TIME DV AMT ORAL CMT EVID MDV
101 0 0 0 2302.308 . 2 1 1
101 0 0 0 2302.308 . 2 1 1
101 0.25 0.25 5.430537181 . . 2 0 0
101 0.25 0.25 0.741358053 . . 3 0 0
101 0.5 0.5 4.799111134 . . 2 0 0
101 0.5 0.5 0.854669023 . . 3 0 0
101 0.75 0.75 4.55617397 . . 2 0 0
101 0.75 0.75 0.691490788 . . 3 0 0
101 1 1 4.106244674 . . 2 0 0
101 1 1 0.589508916 . . 3 0 0
101 1.5 1.5 3.822383616 . . 2 0 0
101 1.5 1.5 0.409972825 . . 3 0 0
101 2 2 3.652067835 . . 2 0 0
101 2 2 0.284763877 . . 3 0 0
101 2.5 2.5 3.346291176 . . 2 0 0
101 2.5 2.5 0.08938465 . . 3 0 0
101 3 3 3.121642304 . . 2 0 0
101 3 3 -0.090114893 . . 3 0 0
101 3.5 3.5 3.278754426 . . 2 0 0
101 3.5 3.5 -0.108362666 . . 3 0 0
101 4 4 . 4604.619 1 1 1 1
101 4 4 . 4604.619 1 1 1 1
101 4 4 3.44923847 . 1 2 0 0
101 4 4 -0.071713115 . 1 3 0 0
101 4.25 4.25 3.597385022 . 1 2 0 0
101 4.25 4.25 -0.048409056 . 1 3 0 0
101 4.5 4.5 3.716095668 . 1 2 0 0
101 4.5 4.5 1.175372119 . 1 3 0 0
101 4.75 4.75 4.154635181 . 1 2 0 0
101 4.75 4.75 2.212447576 . 1 3 0 0
101 5 5 4.08855346 . 1 2 0 0
101 5 5 2.253719503 . 1 3 0 0
101 5.5 5.5 3.726503911 . 1 2 0 0
101 5.5 5.5 1.86297201 . 1 3 0 0
101 6 6 3.52409438 . 1 2 0 0
101 6 6 1.48545147 . 1 3 0 0
101 7 7 -0.791943487 . 1 3 0 0
101 8 8 2.861295756 . 1 2 0 0
101 8 8 0.195365359 . 1 3 0 0
101 10 10 2.960551062 . 1 2 0 0
101 10 10 -0.709552271 . 1 3 0 0
101 12 12 2.164593204 . 1 2 0 0
101 12 12 -0.857712813 . 1 3 0 0