Fatemeh,
It is better to start with the sequential fit: first fit PK (you seems
to indicate that you can get a good fit), then fix individual PK
parameters and use the PK individual predictions to drive the PK-PD
part. If and when you get the good PK-PD model, you can try to free the
PK part to get simultaneous fit.
From your description it looks like incorrect PD affects your PK fit.
You need to correct PD model but it is difficult to do when your PK is
biased. It will be easier when you have PK fixed to correct values: the
bias will shift to PD part that can be explored graphically and using
various PK-PD models.
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Fatemeh Akhlaghi, PhD wrote:
Dear NMusers group:
I am puzzled by the result of a NONMEM analysis I am working on. I have
modeled plasma conc versus effect data using ADVAN5 (simultaneous link,
comp3=effect) and can get a reasonable fit for the PD but the PK IPRED versus
observed plot has a very unusual S-shape. Fitting the same plasma conc
independently using ADVAN3 with the same error structure does not produce such
pattern. I log transform the plasma concentration data to obtain a better PK
fit. Also I have built a non-linear binding equation into the error structure
of the PKPD model. I have included the code below. Do you know what is
wrong?
Many thanks in advance and I look forward to hear from you.
Fatemeh Akhlaghi
$PROBLEM
;MODEL DESC:PKPDLINKWITH BINDING PARAMETERS
;PROJECT NAME: EXAMPLE1
;PROJECT ID: PKPDLINK MODEL
; MODEL: C = BIEXP; CE = C*KEO.EXP(-KEO.T); E = SIGM_EMX(CE)
; NOTE: MAY BE MORE ETAS HERE THAN REASONABLE
; NOTE: MODEL FOR C CAN BE MORE COMPLEX BY ADDING CMPTS
;
; THE DATA FILE CONTAINS BOTH CP AND EFFECT OBSERVATIONS.
; WHEN DV IS A CP OBSERVATION, CMT = 1 (OR 0),
; WHEN DV IS AN EFFECT OBSERVATION, CMT =2.
$DATA ..\PKPDLINK1ADDDOSE.CSV IGNORE=C
$INPUT ID OCC TIME AMT DV DV1 MDV CMT EVID WT TPRO ALB DOSE HT SEX AST TBIL
UREA CREA WBC DROP=RBC
$SUBROUTINES ADVAN=5
$MODEL
COMP=(CENTRAL,DEFDOSE,DEFOBS)
COMP=PERIPH
COMP=EFFECT
$PK
K10=THETA(1)
TVK12=THETA(2)
K12=TVK12*EXP(ETA(1))
K13= .001*K10 ; TRIVIAL LOSS TO EFFECT COMPT
K21=THETA(3)
TVS1=THETA(4)
S1=TVS1 ; V1 FOR DRUG
K30=THETA(5) ; KEO
E0=THETA(6)*EXP(ETA(2))
EMAX=THETA(7)
C50=THETA(8)*EXP(ETA(3))
HILL=THETA(9)
TVBMAX=THETA(10)*EXP(ETA(4))
BMAX=TVBMAX
KD=THETA(11)
KNS=THETA(12)
W=THETA(13)
S3=S1*K13/K30 ; PRESERVES CESS = CPSS
$ERROR
FLAG=0
IF(AMT.GT.0) FLAG=1 ;DOSING RECORD ONLY
CP1=1
IF(F.NE.0) CP1=F
LNCP=LOG(CP1+FLAG) ;TRANFORM THE PREDICTION TO THE LOG OF PRED
Y1=LNCP+W*ERR(1)
CP=0
IF(LNCP.GT.-4) CP=EXP(LNCP)
CB=HT*((CP*BMAX/(CP+KD))+KNS*CP)+CP*(1-HT)
E=E0*(1-(EMAX*(CB**HILL))/((C50**HILL)+(CB**HILL)))
Y2=E+E*(ERR(2))+ERR(3)
Q=1
IF(CMT.EQ.2) Q=0 ; CMT = 3 = EFFECT OBS
Y=Q*Y1+(1-Q)*Y2
F1=Q*LNCP+(1-Q)*E
IPRE=F1
DEL=0
IF(IPRE.EQ.0) DEL=1
W=IPRE+DEL
IRES=IPRE-DV
IWRES=IRES/W
$THETA (0.01,0.5,1) ;K10 1
$THETA (0.1,1,2) ;K12 2
$THETA (0.01,0.05,0.5) ;K21 3
$THETA (0.1,4,10) ;V1 OR S1 4
$THETA (0.1,0.5,) ;K30 5
$THETA (0.1,0.2,) ;E0 6
$THETA (0.01,0.1,) ;EMAX 7
$THETA (0.1,150,) ;EC50 8
$THETA (2,4,6) ;HILL 9
$THETA (200,250,350) ;BMAX 10
$THETA (0.1,0.6,12) ;KD 11
$THETA (0.01,0.1,2) ;KNS 12
$THETA (0.001,0.1,) ;PRO RES ERR 13
$OMEGA BLOCK(3)
0.001 ;k12
0.0001 0.001 ;e0
0.0001 0.0001 0.01 ;ec50
$OMEGA
0.2 ;BMAX 4
$SIGMA
0.17 ;[A] SIGMA(1,1)
0.002 ;[A] SIGMA(2,2)
0.0001 ;[A] SIGMA(3,3)
$COV PRINT=E
$ESTIMATION METHOD=1 INTER PRINT=10 MAXEVAL=9999 SIGDIG=6 NOABORT
Fatemeh Akhlaghi, PharmD, PhD
Associate Professor in Pharmacokinetics
Biomedical and Pharmaceutical Sciences (BPS)
University of Rhode Island
125 Fogarty Hall, 41 Lower College Road
Kingston, RI 02881, USA
Phone/Fax: (401) 874 9205/(401) 874 2181
Email: [EMAIL PROTECTED]
Laboratory Website: http://www.uri.edu/pharmacy/faculty/aps/akhlaghi/index
