Re: Sequential PD model parameter stays at initial estimation problem

From: Lei Diao Date: November 11, 2011 technical Source: mail-archive.com
Hi Dear Dr. Holford, Thank you so much for your response. What I model is an enzyme drug. The base was not zero and it was the baseline level of the substrate of the enzyme for each individual measured. I was just trying to fix the baseline level as constant at the baseline for each individual and model the effect of enzyme activity on its substrate concentration by the M-M function. I guess I should not use the model in my question since an input should be included. I also tried to include kin and kout to model the baseline level and that way the model was able to run: DADT(4)=kin-kout*A(4) -Vmax*CP*A(4)/(Km+A(4)). For the model with kin, kout, if I only use one parameter kin and replace kout with kin/base, the model was able to run ok. However, if I try to estimate both kin and kout with the following code: kin= THETA(1)*EXP(ETA(1)) kout= THETA(2)*EXP(ETA(2)) Vmax= THETA(3)* EXP(ETA(3)) Km = 38.9 ; Enobia Km data kin=kout*base F4=kin/kout ; kin stays at its initial estimation I provided and gradient remains zero. Is it because kin and kout are related, so NM just fix one and estimate the other one? You are right that I was initializing a differential equation by putting a AMT of 1 in CMT 4 at TIME=0. I will definitely try what you suggest. Do you have other suggestions to model such enzyme replacement drug? Thanks again! Lei
Quoted reply history
On Thu, Nov 10, 2011 at 11:07 PM, Nick Holford <[email protected]>wrote: > Lei, > > Have you checked in a $TABLE file that CP has the expected value and that > A(4) is indeed initialized at a non zero value of 'base'? You don't > explicitly define 'base' in your code. If it zero then of A(4) will remain > at zero and Vmax will have a gradient of zero. > > You don't give any clue what kind of PD marker you are trying to model but > it is rather strange that you don't allow any input of the marker in > DADT(4). Even if CP remained zero the marker would disappear because there > is no input. > > You seem to be using the very old fashioned NONMEM V method of > initializing a differential equation by putting a AMT of 1 in CMT 4 at > TIME=0. > > Since NONMEM VI this has become much simpler. > > Just use this: > A_0(4)=base > Don't set F4 to anything and don't put and AMT into CMT=4. > > Nick > > > On 11/11/2011 8:18 a.m., Lei Diao wrote: > >> Hi Dear NMusers, >> >> I have a sequential PD model and I listed the code here. base is the >> baseline level of the PD parameter for each individual and was included in >> the dataset. The problem with this code is that my only parameter to be >> estimated Vmax stays at the initial estimation whatever I provide and the >> gradient for THETA1 stays at 0 from the beginning. And the run time is >> extremely long. If I change F4 to another THETA to be estimated, the same >> problem still exists. >> >> Will anyone please shed some light on this problem? >> >> Thanks a lot! >> >> Lei >> >> >> $PROBLEM PD model >> $INPUT ID ETACL ETAV2 ETAKA Weight AMT DV TIME STUDYbase CMT >> >> $DATAPD.csv IGNORE=@ WIDE >> >> $SUBROUTINES ADVAN6 TOL=3 >> >> $MODEL NCOMP=4 >> COMP=GUT COMP=CENTRAL COMP=PERI COMP=EFFECT >> >> ;--------------- >> $PKSCALE= Weight >> >> SCALE2 = Weight ** 0.75; allometric >> >> THETACL=1 ; L/day >> THETAV1= 1; L/kg >> THETACLRA= 1 ; L/day >> THETAV2=1 ; L/kg >> THETAKA= 1 ; 1/day >> THETAALAG1= 1 ;days >> THETAF1= 1 >> THETACLHILL= 1 >> THETACLTITER= 1 >> THETACLRAHILL= 1 >> >> CL= SCALE2 * THETACL * EXP(ETACL) >> >> V1= SCALE * THETAV1 >> CLRA= SCALE2 * THETACLRA >> V2= SCALE * THETAV2 * EXP(ETAV2) >> KA= THETAKA * EXP(ETAKA) >> ALAG1= THETAALAG1 >> >> F1 = THETAF1 >> S2=V1 >> Vmax= THETA(1)* EXP(ETA(1)) >> Km = 100 >> F4=base ; R0 is the baseline for each individual >> >> K= CL / V1 >> K23= CLRA / V1 >> K32= CLRA / V2 >> >> >> >> $DES DADT(1)= -KA * A(1) >> DADT(2)= (KA * A(1)) - ((K + K23) * A(2)) + (K32 * A(3)) >> DADT(3)= K23 * A(2) - K32 * A(3) >> CP= A(2)/S2 >> DADT(4)= -Vmax*CP*A(4)/(Km+A(4)) >> >> >> $ERROR >> IPRED=F >> Y= A(4)*(1+ERR(1))+ERR(2) >> ;--------------- >> $THETA(0,10) >> $OMEGA (0 FIXED) >> $SIGMA 0.1 10 >> ;--------------- >> $EST METHOD=0 MAXEVAL=9999 NOABORT PRINT=5 >> $COVARIANCE >> >> > -- > Nick Holford, Professor Clinical Pharmacology > Dept Pharmacology& Clinical Pharmacology, Bldg 505 Room 202D > University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand > tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53 > email: [email protected] > http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford > > -- Lei Diao Postdoc in PK/PD modeling and simulation University of Tennessee College of Pharmacy
Nov 10, 2011 Lei Diao Sequential PD model parameter stays at initial estimation problem
Nov 11, 2011 Nick Holford Re: Sequential PD model parameter stays at initial estimation problem
Nov 11, 2011 Lei Diao Re: Sequential PD model parameter stays at initial estimation problem