Re: Final Parameter is same as initial parameter - integrated PK-PD models with two PD parameters

From: Leonid Gibiansky Date: December 08, 2019 technical Source: mail-archive.com
ERR3 and ERR4 are mixed up, should be in order (in the ERROR block). Can it be the reason? Leonid
Quoted reply history
On 12/8/2019 2:24 PM, Singla, Sumeet K wrote: > Hello everyone! > > This is giving me great deal of headache. If you can please help me with this, my subsequent models will start working too. Please take your extremely valuable time to help me, if you can. > > I am trying to relate THC concentration in the central compartment to heart rate, and in the effect compartment to psychological highness. So, there are two PD effects, heart rate and highness. My model is successfully converging and giving me physiologically relevant parameters when I run those models separately i.e. simultaneous estimation of PK parameters and PD parameters related to heart rate OR simultaneous estimation of PK parameters and PD parameters related to highness. However, when I try to estimate all of them all at once, my model is just not running. Errors are: > > 1. My final parameters are same as initial parameters > 2. “OCCURS DURING SEARCH FOR ETA AT A NONZERO VALUE OF ETA NUMERICAL > > DIFFICULTIES WITH INTEGRATION ROUTINE. NO. OF REQUIRED SIGNIFICANT DIGITS IN SOLUTION VECTOR TO DIFFERENTIAL EQUATIONS, 6, MAY BE TOO LARGE.” > > I have tried ADVAN 6, 8 AND 13 and have mostly used FOCE as estimation. Couple of things to be noticed in NONMEM control stream below: > > 1. I am fixing THETA and OMEGAS for PK parameters derived from poppk > model. > 2. There are two emax equations, one for heart (EMAX) and one for > effect compartment in brain (EMAXB). > 3. I am not estimating ETA around effect compartment rate constant and > EC50. > 4. I have 4 observations per subject for heart rate and highness. > 5. TYPE 1 (=1) relates to highness, TYPE2(=1) relates to heart rate and > TYPE 3 (=1) relates to Cp > > So, you can see that overall, I am estimating very few parameters. Below is the dataset and control stream > > ID > > TIME > > AMT > > DV > > CMT > > MDV > > TYPE1 > > TYPE2 > > TYPE3 > > 1402 > > 9:39 > > 40000 > > 0 > > 1 > > 1 > > 0 > > 0 > > 1 > > 1402 > > 9:39 > > . > > 0 > > 3 > > 0 > > 1 > > 0 > > 0 > > 1402 > > 9:39 > > . > > 0 > > 1 > > 0 > > 0 > > 1 > > 0 > > 1402 > > 9:50 > > . > > 271.8 > > 1 > > 0 > > 0 > > 0 > > 1 > > 1402 > > 9:50 > > . > > 6 > > 3 > > 0 > > 1 > > 0 > > 0 > > 1402 > > 9:50 > > . > > 34.4 > > 1 > > 0 > > 0 > > 1 > > 0 > > $INPUT C ID TIME AMT DV CMT MDV TYPE1 TYPE2 TYPE3 > > $SUBROUTINE ADVAN6 TRANS1 TOL=6 > > $MODEL NCOMP = 3 > > COMP = (CENTRAL) > > COMP = (PERIPH1) > > COMP = (EFFTHC) > > $PK > > TVV1 = THETA(1) ;Central Volume of distribution in L > > V1 = TVV1*EXP(ETA(1)) > > TVCL = THETA(2) > > CL = TVCL*EXP(ETA(2)) ;Clearance > > TVQ = THETA(3) > > Q = TVQ*EXP(ETA(3)) ;Intercompartment Clearance > > TVV2 = THETA(4) > > V2 = TVV2*EXP(ETA(4)) > > KE01= THETA(5) > > EC50H = THETA(6) > > EMAXH = THETA(7)*EXP(ETA(5)) > > EC50B = THETA(8) > > EMAXB = THETA(9) > > HILL = THETA(10) > > S1 = V1 > > A_0(1)=0 > > A_0(3)=0 > > $DES > > C1 = A(1)/V1 > > C3 = A(3) ;effect compartment for THC > > DADT(1) = (Q/V2)*A(2) - (Q/V1)*A(1) - (CL/V1)*A(1) > > DADT(2) = (Q/V1)*A(1) - (Q/V2)*A(2) > > DADT(3) = KE01*C1 - KE01*A(3) > > $ERROR > > CP = A(1)/V1 > > CE1 = A(3) > > CONC = CP*(1 + ERR(1)) + ERR(3) > > H = EMAXH*(((CP**HILL))/((EC50H**HILL)+(CP**HILL))) > > B = EMAXB*(((CE1**HILL))/((EC50B**HILL)+(CE1**HILL))) > > EFF1 = B + ERR(2) > > EFF2 = H + ERR(4) > > IF(TYPE1.EQ.1) IPRED = B > > IF(TYPE2.EQ.1) IPRED = H > > IF(TYPE3.EQ.1) IPRED = CP > > Y = (EFF1*TYPE1) + (EFF2*TYPE2) + (CONC*TYPE3) > > $THETA > > 16.5 FIX ; [V1] > > 255 FIX ; [CL] > > 33.5 FIX ; [Q] > > 29.7 FIX ; [V2] > > (0, 1, 10) ; [KEO1] > > (0.01,16.3) ; EC50H > > (0, 79) ; EMAXH > > (0.01,16.3) ; EC50B > > 10 FIX ; EMAXB > > 1 FIX ; HILL > > $OMEGA > > 0.085 FIX ; [V1] > > 0.159 FIX ; [CL] > > 0.140 FIX ; [Q] > > 0.191 FIX ; [V2] > > (0.001, 0.1) ; EMAXH > > $SIGMA > > 0.0672 ;ERR1 > > 178 ;ERR2 > > 100 ;ERR4 > > $SIGMA > > 0.00004 FIX ;[ERR3] > > $COV MATRIX=R UNCONDITIONAL > > $ESTIMATION METHOD=1 MAXEVAL=99999 SIG=3 NOABORT PRINT=5 MSFO=simultaneous.MSF > > Regards, > > *Sumeet K. Singla* > > *Ph.D. Candidate* > > *Division of Pharmaceutics and Translational Therapeutics* > > *College of Pharmacy | University of Iowa* > > *Iowa City, Iowa* > > *[email protected] <mailto:[email protected]>* > > *518.577.5881*
Dec 08, 2019 Sumeet K Singla Final Parameter is same as initial parameter - integrated PK-PD models with two PD parameters
Dec 08, 2019 Leonid Gibiansky Re: Final Parameter is same as initial parameter - integrated PK-PD models with two PD parameters