Dear nmusers,
I have a data set which contains single and multiple ascending dose data.
The model development was initially performed on the single dose data.
I initially developed a model using ADVAN4 TRANS 2 (2 compartment linear
model with oral administration) which I later reparameterized into ADVAN6.
I expected to see some minor differences in parameter estimates, OFV etc
due to the change in subroutine but was surprised to see large differences
in both parameter estimates and OFV (+180 points) but also a significant
improvement in overall fit (graphically) while the data was the same. With
the ADVAN4 the model fit was particularly poor to parts of the multiple
dose data, with the ADVAN6 the overall fit to all data was much improved. I
was using NONMEM7.3 for the analysis.
I guess the ADVAN4 model gets stuck in a local minima, but using the final
estimates from the ADVAN6 model does not help. I would be grateful for an
explanation of the reasons why this happens.
I have included the two models below.
Kind regards,
Hanna Silber
$PROBLEM PK with ADVAN4
$INPUT C ID TAD TIME AMT DV EVID CMT PTIM LDV DOSE BW BMI CLCR SEX AGE
STUDY DAY BLQ
$DATA nmpk05DEC16.csv IGNORE=@
$SUBROUTINES ADVAN4 TRANS4
$PK
CL = THETA(1) * EXP(ETA(1))
V2 = THETA(2) * EXP(ETA(2))
KA = THETA(3) * EXP(ETA(3))
ALAG1 = THETA(6) * EXP(ETA(4))
Q = THETA(7) * EXP(ETA(5))
V3 = THETA(8) * EXP(ETA(6))
S2 = V2/1000
$ERROR
IPRED = F
W = SQRT(THETA(4)**2*IPRED**2 + THETA(5)**2)
Y = IPRED + W*EPS(1)
IRES = DV-IPRED
IWRES = IRES/W
$THETA
(0,12.7) ;1 CL
(0,275) ;2 V2
(0,3.06) ;3 KA
(0, 0.12) ;4 Prop.RE (sd)
(0, 0.0153) ;5 Add.RE (sd)
(0,0.474) ;6 ALAG1
(0,26.3) ;7 Q
(0,133) ;8 V3
$OMEGA BLOCK(2) 0.0747 ;1 IIV CL
0.0723 0.0942 ;2 IIV V2
$OMEGA
1.76 ;3 IIV KA
0.00166 ;4 IIV ALAG
0.036 ;5 IIV Q
0.0407 ;6 IIV V3
$SIGMA
1 FIX ;
$EST METHOD=1 INTER MAXEVAL=9999 NOABORT SIG=3 PRINT=1 POSTHOC
$COV
######################################################
$PROBLEM PK with ADVAN6
$INPUT C ID TAD TIME AMT DV EVID CMT PTIM LDV DOSE BW BMI CLCR SEX AGE
STUDY DAY BLQ
$DATA nmpk05DEC16.csv IGNORE=@
$SUBROUTINES ADVAN6 TOL=5
$MODEL
COMP = (ABS) ;1
COMP = (CENT) ;2
COMP = (PER) ;3
$PK
CL = THETA(1) * EXP(ETA(1))
V2 = THETA(2) * EXP(ETA(2))
KA = THETA(3) * EXP(ETA(3))
ALAG1 = THETA(6) * EXP(ETA(4))
Q = THETA(7) * EXP(ETA(5))
V3 = THETA(8) * EXP(ETA(6))
K=CL/V2
K23 = Q/V2
K32 = Q/V3
A_0(1) = 0
A_0(2) = 0
A_0(3) = 0
$DES
DADT(1) = -KA*A(1)
DADT(2) = KA*A(1) - K*A(2) - K23*A(2) + K32*A(3)
DADT(3) = K23*A(2) - K23*A(3)
$ERROR
CONC = A(2)*1000/V2
IPRED = CONC
IF(CONC.EQ.0) IPRED = 1
W = SQRT(THETA(4)**2*IPRED**2 + THETA(5)**2)
Y = IPRED + W*EPS(1)
IRES = DV-IPRED
IWRES = IRES/W
$THETA
(0,12.1) ;1 CL
(0,275) ;2 V2
(0,3.06) ;3 KA
(0, 0.12) ;4 Prop.RE (sd)
(0, 0.0153) ;5 Add.RE (sd)
(0,0.474) ;6 ALAG1
(0,26.3) ;7 Q
(0,133) ;8 V3
$OMEGA BLOCK(2) 0.0747 ;1 IIV CL
0.0723 0.0942 ;2 IIV V2
$OMEGA
1.76 ;3 IIV KA
0.00166 ;4 IIV ALAG
0.036 ;5 IIV Q
0.0407 ;6 IIV V3
$SIGMA
1 FIX ;
$EST METHOD=1 INTER MAXEVAL=9999 NOABORT SIG=3 PRINT=1 POSTHOC
$COV
###############################
Data set example:
C ID TAD TIME AMT DV EVID CMT PTIM LDV DOSE BW BMI CLCR SEX AGE STUDY DAY
BLQ
0 11001 0 0 5 0 1 1 0 0 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 0.5 0.5 0 1.94 0 2 0.5 0.662688 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 1 1 0 14.6 0 2 1 2.681022 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 1.5 1.5 0 22.4 0 2 1.5 3.109061 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 2 2 0 18.1 0 2 2 2.895912 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 2.5 2.5 0 15.4 0 2 2.5 2.734368 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 3 3 0 16.3 0 2 3 2.791165 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 4 4 0 15.5 0 2 4 2.74084 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 6 6 0 11.9 0 2 6 2.476538 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 8 8 0 11.5 0 2 8 2.442347 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 12 12 0 7.71 0 2 12 2.042518 5 54.8 20.63 74.32657 0 44 1 1 0
0 11001 16.017 16.017 0 8.71 0 2 16 2.164472 5 54.8 20.63 74.32657 0 44 1 2
0
0 11001 24 24 0 5.55 0 2 24 1.713798 5 54.8 20.63 74.32657 0 44 1 2 0
0 11001 48 48 0 3.5 0 2 48 1.252763 5 54.8 20.63 74.32657 0 44 1 3 0
0 11001 72 72 0 1.86 0 2 72 0.620576 5 54.8 20.63 74.32657 0 44 1 4 0
0 11001 120.883 120.883 0 0.597 0 2 120 -0.51584 5 54.8 20.63 74.32657 0 44
1 6 0
0 11001 144.9 144.9 0 0.356 0 2 144 -1.03282 5 54.8 20.63 74.32657 0 44 1 7
0
0 11001 168.883 168.883 0 0.177 0 2 168 -1.73161 5 54.8 20.63 74.32657 0 44
1 8 0
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