Dear NONMEM users,
I try to fit a dataset with a high variability in TLAG. With the
standard approaches it was not possible to get successful runs
(variability in Tlag is always modeled as zero, but their is clearly a
high variability)
Therefore I used the transit model, published by Justin Wilkins/Radoika
Savic. For single dose studies it works well (improved fit/successful
runs). Next , I included a multiple drug study and adapted the model.
The model works, but I have some questions regarding the code (see below
in red). It would be very nice if someone can help to enhance my
understanding.
Thank you in advance
Dirk
$SUBROUTINE ADVAN6 TOL=3
$MODEL NCOMP=3 COMP=(DEPOT) COMP=(CENTRAL,DEFOBS) COMP=(PERIPH)
$PK
"FIRST
" COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" IMAX=9900000
IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
IF(AMT.GT.0) TDOS=TIME
TVCL=THETA(1)
CL=TVCL*EXP(ETA(1))
TVV2=THETA(2)
V2=TVV2*EXP(ETA(2))
TVV3=THETA(3)
V3=TVV3*EXP(ETA(3))
TVQ=THETA(4)
Q=TVQ*EXP(ETA(4))
; Absorption model
;F1=0 delete NONMEMS Dose record
F1=0
TVKA=THETA(5)
KA=TVKA*EXP(ETA(5))
;Mean transit time
TVMTT=THETA(6)
MTT=TVMTT*EXP(ETA(6))
;Number of transit compartments
TVNN=THETA(7)
NN=TVNN*EXP(ETA(7))
;Transit rate constant
KTR=(NN+1)/MTT
;Sterling
L=LOG(2.5066)+(NN+.5)*LOG(NN)-NN
S2=V2/1000
; DOSE : mg
; CONC: ng/ml
$DES
X=0.00001; Avoid LOG 0
;multiple dose
IF(T.GE.TDOS)THEN ; if current time greater than TDOS
Is this correct? I think GE might be a typo and should be GT?
DADT(1) = EXP(LOG(PD + X) + LOG(KTR +
X)+NN*LOG(KTR*(T-TDOS)+X)-KTR*(T-TDOS)-L)-KA*A(1)
ELSE
; Dose given
DADT(1) = EXP(LOG(PD + X) + LOG(KTR + X)+ NN*LOG(KTR*T + X) - KTR*T -
L)- KA*A(1)
ENDIF
T.GE.TDOS (see above) might be a typo; otherwise this equation will
never be active?
I try this model with GT, the fit improves, but why is this statement
needed?
Can someone explain this (red) part of the equation, please?
I think if the time is e.g. 24 hours (time of second dose) the value of
the input function will be low, as it should be to simulate the lag time
(I used MTT=1, NN=4, to recalculate it). With further increased time
(next doses), the value of the input function will be approximately zero
(ok).
But without this equation and
IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
IF(AMT.GT.0) TDOS=TIME
(T-TDOS) should be zero at each dose event and the value of the input
function at a new dose event is also approximately zero (same as above?)
Any help to enhance my understanding is welcome
DADT(2)=KA*A(1)-Q/V2*A(2)+Q/V3*A(3)-CL/V2*A(2)
DADT(3)=Q/V2*A(2)-Q/V3*A(3)
$ERROR
One last question:
For some subjects I got some bizarre estimation values. I think this
might be because I have sometimes dose events, but no observations
(multiple dose study) prior to the next dose.. Therefore, if I correctly
understand the code, the input value for these dose events will be
approximately zero.
Any suggestions to solve this problem are welcome.
Best regards
Dirk Garmann
--------------------------------------------------------
SCHWARZ BIOSCIENCES GmbH
A Member of the UCB Group
Alfred-Nobel-Str. 10 - 40789 Monheim - Germany
Tel +49 2173 48 0 - Fax +49 2173 48 1608
Geschaeftsfuehrer: Prof. Dr. Iris Loew-Friedrich, Detlef Thielgen
Amtsgericht Duesseldorf HRB 46849
--------------------------------------------------------
Legal Notice: This electronic mail and its attachments are intended solely for
the person(s) to whom they are addressed and contain information which is
confidential or otherwise protected from disclosure, except for the purpose for
which they are intended. Dissemination, distribution, or reproduction by anyone
other than the intended recipients is prohibited and may be illegal. If you are
not an intended recipient, please immediately inform the sender and return the
electronic mail and its attachments and destroy any copies which may be in your
possession. UCB screens electronic mails for viruses but does not warrant that
this electronic mail is free of any viruses. UCB accepts no liability for any
damage caused by any virus transmitted by this electronic mail. (Ref: #*BG0508)
transit model
Dirk,
This absorption can correctly accommodate multiple dosing only if the absorption of dose n is complete when dose n+1 is given ! Since the input is hard-coded and reset at each dose, you have to make sure that the estimate you get for MTT and NN provide this complete absorption. Otherwise, part of each dose does never enter the system.
I don't really understand how you implemented the transit model but you may refer to the following code (for Wings for NONMEM) that worked just fine for me. The frame for the input function has to start at zero to I used a time transform based on a dosing interval of 24h. A column DAY is included in the dataset to calculate the new time MYT.
Hope it helps.
Sebastien Bihorel
$PROBLEM Simulation Transit model
$INPUT ID DOSE DAY TI24 TIME AMT RATX CMT EVID DVID DV MDV
$DATA ../Data/Simulation.csv IGNORE=#
$SIM (32047023) NSUB=1
$SUB ADVAN6 TOL3
$THETA (0,6.) ; POP_CL
$THETA (0,100.) ; POP_V2
$THETA (0,18.) ; POP_MTT
$THETA (0.00001,3.) ; POP_n
$THETA (0,6.) ; POP_TABS
$OMEGA BLOCK(2)
0.1 ; BSVCL
0.01 0.1 ; BSVV2
$OMEGA BLOCK(3)
0.1 ; BSVMTT
0.01 0.1 ; BSVN
0.01 0.01 0.1 ; BSVTABS
$SIGMA 0.1 ;cvcp
$SIGMA 0.05 ;sdcp
$MODEL COMP = (ABS) ; absorption compartment
COMP = (CEN) ; central compartment
;$ABBREVIATED DERIV2=NOCOMMON
$PK
"FIRST
" COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" IMAX=1000000
IF(AMT.GT.0.AND.CMT.EQ.1)PODO=AMT; oral dose
F1 = 0.
F2 = 0.
ECL = EXP(BSVCL)
EV2 = EXP(BSVV2)
EMTT = EXP(BSVMTT)
ENB = EXP(BSVN)
ETAB = EXP(BSVTABS)
CL = POP_CL * ECL
V = POP_V2 * EV2
MTT = (POP_MTT * EMTT)/60
NB = POP_n * ENB
TABS = POP_TABS * ETAB
KA = LOG(2)/(TABS/60)
KTR = (NB+1)/MTT ; transit rate constant
LNFA = 0.5*LOG(2*3.14159*NB)+NB*LOG(NB)-NB+LOG(1.+1./(12.*NB)) ; logarithmic transformation of 2nd Stirling approximation
S2 = V
BIO =1.
$DES
MYT = T -(DAY-1)*24
IF (MYT.LT.0.001) THEN
INPU = 0.
ELSE
INPU = EXP(LOG(BIO*PODO)+LOG(KTR)+NB*LOG(KTR*MYT)-KTR*MYT-LNFA)
ENDIF
DADT(1) = INPU-KA*A(1)
DADT(2) = (KA*A(1)-CL*A(2))/V
$ERROR
CP=A(2)
Y=CP*(1+CVCP)+SDCP
$TABLE ID DAY TIME AMT CMT EVID DVID Y
CL V MTT NB TABS ECL EV2 EMTT ENB ETAB
ONEHEADER NOPRINT
FILE=k0ka1l.fit
Garmann Dirk a écrit :
> Dear NONMEM users,
>
> I try to fit a dataset with a high variability in TLAG. With the standard approaches it was not possible to get successful runs (variability in Tlag is always modeled as zero, but their is clearly a high variability)
>
> Therefore I used the transit model, published by Justin Wilkins/Radoika Savic. For single dose studies it works well (improved fit/successful runs). Next , I included a multiple drug study and adapted the model. The model works, but I have some questions regarding the code (see below in red). It would be very nice if someone can help to enhance my understanding.
>
> Thank you in advance
>
> Dirk
>
> $SUBROUTINE ADVAN6 TOL=3
>
> $MODEL NCOMP=3 COMP=(DEPOT) COMP=(CENTRAL,DEFOBS) COMP=(PERIPH)
>
> $PK
>
> "FIRST
>
> " COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
>
> " INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
>
> " IMAX=9900000
>
> IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
>
> IF(AMT.GT.0) TDOS=TIME
>
> TVCL=THETA(1)
>
> CL=TVCL*EXP(ETA(1))
>
> TVV2=THETA(2)
>
> V2=TVV2*EXP(ETA(2))
>
> TVV3=THETA(3)
>
> V3=TVV3*EXP(ETA(3))
>
> TVQ=THETA(4)
>
> Q=TVQ*EXP(ETA(4))
>
> ; Absorption model
>
> ;F1=0 delete NONMEMS Dose record
>
> F1=0
>
> TVKA=THETA(5)
>
> KA=TVKA*EXP(ETA(5))
>
> ;Mean transit time
>
> TVMTT=THETA(6)
>
> MTT=TVMTT*EXP(ETA(6))
>
> ;Number of transit compartments
>
> TVNN=THETA(7)
>
> NN=TVNN*EXP(ETA(7))
>
> ;Transit rate constant
>
> KTR=(NN+1)/MTT
>
> ;Sterling
>
> L=LOG(2.5066)+(NN+.5)*LOG(NN)-NN
>
> S2=V2/1000
>
> ; DOSE : mg
>
> ; CONC: ng/ml
>
> $DES
>
> X=0.00001; Avoid LOG 0
>
> ;multiple dose
>
> IF(T.GE.TDOS)THEN ; if current time greater than TDOS
>
> *Is this correct? I think GE might be a typo and should be GT?*
>
> * *
>
> DADT(1) = EXP(LOG(PD + X) + LOG(KTR + X)+NN*LOG(KTR*(T-TDOS)+X)-KTR*(T-TDOS)-L)-KA*A(1)
>
> ELSE
>
> ; Dose given
>
> DADT(1) = EXP(LOG(PD + X) + LOG(KTR + X)+ NN*LOG(KTR*T + X) - KTR*T - L)- KA*A(1)
>
> ENDIF
>
> *T.GE.TDOS (see above) might be a typo; otherwise this equation will never be active?*
>
> *I try this model with GT, the fit improves, but why is this statement needed?*
>
> * *
>
> *Can someone explain this (red) part of the equation, please? *
>
> *I think if the time is e.g. 24 hours (time of second dose) the value of the input function will be low, as it should be to simulate the lag time (I used MTT=1, NN=4, to recalculate it). With further increased time (next doses), the value of the input function will be approximately zero (ok). *
>
> * *
>
> *But _without_ this equation and *
>
> *IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT*
>
> *IF(AMT.GT.0) TDOS=TIME*
>
> * *
>
> *(T-TDOS) should be zero * *at each dose event* *and the value of the input function at a new dose event is also approximately zero (same as above?)*
>
> * *
>
> *Any help to enhance my understanding is welcome*
>
> DADT(2)=KA*A(1)-Q/V2*A(2)+Q/V3*A(3)-CL/V2*A(2)
>
> DADT(3)=Q/V2*A(2)-Q/V3*A(3)
>
> $ERROR
>
> *One last question:*
>
> *For some subjects I got some bizarre estimation values. I think this might be because I have sometimes dose events, but no observations (multiple dose study) prior to the next dose.. Therefore, if I correctly understand the code, the input value for these dose events will be approximately zero.*
>
> * *
>
> *Any suggestions to solve this problem are welcome.*
>
> **
>
> *Best regards*
>
> *Dirk Garmann*
>
> ------------------------------------------------------------------------
>
> SCHWARZ BIOSCIENCES GmbH
> A Member of the UCB Group
> Alfred-Nobel-Str. 10 - 40789 Monheim - Germany
> Tel +49 2173 48 0 - Fax +49 2173 48 1608
> Geschaeftsfuehrer: Prof. Dr. Iris Loew-Friedrich, Detlef Thielgen
> Amtsgericht Duesseldorf HRB 46849
> ------------------------------------------------------------------------
>
> Legal Notice: This electronic mail and its attachments are intended solely for the person(s) to whom they are addressed and contain information which is confidential or otherwise protected from disclosure, except for the purpose for which they are intended. Dissemination, distribution, or reproduction by anyone other than the intended recipients is prohibited and may be illegal. If you are not an intended recipient, please immediately inform the sender and return the electronic mail and its attachments and destroy any copies which may be in your possession. UCB screens electronic mails for viruses but does not warrant that this electronic mail is free of any viruses. UCB accepts no liability for any damage caused by any virus transmitted by this electronic mail. (Ref: #*BG0508)
>
>
Dear Dirk (and all),
This is a tricky one. After we got our heads together to look at it, we
realized that it's a bit more complex than it appears. The reason why we
use greater-than or equal to (T.GE.TDOS) instead of (T.GT.TDOS) is to get
around an issue with NONMEM. The easiest way to explain why is through an
example - given multiple dosing every 12 hours, and observations at 1, 2,
4, and 8 h post-dose, time after dose (TAD) will need to be set to 0 at
every 12-hourly dosing event - so at this point, TAD=0 and TDOS=12.
However, in order to integrate between 8 h and 12 h in this scheme, NONMEM
will use a TDOS value of 12 h here, resulting in negative values of TAD
over the 8-12h period - which will clearly produce undesirable results.
Using the IF-THEN structure with (T.GE.TDOS) is a cheat to overcome this.
However, as Sebastien pointed out, another assumption is introduced by
doing it this way - the dose is assumed to be fully absorbed by the last
observation event, in this case 8 h (as opposed to the time of the next
dose, 12 h). This may have fairly problematic consequences, especially
where you have a series of dosing events without observations between
them. We think the best way to tackle this will be to add dummy
observation records (using EVID=2) at inter-dose troughs (e.g. 11.9 h)
between each successive dose event - another method might be to leverage
NONMEM VI's very helpful model event time (MTIME) variable to take care of
this.
Hope this was helpful!
Best
Justin (and Rada)
Justin Wilkins
Novartis Pharma AG
PH346, MODELING & SIMULATION
CHBS, WSJ-027.1.084
Novartis Pharma AG
Lichtstrasse 35
CH-4056 Basel
Switzerland
Phone: +41 61 324 6549
Fax: +41 61 324 3039
Mobile: +41 76 561 0949
Email : justin.wilkins
Sbastien Bihorel <sbihorel
Sent by: owner-nmusers
27/08/2008 15:59
To
Garmann Dirk <Dirk.Garmann
cc
nmusers
Subject
Re: [NMusers] FW: transit model
(Sorry for the spelling mistakes)
Dirk,
This absorption model can correctly accommodate multiple dosing only if
the absorption of dose n is complete when dose n+1 is given ! Since the
input is hard-coded and reset at each dose, you have to make sure that
your estimates for MTT and NN provide this complete absorption. Otherwise,
a part of each dose never enters the system.
I don't really understand how you implemented the transit model but you
may refer to the following code (for Wings for NONMEM) that worked just
fine for me. The frame time for the input function has to start at zero,
so I used a time transform based on a dosing interval of 24h. A column DAY
is included in the dataset to calculate the new time MYT.
Hope it helps.
Sebastien Bihorel
$PROBLEM Simulation Transit model
$INPUT ID DOSE DAY TI24 TIME AMT RATX CMT EVID DVID DV MDV
$DATA ../Data/Simulation.csv IGNORE=#
$SIM (32047023) NSUB=1
$SUB ADVAN6 TOL3
$THETA (0,6.) ; POP_CL
$THETA (0,100.) ; POP_V2
$THETA (0,18.) ; POP_MTT
$THETA (0.00001,3.) ; POP_n
$THETA (0,6.) ; POP_TABS
$OMEGA BLOCK(2)
0.1 ; BSVCL
0.01 0.1 ; BSVV2
$OMEGA BLOCK(3)
0.1 ; BSVMTT
0.01 0.1 ; BSVN
0.01 0.01 0.1 ; BSVTABS
$SIGMA 0.1 ;cvcp
$SIGMA 0.05 ;sdcp
$MODEL COMP = (ABS) ; absorption compartment
COMP = (CEN) ; central compartment
;$ABBREVIATED DERIV2=NOCOMMON
$PK
"FIRST
" COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" IMAX00000
IF(AMT.GT.0.AND.CMT.EQ.1)PODO=AMT; oral dose
F1 = 0.
F2 = 0.
ECL = EXP(BSVCL)
EV2 = EXP(BSVV2)
EMTT = EXP(BSVMTT)
ENB = EXP(BSVN)
ETAB = EXP(BSVTABS)
CL = POP_CL * ECL
V = POP_V2 * EV2
MTT = (POP_MTT * EMTT)/60
NB = POP_n * ENB
TABS = POP_TABS * ETAB
KA = LOG(2)/(TABS/60)
KTR = (NB+1)/MTT ; transit rate constant
LNFA = 0.5*LOG(2*3.14159*NB)+NB*LOG(NB)-NB+LOG(1.+1./(12.*NB)) ;
logarithmic transformation of 2nd Stirling approximation
S2 = V
BIO =1.
$DES
MYT = T -(DAY-1)*24
IF (MYT.LT.0.001) THEN
INPU = 0.
ELSE
INPU = EXP(LOG(BIO*PODO)+LOG(KTR)+NB*LOG(KTR*MYT)-KTR*MYT-LNFA)
ENDIF
DADT(1) = INPU-KA*A(1)
DADT(2) = (KA*A(1)-CL*A(2))/V
$ERROR
CP=A(2)
Y=CP*(1+CVCP)+SDCP
$TABLE ID DAY TIME AMT CMT EVID DVID Y
CL V MTT NB TABS ECL EV2 EMTT ENB ETAB
ONEHEADER NOPRINT
FILE=k0ka1l.fit
Garmann Dirk a crit :
Dear NONMEM users,
I try to fit a dataset with a high variability in TLAG. With the standard
approaches it was not possible to get successful runs (variability in Tlag
is always modeled as zero, but their is clearly a high variability)
Therefore I used the transit model, published by Justin Wilkins/Radoika
Savic. For single dose studies it works well (improved fit/successful
runs). Next , I included a multiple drug study and adapted the model. The
model works, but I have some questions regarding the code (see below in
red). It would be very nice if someone can help to enhance my
understanding.
Thank you in advance
Dirk
$SUBROUTINE ADVAN6 TOL=3
$MODEL NCOMP=3 COMP=(DEPOT) COMP=(CENTRAL,DEFOBS) COMP=(PERIPH)
$PK
"FIRST
" COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" IMAX00000
IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
IF(AMT.GT.0) TDOS=TIME
TVCL=THETA(1)
CL=TVCL*EXP(ETA(1))
TVV2=THETA(2)
V2=TVV2*EXP(ETA(2))
TVV3=THETA(3)
V3=TVV3*EXP(ETA(3))
TVQ=THETA(4)
Q=TVQ*EXP(ETA(4))
; Absorption model
;F1=0 delete NONMEMS Dose record
F1=0
TVKA=THETA(5)
KA=TVKA*EXP(ETA(5))
;Mean transit time
TVMTT=THETA(6)
MTT=TVMTT*EXP(ETA(6))
;Number of transit compartments
TVNN=THETA(7)
NN=TVNN*EXP(ETA(7))
;Transit rate constant
KTR=(NN+1)/MTT
;Sterling
L=LOG(2.5066)+(NN+.5)*LOG(NN)-NN
S2=V2/1000
; DOSE : mg
; CONC: ng/ml
$DES
X=0.00001; Avoid LOG 0
;multiple dose
IF(T.GE.TDOS)THEN ; if current time greater than TDOS
Is this correct? I think GE might be a typo and should be GT?
DADT(1) = EXP(LOG(PD + X) + LOG(KTR +
X)+NN*LOG(KTR*(T-TDOS)+X)-KTR*(T-TDOS)-L)-KA*A(1)
ELSE
; Dose given
DADT(1) = EXP(LOG(PD + X) + LOG(KTR + X)+ NN*LOG(KTR*T + X) - KTR*T - L)-
KA*A(1)
ENDIF
T.GE.TDOS (see above) might be a typo; otherwise this equation will never
be active?
I try this model with GT, the fit improves, but why is this statement
needed?
Can someone explain this (red) part of the equation, please?
I think if the time is e.g. 24 hours (time of second dose) the value of
the input function will be low, as it should be to simulate the lag time
(I used MTT=1, NN=4, to recalculate it). With further increased time (next
doses), the value of the input function will be approximately zero (ok).
But without this equation and
IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
IF(AMT.GT.0) TDOS=TIME
(T-TDOS) should be zero at each dose event and the value of the input
function at a new dose event is also approximately zero (same as above?)
Any help to enhance my understanding is welcome
DADT(2)=KA*A(1)-Q/V2*A(2)+Q/V3*A(3)-CL/V2*A(2)
DADT(3)=Q/V2*A(2)-Q/V3*A(3)
$ERROR
One last question:
For some subjects I got some bizarre estimation values. I think this might
be because I have sometimes dose events, but no observations (multiple
dose study) prior to the next dose.. Therefore, if I correctly understand
the code, the input value for these dose events will be approximately
zero.
Any suggestions to solve this problem are welcome.
Best regards
Dirk Garmann
SCHWARZ BIOSCIENCES GmbH
A Member of the UCB Group
Alfred-Nobel-Str. 10 - 40789 Monheim - Germany
Tel +49 2173 48 0 - Fax +49 2173 48 1608
Geschaeftsfuehrer: Prof. Dr. Iris Loew-Friedrich, Detlef Thielgen
Amtsgericht Duesseldorf HRB 46849
Legal Notice: This electronic mail and its attachments are intended solely
for the person(s) to whom they are addressed and contain information which
is confidential or otherwise protected from disclosure, except for the
purpose for which they are intended. Dissemination, distribution, or
reproduction by anyone other than the intended recipients is prohibited
and may be illegal. If you are not an intended recipient, please
immediately inform the sender and return the electronic mail and its
attachments and destroy any copies which may be in your possession. UCB
screens electronic mails for viruses but does not warrant that this
electronic mail is free of any viruses. UCB accepts no liability for any
damage caused by any virus transmitted by this electronic mail. (Ref:
#*BG0508)
Dear Dirk (and all),
This is a tricky one. After we got our heads together to look at it, we
realized that it's a bit more complex than it appears. The reason why we
use greater-than or equal to (T.GE.TDOS) instead of (T.GT.TDOS) is to get
around an issue with NONMEM. The easiest way to explain why is through an
example - given multiple dosing every 12 hours, and observations at 1, 2,
4, and 8 h post-dose, time after dose (TAD) will need to be set to 0 at
every 12-hourly dosing event - so at this point, TAD==0 and TDOS==12.
However, in order to integrate between 8 h and 12 h in this scheme, NONMEM
will use a TDOS value of 12 h here, resulting in negative values of TAD
over the 8-12h period - which will clearly produce undesirable results.
Using the IF-THEN structure with (T.GE.TDOS) is a cheat to overcome this.
However, as Sebastien pointed out, another assumption is introduced by
doing it this way - the dose is assumed to be fully absorbed by the last
observation event, in this case 8 h (as opposed to the time of the next
dose, 12 h). This may have fairly problematic consequences, especially
where you have a series of dosing events without observations between
them. We think the best way to tackle this will be to add dummy
observation records (using EVID==2) at inter-dose troughs (e.g. 11.9 h)
between each successive dose event - another method might be to leverage
NONMEM VI's very helpful model event time (MTIME) variable to take care of
this.
Hope this was helpful!
Best
Justin (and Rada)
Justin Wilkins
Novartis Pharma AG
PH346, MODELING & SIMULATION
CHBS, WSJ-027.1.084
Novartis Pharma AG
Lichtstrasse 35
CH-4056 Basel
Switzerland
Phone: +41 61 324 6549
Fax: +41 61 324 3039
Mobile: +41 76 561 0949
Email : [EMAIL PROTECTED]
Sébastien Bihorel <[EMAIL PROTECTED]>
Sent by: [EMAIL PROTECTED]
27/08/2008 15:59
To
Garmann Dirk <[EMAIL PROTECTED]>
cc
[email protected]
Subject
Re: [NMusers] FW: transit model
(Sorry for the spelling mistakes)
Dirk,
This absorption model can correctly accommodate multiple dosing only if
the absorption of dose n is complete when dose n+1 is given ! Since the
input is hard-coded and reset at each dose, you have to make sure that
your estimates for MTT and NN provide this complete absorption. Otherwise,
a part of each dose never enters the system.
I don't really understand how you implemented the transit model but you
may refer to the following code (for Wings for NONMEM) that worked just
fine for me. The frame time for the input function has to start at zero,
so I used a time transform based on a dosing interval of 24h. A column DAY
is included in the dataset to calculate the new time MYT.
Hope it helps.
Sebastien Bihorel
$PROBLEM Simulation Transit model
$INPUT ID DOSE DAY TI24 TIME AMT RATX CMT EVID DVID DV MDV
$DATA ../Data/Simulation.csv IGNORE=#
$SIM (32047023) NSUB=1
$SUB ADVAN6 TOL3
$THETA (0,6.) ; POP_CL
$THETA (0,100.) ; POP_V2
$THETA (0,18.) ; POP_MTT
$THETA (0.00001,3.) ; POP_n
$THETA (0,6.) ; POP_TABS
$OMEGA BLOCK(2)
0.1 ; BSVCL
0.01 0.1 ; BSVV2
$OMEGA BLOCK(3)
0.1 ; BSVMTT
0.01 0.1 ; BSVN
0.01 0.01 0.1 ; BSVTABS
$SIGMA 0.1 ;cvcp
$SIGMA 0.05 ;sdcp
$MODEL COMP = (ABS) ; absorption compartment
COMP = (CEN) ; central compartment
;$ABBREVIATED DERIV2=NOCOMMON
$PK
"FIRST
" COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" IMAX=1000000
IF(AMT.GT.0.AND.CMT.EQ.1)PODO=AMT; oral dose
F1 = 0.
F2 = 0.
ECL = EXP(BSVCL)
EV2 = EXP(BSVV2)
EMTT = EXP(BSVMTT)
ENB = EXP(BSVN)
ETAB = EXP(BSVTABS)
CL = POP_CL * ECL
V = POP_V2 * EV2
MTT = (POP_MTT * EMTT)/60
NB = POP_n * ENB
TABS = POP_TABS * ETAB
KA = LOG(2)/(TABS/60)
KTR = (NB+1)/MTT ; transit rate constant
LNFA = 0.5*LOG(2*3.14159*NB)+NB*LOG(NB)-NB+LOG(1.+1./(12.*NB)) ;
logarithmic transformation of 2nd Stirling approximation
S2 = V
BIO =1.
$DES
MYT = T -(DAY-1)*24
IF (MYT.LT.0.001) THEN
INPU = 0.
ELSE
INPU = EXP(LOG(BIO*PODO)+LOG(KTR)+NB*LOG(KTR*MYT)-KTR*MYT-LNFA)
ENDIF
DADT(1) = INPU-KA*A(1)
DADT(2) = (KA*A(1)-CL*A(2))/V
$ERROR
CP=A(2)
Y=CP*(1+CVCP)+SDCP
$TABLE ID DAY TIME AMT CMT EVID DVID Y
CL V MTT NB TABS ECL EV2 EMTT ENB ETAB
ONEHEADER NOPRINT
FILE=k0ka1l.fit
Garmann Dirk a écrit :
Dear NONMEM users,
I try to fit a dataset with a high variability in TLAG. With the standard
approaches it was not possible to get successful runs (variability in Tlag
is always modeled as zero, but their is clearly a high variability)
Therefore I used the transit model, published by Justin Wilkins/Radoika
Savic. For single dose studies it works well (improved fit/successful
runs). Next , I included a multiple drug study and adapted the model. The
model works, but I have some questions regarding the code (see below in
red). It would be very nice if someone can help to enhance my
understanding.
Thank you in advance
Dirk
$SUBROUTINE ADVAN6 TOL=3
$MODEL NCOMP=3 COMP=(DEPOT) COMP=(CENTRAL,DEFOBS) COMP=(PERIPH)
$PK
"FIRST
" COMMON /PRCOMG/ IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" INTEGER IDUM1,IDUM2,IMAX,IDUM4,IDUM5
" IMAX=9900000
IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
IF(AMT.GT.0) TDOS=TIME
TVCL=THETA(1)
CL=TVCL*EXP(ETA(1))
TVV2=THETA(2)
V2=TVV2*EXP(ETA(2))
TVV3=THETA(3)
V3=TVV3*EXP(ETA(3))
TVQ=THETA(4)
Q=TVQ*EXP(ETA(4))
; Absorption model
;F1=0 delete NONMEMS Dose record
F1=0
TVKA=THETA(5)
KA=TVKA*EXP(ETA(5))
;Mean transit time
TVMTT=THETA(6)
MTT=TVMTT*EXP(ETA(6))
;Number of transit compartments
TVNN=THETA(7)
NN=TVNN*EXP(ETA(7))
;Transit rate constant
KTR=(NN+1)/MTT
;Sterling
L=LOG(2.5066)+(NN+.5)*LOG(NN)-NN
S2=V2/1000
; DOSE : mg
; CONC: ng/ml
$DES
X=0.00001; Avoid LOG 0
;multiple dose
IF(T.GE.TDOS)THEN ; if current time greater than TDOS
Is this correct? I think GE might be a typo and should be GT?
DADT(1) = EXP(LOG(PD + X) + LOG(KTR +
X)+NN*LOG(KTR*(T-TDOS)+X)-KTR*(T-TDOS)-L)-KA*A(1)
ELSE
; Dose given
DADT(1) = EXP(LOG(PD + X) + LOG(KTR + X)+ NN*LOG(KTR*T + X) - KTR*T - L)-
KA*A(1)
ENDIF
T.GE.TDOS (see above) might be a typo; otherwise this equation will never
be active?
I try this model with GT, the fit improves, but why is this statement
needed?
Can someone explain this (red) part of the equation, please?
I think if the time is e.g. 24 hours (time of second dose) the value of
the input function will be low, as it should be to simulate the lag time
(I used MTT=1, NN=4, to recalculate it). With further increased time (next
doses), the value of the input function will be approximately zero (ok).
But without this equation and
IF(AMT.GT.0.AND.CMT.EQ.1) PD=AMT
IF(AMT.GT.0) TDOS=TIME
(T-TDOS) should be zero at each dose event and the value of the input
function at a new dose event is also approximately zero (same as above?)
Any help to enhance my understanding is welcome
DADT(2)=KA*A(1)-Q/V2*A(2)+Q/V3*A(3)-CL/V2*A(2)
DADT(3)=Q/V2*A(2)-Q/V3*A(3)
$ERROR
One last question:
For some subjects I got some bizarre estimation values. I think this might
be because I have sometimes dose events, but no observations (multiple
dose study) prior to the next dose.. Therefore, if I correctly understand
the code, the input value for these dose events will be approximately
zero.
Any suggestions to solve this problem are welcome.
Best regards
Dirk Garmann
SCHWARZ BIOSCIENCES GmbH
A Member of the UCB Group
Alfred-Nobel-Str. 10 - 40789 Monheim - Germany
Tel +49 2173 48 0 - Fax +49 2173 48 1608
Geschaeftsfuehrer: Prof. Dr. Iris Loew-Friedrich, Detlef Thielgen
Amtsgericht Duesseldorf HRB 46849
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