Dear all,
I have a question concerning the nonparametric estimation in NONMEM. I
used the nonparametric method for phase I single dose PK data because
parameters seemed not to be normally distributed. The dataset contained 40
subjects and each received 3 different doses. The model fit the data well,
and as a last evaluation I wanted to simulate 500 new subjects for each
dose level and compare the simulations to the observed values (in a
spaghetti plot which includes all simulated profiles as half-transparent,
which enables the identification of concentrations which are repeated more
often than others, as the respective area is darker). For comparison, I
wanted to use the IPRED values and disregard the residual error component.
What puzzled me when I saw the plot was that I did only see as many lines
as I had subjects in the trial. So my question is: If I only have a
limited number of subjects, does it make sense to use a nonparametric
method at all, because the simulations I get from this seem to be a bit
limited? Do I only get the exact parameter combination as I have already
observed with my subjects, or can a nonparametric method also simulate
other parameter combinations (in my case I have IIV on three different
parameters)? The used model code is shown below.
Thanks and best regards
Nele
$MODEL COMP=(GUT) COMP=(CENTRAL) COMP=(PERIPH) COMP=(BINDING)
;
$PK
JDN_
DN1EN_(1)
DN2EN_(2)
DN3EN_(3)
;
TVCL=THETA(1)
CL=TVCL*EXP(ETA(1))
TVV2=THETA(2)
V2=TVV2*EXP(ETA(3))
TVQ=THETA(3)
Q=TVQ
TVV3=THETA(4)
V3=TVV3
TVKA=THETA(5)
KA=TVKA
TVF1=THETA(6)
F1=TVF1*EXP(ETA(2))
TVLAG=THETA(7)
ALAG1=TVLAG
TVK1=THETA(8)
K1=TVK1
TVK2=THETA(9)
K2=TVK2
TVBMAX=THETA(10)
BMAX=TVBMAX
S2=V2
K23=Q/V2
K32=Q/V3
K20=CL/V2
$DES
DADT(1)=-KA*A(1)
DADT(2)= KA*A(1)-K23*A(2)+K32*A(3)-K20*A(2)-K1*A(2)*(BMAX-A(4))+K2*A(4)
DADT(3)= K23*A(2)-K32*A(3)
DADT(4)= K1*A(2)*(BMAX-A(4))-K2*A(4)
;
$ERROR
IPRED=F
DEL=0
IF (IPRED.EQ.0) DEL=0.0001
W=F
IRES=DV-IPRED
IWRES=IRES/(W+DEL)
Y=F+SQRT(THETA(12)*THETA(12)+THETA(11)*THETA(11)*F**2)*EPS(1)
$MSFI=msfb1
$SIMULATION (12245) (123456 NONPARAMETRIC) ONLYSIM TRUE=FINAL
SUBPROBLEMSP0
$TABLE ID TIME TAD DOSE DV IPRED NOPRINT ONEHEADER FILE=simtab073
______________________________________________________________
Dr. Nele Kner
Pharmacometrics -- Modeling and Simulation
Nycomed GmbH
Byk-Gulden-Str. 2
D-78467 Konstanz, Germany
Fon: (+49) 7531 / 84 - 4759
Fax: (+49) 7531 / 84 - 94759
mailto: nele.kaessner
http://www.nycomed.com
County Court: Freiburg, Commercial Register HRB 701257
Chairman Supervisory Board: Charles Depasse
Management Board: Dr. Barthold Piening, Gilbert Rademacher, Dr. Anders
Ullman
----------------------------------------------------------------------
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simulation with nonparametric method in NONMEM
Dear all,
I have a question concerning the nonparametric estimation in NONMEM. I
used the nonparametric method for phase I single dose PK data because
parameters seemed not to be normally distributed. The dataset contained 40
subjects and each received 3 different doses. The model fit the data well,
and as a last evaluation I wanted to simulate 500 new subjects for each
dose level and compare the simulations to the observed values (in a
spaghetti plot which includes all simulated profiles as half-transparent,
which enables the identification of concentrations which are repeated more
often than others, as the respective area is darker). For comparison, I
wanted to use the IPRED values and disregard the residual error component.
What puzzled me when I saw the plot was that I did only see as many lines
as I had subjects in the trial. So my question is: If I only have a
limited number of subjects, does it make sense to use a nonparametric
method at all, because the simulations I get from this seem to be a bit
limited? Do I only get the exact parameter combination as I have already
observed with my subjects, or can a nonparametric method also simulate
other parameter combinations (in my case I have IIV on three different
parameters)? The used model code is shown below.
Thanks and best regards
Nele
$MODEL COMP=(GUT) COMP=(CENTRAL) COMP=(PERIPH) COMP=(BINDING)
;
$PK
JD=DEN_
DN1=CDEN_(1)
DN2=CDEN_(2)
DN3=CDEN_(3)
;
TVCL=THETA(1)
CL=TVCL*EXP(ETA(1))
TVV2=THETA(2)
V2=TVV2*EXP(ETA(3))
TVQ=THETA(3)
Q=TVQ
TVV3=THETA(4)
V3=TVV3
TVKA=THETA(5)
KA=TVKA
TVF1=THETA(6)
F1=TVF1*EXP(ETA(2))
TVLAG=THETA(7)
ALAG1=TVLAG
TVK1=THETA(8)
K1=TVK1
TVK2=THETA(9)
K2=TVK2
TVBMAX=THETA(10)
BMAX=TVBMAX
S2=V2
K23=Q/V2
K32=Q/V3
K20=CL/V2
$DES
DADT(1)=-KA*A(1)
DADT(2)= KA*A(1)-K23*A(2)+K32*A(3)-K20*A(2)-K1*A(2)*(BMAX-A(4))+K2*A(4)
DADT(3)= K23*A(2)-K32*A(3)
DADT(4)= K1*A(2)*(BMAX-A(4))-K2*A(4)
;
$ERROR
IPRED=F
DEL=0
IF (IPRED.EQ.0) DEL=0.0001
W=F
IRES=DV-IPRED
IWRES=IRES/(W+DEL)
Y=F+SQRT(THETA(12)*THETA(12)+THETA(11)*THETA(11)*F**2)*EPS(1)
$MSFI=msfb1
$SIMULATION (12245) (123456 NONPARAMETRIC) ONLYSIM TRUE=FINAL
SUBPROBLEMS=500
$TABLE ID TIME TAD DOSE DV IPRED NOPRINT ONEHEADER FILE=simtab073
______________________________________________________________
Dr. Nele Käßner
Pharmacometrics -- Modeling and Simulation
Nycomed GmbH
Byk-Gulden-Str. 2
D-78467 Konstanz, Germany
Fon: (+49) 7531 / 84 - 4759
Fax: (+49) 7531 / 84 - 94759
mailto: [email protected]
http://www.nycomed.com
County Court: Freiburg, Commercial Register HRB 701257
Chairman Supervisory Board: Charles Depasse
Management Board: Dr. Barthold Piening, Gilbert Rademacher, Dr. Anders
Ullman
----------------------------------------------------------------------
Proprietary or confidential information belonging to Nycomed Group may
be contained in this message. If you are not the addressee indicated
in this message, please do not copy or deliver this message to anyone.
In such case, please destroy this message and notify the sender by
reply e-mail. Please advise the sender immediately if you or your
employer do not consent to Internet e-mail for messages of this kind.
Opinions, conclusions and other information in this message that
pertain to the sender's employer and its products and services
represent the opinion of the sender and do not necessarily represent
or reflect the views and opinions of the employer.
Dear Nele,
Simulating with the nonparametric option in NONMEM is performed by sampling based on the original nonparametric distribution you obtained by fitting your data. Therefore, values of simulated nonparametric IPRED will all be issued from the estimated IPRED, the difference between simulated and estimated distribution of IPRED being in the frequency of appearance (spike height).
Hope this helps.
Paul.
Quoting [email protected]:
> Dear all,
>
> I have a question concerning the nonparametric estimation in NONMEM. I
> used the nonparametric method for phase I single dose PK data because
> parameters seemed not to be normally distributed. The dataset contained 40
> subjects and each received 3 different doses. The model fit the data well,
> and as a last evaluation I wanted to simulate 500 new subjects for each
> dose level and compare the simulations to the observed values (in a
> spaghetti plot which includes all simulated profiles as half-transparent,
> which enables the identification of concentrations which are repeated more
> often than others, as the respective area is darker). For comparison, I
> wanted to use the IPRED values and disregard the residual error component.
> What puzzled me when I saw the plot was that I did only see as many lines
> as I had subjects in the trial. So my question is: If I only have a
> limited number of subjects, does it make sense to use a nonparametric
> method at all, because the simulations I get from this seem to be a bit
> limited? Do I only get the exact parameter combination as I have already
> observed with my subjects, or can a nonparametric method also simulate
> other parameter combinations (in my case I have IIV on three different
> parameters)? The used model code is shown below.
>
> Thanks and best regards
> Nele
>
> $MODEL COMP=(GUT) COMP=(CENTRAL) COMP=(PERIPH) COMP=(BINDING)
> ;
> $PK
>
> JD=DEN_
> DN1=CDEN_(1)
> DN2=CDEN_(2)
> DN3=CDEN_(3)
>
> ;
> TVCL=THETA(1)
> CL=TVCL*EXP(ETA(1))
>
> TVV2=THETA(2)
> V2=TVV2*EXP(ETA(3))
>
> TVQ=THETA(3)
> Q=TVQ
>
> TVV3=THETA(4)
> V3=TVV3
>
> TVKA=THETA(5)
> KA=TVKA
>
> TVF1=THETA(6)
> F1=TVF1*EXP(ETA(2))
>
> TVLAG=THETA(7)
> ALAG1=TVLAG
>
> TVK1=THETA(8)
> K1=TVK1
>
> TVK2=THETA(9)
> K2=TVK2
>
> TVBMAX=THETA(10)
> BMAX=TVBMAX
>
> S2=V2
> K23=Q/V2
> K32=Q/V3
> K20=CL/V2
>
> $DES
>
> DADT(1)=-KA*A(1)
> DADT(2)= KA*A(1)-K23*A(2)+K32*A(3)-K20*A(2)-K1*A(2)*(BMAX-A(4))+K2*A(4)
> DADT(3)= K23*A(2)-K32*A(3)
> DADT(4)= K1*A(2)*(BMAX-A(4))-K2*A(4)
> ;
> $ERROR
> IPRED=F
> DEL=0
> IF (IPRED.EQ.0) DEL=0.0001
> W=F
> IRES=DV-IPRED
> IWRES=IRES/(W+DEL)
> Y=F+SQRT(THETA(12)*THETA(12)+THETA(11)*THETA(11)*F**2)*EPS(1)
>
> $MSFI=msfb1
> $SIMULATION (12245) (123456 NONPARAMETRIC) ONLYSIM TRUE=FINAL
> SUBPROBLEMS=500
> $TABLE ID TIME TAD DOSE DV IPRED NOPRINT ONEHEADER FILE=simtab073
> ______________________________________________________________
>
> Dr. Nele Käßner
> Pharmacometrics -- Modeling and Simulation
>
> Nycomed GmbH
> Byk-Gulden-Str. 2
> D-78467 Konstanz, Germany
>
> Fon: (+49) 7531 / 84 - 4759
> Fax: (+49) 7531 / 84 - 94759
>
> mailto: [email protected]
> http://www.nycomed.com
>
> County Court: Freiburg, Commercial Register HRB 701257
> Chairman Supervisory Board: Charles Depasse
> Management Board: Dr. Barthold Piening, Gilbert Rademacher, Dr. Anders
> Ullman
>
> ----------------------------------------------------------------------
> Proprietary or confidential information belonging to Nycomed Group may
> be contained in this message. If you are not the addressee indicated
> in this message, please do not copy or deliver this message to anyone.
> In such case, please destroy this message and notify the sender by
> reply e-mail. Please advise the sender immediately if you or your
> employer do not consent to Internet e-mail for messages of this kind.
> Opinions, conclusions and other information in this message that
> pertain to the sender's employer and its products and services
> represent the opinion of the sender and do not necessarily represent
> or reflect the views and opinions of the employer.
>