Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some
strange PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data)
both have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time
point). IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or
whether PRED values for BQL means something else other than prediction for
BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
Strange PRED prediction in SAEM with M3 BQL handling
Hi Andrew,
When your observation is <BLQ, M3 gives you a likelihood of this value being <
BLQ in the PRED column. So this value will be close to 1 when the model is
fairly sure that the concentration should be BLQ. This might explain why the
PREDs might be relatively high in your diagnostics here. I usually exlude the
<BLQ values in my GOF diagnostics, and check for model misspecification with a
VPC showing BLQ data (as described in
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/ ). You can do this with
the old xpose package. I don’t think there is any way to visualize the BLQ
prediction in the ‘usual’ GOF but I’m very curious if someone else has some
ideas regarding this.
Kind regards,
Cornelis Smit
Hospital Pharmacist / PhD candidate
Dept. of Clinical Pharmacy
St. Antonius Hospital
Dept. of Pharmacology,
Leiden Academic Centre for Drug Research,
Leiden University, Leiden, The Netherlands
VRIJWARING: Dit e-mail bericht is uitsluitend bestemd voor de geadresseerde(n).
Verstrekking aan en gebruik door anderen
is niet toegestaan. Als u niet de geadresseerde bent, stel dan de verzender
hiervan op de hoogte en verwijder het bericht.
Aan de inhoud van dit bericht kunnen geen rechten worden ontleend.
Quoted reply history
Van: [email protected] [mailto:[email protected]] Namens
Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
Aan: [email protected]
Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange
PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both
have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time point).
IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether
PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
Dear Andrew, Cornelis,
To add to Cornelis’s answer, likelihood function is not pdf and the integral is
not necessarily equal to 1, so I think it should not be judged by checking how
close it is to 1.
Warm regards,
Tingjie Guo
Quoted reply history
From: <[email protected]> on behalf of "Smit, Cornelis (Klinische
Farmacie)" <[email protected]>
Date: Friday, 22 February 2017 at 11:22
To: "[email protected]" <[email protected]>
Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Hi Andrew,
When your observation is <BLQ, M3 gives you a likelihood of this value being <
BLQ in the PRED column. So this value will be close to 1 when the model is
fairly sure that the concentration should be BLQ. This might explain why the
PREDs might be relatively high in your diagnostics here. I usually exlude the
<BLQ values in my GOF diagnostics, and check for model misspecification with a
VPC showing BLQ data (as described in
www.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2691472%2F&data=02%7C01%7C%7Cb08e3cd2c19e4b6e8a3608d698afb449%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C636864277737648346&sdata=UNUEYX%2FUiotcqhT423WbAQ1gxg%2FM6aVf%2FbcBd9bF0r8%3D&reserved=0">https://nam03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2691472%2F&data=02%7C01%7C%7Cb08e3cd2c19e4b6e8a3608d698afb449%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C636864277737648346&sdata=UNUEYX%2FUiotcqhT423WbAQ1gxg%2FM6aVf%2FbcBd9bF0r8%3D&reserved=0
). You can do this with the old xpose package. I don’t think there is any way
to visualize the BLQ prediction in the ‘usual’ GOF but I’m very curious if
someone else has some ideas regarding this.
Kind regards,
Cornelis Smit
Hospital Pharmacist / PhD candidate
Dept. of Clinical Pharmacy
St. Antonius Hospital
Dept. of Pharmacology,
Leiden Academic Centre for Drug Research,
Leiden University, Leiden, The Netherlands
VRIJWARING: Dit e-mail bericht is uitsluitend bestemd voor de geadresseerde(n).
Verstrekking aan en gebruik door anderen
is niet toegestaan. Als u niet de geadresseerde bent, stel dan de verzender
hiervan op de hoogte en verwijder het bericht.
Aan de inhoud van dit bericht kunnen geen rechten worden ontleend.
Van: [email protected] [mailto:[email protected]] Namens
Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
Aan: [email protected]
Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange
PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both
have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time point).
IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether
PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
Normally, the NONMEM reserved variable PRED will be automatically calculated
for the user when the data is the typical normally distributed type. However,
when data are modeled with a user specified likelihood (F_FLAG>0), the PRED
value will be set to an uninformative value. To get around this,
In $ERROR block, right after you define IPRED, insert
IF(COMACT==1) PREDV=IPRED
and add PREDV as one of your table items. During COMACT=1, your model will be
evaluated at ETA=0, and you can use that to pick out IPRED evaluated at ETA=0,
which is equivalent to the normal meaning of PRED.
Robert J. Bauer, Ph.D.
Senior Director
Pharmacometrics R&D
ICON Early Phase
820 W. Diamond Avenue
Suite 100
Gaithersburg, MD 20878
Office: (215) 616-6428
Mobile: (925) 286-0769
[email protected]<mailto:[email protected]>
http://www.iconplc.com/
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Andrew Tse
Sent: Friday, February 22, 2019 1:23 AM
To: [email protected]
Subject: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange
PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both
have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time point).
IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether
PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
One can get PRED at BQLs using COMACT option, see manual:
"COMACT=1 is a pass with final thetas and zero-valued etas".
Things computed at this stage are based on THETAS with zero ETAs and thus provide PRED values. E.g.,
IPRED = ...
IF(COMACT==1) PRED1=IPRED
creates the PRED1 variable that is a population prediction even at BQL records.
Have not tried it but it looks like it can be used to create population predictions of other derived variables as well (like AUC, half-life, etc.) that need to be computed based on THETAs (with ETAs equal to zero).
Leonid
Quoted reply history
On 2/22/2019 5:11 AM, Smit, Cornelis (Klinische Farmacie) wrote:
> Hi Andrew,
>
> When your observation is <BLQ, M3 gives you a likelihood of this value being < BLQ in the PRED column. So this value will be close to 1 when the model is fairly sure that the concentration should be BLQ. This might explain why the PREDs might be relatively high in your diagnostics here. I usually exlude the <BLQ values in my GOF diagnostics, and check for model misspecification with a VPC showing BLQ data (as described in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/ ). You can do this with the old xpose package. I don’t think there is any way to visualize the BLQ prediction in the ‘usual’ GOF but I’m very curious if someone else has some ideas regarding this.
>
> Kind regards,
>
> *Cornelis Smit*
> Hospital Pharmacist / PhD candidate
>
> Dept. of Clinical Pharmacy
> St. Antonius Hospital
>
> Dept. of Pharmacology,
>
> Leiden Academic Centre for Drug Research,
>
> Leiden University, Leiden, The Netherlands
>
> //
>
> /VRIJWARING: Dit e-mail bericht is uitsluitend bestemd voor de geadresseerde(n). Verstrekking aan en gebruik door anderen is niet toegestaan. Als u niet de geadresseerde bent, stel dan de verzender hiervan op de hoogte en verwijder het bericht.
>
> Aan de inhoud van dit bericht kunnen geen rechten worden ontleend./
>
> *Van:* [email protected] [ mailto: [email protected] ] *Namens *Andrew Tse
>
> *Verzonden:* vrijdag 22 februari 2019 10:23
> *Aan:* [email protected]
> *Onderwerp:* [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
>
> Dear all,
>
> I am running SAEM with M3 BQL handling method via PsN but having some strange PRED values in mytab table if someone can shed some light:
>
> I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both have normal looking fitting with data in individual plots.
>
> Once I have coded SAEM with M3 codes and include BQL data it showed very strange PRED vs time plots (eg. 100 times over prediction at BQL time point). IPRED had normal results.
>
> Here are the control stream that I have used:
>
> $PK
>
> TVCL=THETA(1)
>
> MU_1=LOG(TVCL)
>
> CL=EXP(MU_1+ETA(1))
>
> TVV2=THETA(2)
>
> MU_2=LOG(TVV2)
>
> V2=EXP(MU_2+ETA(2))
>
> TVQ=THETA(3)
>
> MU_3=LOG(TVQ)
>
> Q=EXP(MU_3+ETA(3))
>
> TVV3=THETA(4)
>
> MU_4=LOG(TVV3)
>
> V3=EXP(MU_4+ETA(4))
>
> K23=Q/V2 ;Distribution rate constant
>
> K32=Q/V3 ;Distribution rate constant
>
> KA=0
>
> A_0(1)=0
>
> A_0(2)=0
>
> A_0(3)=0
>
> $DES
>
> DADT(1)= -KA*A(1)
>
> DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
>
> DADT(3)= K23*A(2)-K32*A(3)
>
> $ERROR
>
> IPRED=A(2)/V2
>
> W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
>
> IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
>
> IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
>
> IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
>
> IF(BQL.EQ.0) THEN
>
> F_FLAG=0
>
> Y=IPRED+W*ERR(1)
>
> ELSE
>
> F_FLAG=1 ;BQL so Y is likelihood
>
> Y=PHI((LIM-IPRED)/W)
>
> ENDIF
>
> IWRES=(DV-IPRED)/W
>
> IRES=DV-IPRED
>
> My question is that whether there is error in my M3 $ERROR model? or whether PRED values for BQL means something else other than prediction for BQL data?
>
> Thanks a lot.
>
> Kind regards,
>
> Andrew Tse
>
> Research Pharmacist
Dear Cornelis,
Please have a look at the following for how to visualise NPDEs with a "PRED" for BLQ data:
Nguyen THT, Comets E. Mentre F. Extension of NPDE for evaluation of nonlinear mixed
effect models in presence of data below the quantification limit with applications to HIV
dynamic model. J Pharmacokinet Pharmacodyn (2012) 39:499518
This is possible to implement in NONMEM as per the 7.4 userguide NPDE section for the code.
BW,
Joe
Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Honorary Senior Lecturer, St George's University of London
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
Quoted reply history
________________________________________
From: owner-nmusers_at_globomaxnm.com [owner-nmusers_at_globomaxnm.com] on behalf of Smit, Cornelis (Klinische Farmacie) [c.smit1_at_antoniusziekenhuis.nl]
Sent: 22 February 2019 10:11
To: nmusers_at_globomaxnm.com
Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Hi Andrew,
When your observation is <BLQ, M3 gives you a likelihood of this value being < BLQ in the PRED column. So this value will be close to 1 when the model is fairly sure that the concentration should be BLQ. This might explain why the PREDs might be relatively high in your diagnostics here. I usually exlude the <BLQ values in my GOF diagnostics, and check for model misspecification with a VPC showing BLQ data (as described in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/ ). You can do this with the old xpose package. I dont think there is any way to visualize the BLQ prediction in the usual GOF but Im very curious if someone else has some ideas regarding this.
Kind regards,
Cornelis Smit
Hospital Pharmacist / PhD candidate
Dept. of Clinical Pharmacy
St. Antonius Hospital
Dept. of Pharmacology,
Leiden Academic Centre for Drug Research,
Leiden University, Leiden, The Netherlands
VRIJWARING: Dit e-mail bericht is uitsluitend bestemd voor de geadresseerde(n). Verstrekking aan en gebruik door anderen
is niet toegestaan. Als u niet de geadresseerde bent, stel dan de verzender hiervan op de hoogte en verwijder het bericht.
Aan de inhoud van dit bericht kunnen geen rechten worden ontleend.
Van: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] Namens Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
Aan: nmusers_at_globomaxnm.com
Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very strange PRED vs time plots (eg. 100 times over prediction at BQL time point). IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
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Dear Cornelis,
Please have a look at the following for how to visualise NPDEs with a "PRED"
for BLQ data:
Nguyen THT, Comets E. Mentre ́ F. Extension of NPDE for evaluation of nonlinear
mixed
effect models in presence of data below the quantification limit with
applications to HIV
dynamic model. J Pharmacokinet Pharmacodyn (2012) 39:499–518
This is possible to implement in NONMEM as per the 7.4 userguide NPDE section
for the code.
BW,
Joe
Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Honorary Senior Lecturer, St George's University of London
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
Quoted reply history
________________________________________
From: [email protected] [[email protected]] on behalf of
Smit, Cornelis (Klinische Farmacie) [[email protected]]
Sent: 22 February 2019 10:11
To: [email protected]
Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Hi Andrew,
When your observation is <BLQ, M3 gives you a likelihood of this value being <
BLQ in the PRED column. So this value will be close to 1 when the model is
fairly sure that the concentration should be BLQ. This might explain why the
PREDs might be relatively high in your diagnostics here. I usually exlude the
<BLQ values in my GOF diagnostics, and check for model misspecification with a
VPC showing BLQ data (as described in
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/ ). You can do this with
the old xpose package. I don’t think there is any way to visualize the BLQ
prediction in the ‘usual’ GOF but I’m very curious if someone else has some
ideas regarding this.
Kind regards,
Cornelis Smit
Hospital Pharmacist / PhD candidate
Dept. of Clinical Pharmacy
St. Antonius Hospital
Dept. of Pharmacology,
Leiden Academic Centre for Drug Research,
Leiden University, Leiden, The Netherlands
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Van: [email protected] [mailto:[email protected]] Namens
Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
Aan: [email protected]
Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange
PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both
have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time point).
IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether
PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
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NONMEM 7.4.3 is the most up-to-date in usage of NPDE on BLQ records.
Robert J. Bauer, Ph.D.
Senior Director
Pharmacometrics R&D
ICON Early Phase
820 W. Diamond Avenue
Suite 100
Gaithersburg, MD 20878
Office: (215) 616-6428
Mobile: (925) 286-0769
[email protected]<mailto:[email protected]>
http://www.iconplc.com/
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of STANDING, Joseph (GREAT ORMOND STREET HOSPITAL FOR CHILDREN NHS
FOUNDATION TRUST)
Sent: Monday, February 25, 2019 1:32 AM
To: Smit, Cornelis (Klinische Farmacie); [email protected]
Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear Cornelis,
Please have a look at the following for how to visualise NPDEs with a "PRED"
for BLQ data:
Nguyen THT, Comets E. Mentre ́ F. Extension of NPDE for evaluation of nonlinear
mixed
effect models in presence of data below the quantification limit with
applications to HIV
dynamic model. J Pharmacokinet Pharmacodyn (2012) 39:499–518
This is possible to implement in NONMEM as per the 7.4 userguide NPDE section
for the code.
BW,
Joe
Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Honorary Senior Lecturer, St George's University of London
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
________________________________________
From: [email protected] [[email protected]] on behalf of
Smit, Cornelis (Klinische Farmacie) [[email protected]]
Sent: 22 February 2019 10:11
To: [email protected]
Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Hi Andrew,
When your observation is <BLQ, M3 gives you a likelihood of this value being <
BLQ in the PRED column. So this value will be close to 1 when the model is
fairly sure that the concentration should be BLQ. This might explain why the
PREDs might be relatively high in your diagnostics here. I usually exlude the
<BLQ values in my GOF diagnostics, and check for model misspecification with a
VPC showing BLQ data (as described in
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/
). You can do this with the old xpose package. I don’t think there is any way
to visualize the BLQ prediction in the ‘usual’ GOF but I’m very curious if
someone else has some ideas regarding this.
Kind regards,
Cornelis Smit
Hospital Pharmacist / PhD candidate
Dept. of Clinical Pharmacy
St. Antonius Hospital
Dept. of Pharmacology,
Leiden Academic Centre for Drug Research,
Leiden University, Leiden, The Netherlands
VRIJWARING: Dit e-mail bericht is uitsluitend bestemd voor de geadresseerde(n).
Verstrekking aan en gebruik door anderen
is niet toegestaan. Als u niet de geadresseerde bent, stel dan de verzender
hiervan op de hoogte en verwijder het bericht.
Aan de inhoud van dit bericht kunnen geen rechten worden ontleend.
Van: [email protected] [mailto:[email protected]] Namens
Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
Aan: [email protected]
Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange
PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both
have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time point).
IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether
PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist
********************************************************************************************************************
This message may contain confidential information. If you are not the intended
recipient please inform the
sender that you have received the message in error before deleting it.
Please do not disclose, copy or distribute information in this e-mail or take
any action in relation to its contents. To do so is strictly prohibited and may
be unlawful. Thank you for your co-operation.
NHSmail is the secure email and directory service available for all NHS staff
in England and Scotland. NHSmail is approved for exchanging patient data and
other sensitive information with NHSmail and other accredited email services.
For more information and to find out how you can switch,
https://portal.nhs.net/help/joiningnhsmail