From: GREAT ORMOND STREET HOSPITAL FOR CHILDREN NHS
FOUNDATION TRUST <*joseph.standing *>

Date: Mon, 25 Feb 2019 09:31:49 +0000

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 non=

linear mixed

effect models in presence of data below the quantification limit with appli=

cations 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 secti=

on 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: owner-nmusers

of Smit, Cornelis (Klinische Farmacie) [c.smit1

Sent: 22 February 2019 10:11

To: nmusers

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 bein=

g < 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 wh=

y the PREDs might be relatively high in your diagnostics here. I usually ex=

lude the <BLQ values in my GOF diagnostics, and check for model misspecific=

ation 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 regar=

ding 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

ens Andrew Tse

Verzonden: vrijdag 22 februari 2019 10:23

Aan: nmusers

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 stran=

ge PRED values in mytab table if someone can shed some light:

I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) bo=

th have normal looking fitting with data in individual plots.

Once I have coded SAEM with M3 codes and include BQL data it showed very st=

range 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 whethe=

r PRED values for BQL means something else other than prediction for BQL da=

ta?

Thanks a lot.

Kind regards,

Andrew Tse

Research Pharmacist

***************************************************************************=

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Received on Mon Feb 25 2019 - 04:31:49 EST

Date: Mon, 25 Feb 2019 09:31:49 +0000

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 non=

linear mixed

effect models in presence of data below the quantification limit with appli=

cations 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 secti=

on 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: owner-nmusers

of Smit, Cornelis (Klinische Farmacie) [c.smit1

Sent: 22 February 2019 10:11

To: nmusers

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 bein=

g < 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 wh=

y the PREDs might be relatively high in your diagnostics here. I usually ex=

lude the <BLQ values in my GOF diagnostics, and check for model misspecific=

ation 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 regar=

ding 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

ens Andrew Tse

Verzonden: vrijdag 22 februari 2019 10:23

Aan: nmusers

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 stran=

ge PRED values in mytab table if someone can shed some light:

I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) bo=

th have normal looking fitting with data in individual plots.

Once I have coded SAEM with M3 codes and include BQL data it showed very st=

range 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 whethe=

r PRED values for BQL means something else other than prediction for BQL da=

ta?

Thanks a lot.

Kind regards,

Andrew Tse

Research Pharmacist

***************************************************************************=

*****************************************

This message may contain confidential information. If you are not the inten=

ded 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 ta=

ke 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 sta=

ff in England and Scotland. NHSmail is approved for exchanging patient data=

and other sensitive information with NHSmail and other accredited email se=

rvices.

For more information and to find out how you can switch, https://portal.nhs=

.net/help/joiningnhsmail

Received on Mon Feb 25 2019 - 04:31:49 EST