RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling

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.



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: [] on behalf=
 of Smit, Cornelis (Klinische Farmacie) []
Sent: 22 February 2019 10:11
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

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Van: [] Nam=
ens Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
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:




 K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant


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)



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

F_FLAG=1 ;BQL so Y is likelihood

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=

Thanks a lot.

Kind regards,
Andrew Tse

Research Pharmacist


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

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