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

From: Smit, Cornelis (Klinische Farmacie) <"Smit,>
Date: Fri, 22 Feb 2019 10:11:37 +0000

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: 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

Received on Fri Feb 22 2019 - 05:11:37 EST

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