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RE: [External] Re: Error in Power-model for covariate selection

From: Singla, Sumeet K <sumeet-singla>
Date: Thu, 21 Nov 2019 17:46:46 +0000

I figured out the problem. Apparently, SCM in PsN, by default sets a very large lower and upper limits for thetas of covariate-parameter relationship, if you don’t provide those bounds. NONMEM runs into numerical difficulty when raising a very small or very big quantity to a power of say 10000.There is a way around it. Set this in your configuration file as shown below:

[lower_bounds]
V2:USER-5 = -5

[inits]
V2:USER-5= 0.1

[upper_bounds]

V2:USER-5 = 5

You can define as many “parameter:covariate-model” as you want, in the above format. Note that, order should be: lower_bound, inits, upper bound, and if you are defining more than one parameter-covariate relation, they should be in same order in lower_bound, inits and upper_bounds section.

Regards,
Sumeet

From: Ayyappa Chaturvedula <ayyappach
Sent: Wednesday, November 20, 2019 8:27 AM
To: Singla, Sumeet K <sumeet-singla umeet-singla
Cc: nmusers to:nmusers
Subject: [External] Re: [NMusers] Error in Power-model for covariate selection

Hi Sumeet:
Couple of points, may not be solutions for the modeling problem you are having but in general:
1. Use INTERACTION in your $EST because you are using proportional error
2. Make sure you have enough range of covariates in the data to describe the relationships quantitatively
3. Are there any correlated covariates that you are trying to include same time?
4. Try fitting the model out of SCM for power function and try to find the issue.

Regards,
Ayyappa

On Nov 19, 2019, at 10:48 PM, Singla, Sumeet K <sumeet-singla

Hello Everyone,

I am using PsN enabled SCM option in Pirana to analyze selection of covariates in the PK 2- Comp model. As long as I am using just linear and exponential covariate model, everything runs fine. However, as soon as I add power-model in the mix, “some” power models involving continuous covariates on parameters fail to run and it gives me the following error:
“HESSIAN OF POSTERIOR DENSITY IS NON-POSITIVE-DEFINITE DURING SEARCH”
I understand that individual PK parameter search might be moving into 0 or negative territory. I am trying to fix it but didn’t have much success. I have set lower bounds, removed lower bounds, changed order of model in valid states option in scm configuration file, dataset doesn’t contain any 0 or negative value, but nothing is working. FYI: I don’t need to test hockey-stick relation as literature and data doesn’t support it, power model can only be used on continuous covariates and I have turned on parallel states option.
This is how part of my scm results, followed by scm configuration file, followed by base model for PK 2-Comp looks like:

MODEL TEST BASE OFV NEW OFV TEST OFV (DROP) GOAL dDF SIGNIFICANT PVAL
CLAGE-2 PVAL 2618.02603 2616.67228 1.35375 > 3.84150 1 0.244620
CLAGE-5 PVAL 2618.02603 2616.36273 1.66330 > 3.84150 1 0.197160
CLAGE-4 PVAL 2618.02603 2616.65232 1.37371 > 3.84150 1 0.241180
CLBMI-2 PVAL 2618.02603 2612.96657 5.05946 > 3.84150 1 YES! 0.024492
CLBMI-5 PVAL 2618.02603 FAILED FAILED > 3.84150 1 999

SCM FILE:

search_direction=both
p_forward=0.05
p_backward=0.01
continuous_covariates=BMI,AGE
categorical_covariates=USER,SEX
parallel_states=1
retries=2
threads=6
tweak_inits=1
;;1-NotIncluded, 2-LINEAR, 3-Hockey Stick Relation, 4-Exponential, 5-Power
[test_relations]
CL=AGE,SEX,BMI,USER
V1=AGE,SEX,BMI,USER
V2=AGE,SEX,BMI,USER
Q=AGE,SEX,BMI,USER
[valid_states]
continuous = 1,2,5,4
categorical = 1,2

NONMEM Control Stream:

$SUBROUTINE ADVAN3 TRANS4

$PK

TVV1 = THETA(1) ;Central Volume of distribution in L
V1 = TVV1*EXP(ETA(1))
TVCL = THETA(2)
CL = TVCL*EXP(ETA(2)) ; Clearance L/h
TVQ = THETA(3)
Q = TVQ*EXP(ETA(3)) ;Intercompartment Clearance
TVV2 = THETA(4)
V2 = TVV2*EXP(ETA(4)) ;Peripheral volume in L
S1=V1

$ERROR
IPRED=F
Y= F + F*ERR(1); Proportional Error

$THETA
(0, 16); [V1] based on PK 2 Comp
(0, 255); [CL] based on PK 2 Comp
(0, 33.5); [Q] based on PK 2 Comp
(0, 29.7); [V2] based on PK 2 Comp

$OMEGA
(0, 0.08); [P] omega(1,1)
(0, 0.159); [P] omega(2,2)
(0, 0.140); [P] omega(3,3)
(0, 0.19); [P] omega(4,4)

$SIGMA
(0, 0.06) ;sigma1

$EST METHOD=1 PRINT=5 MAXEVAL=9999 SIG=3 NOABORT


Regards,

Sumeet K. Singla
Ph.D. Candidate
Division of Pharmaceutics and Translational Therapeutics
College of Pharmacy | University of Iowa
Iowa City, Iowa
sumeet-singla owa.edu<mailto:sumeet-singla
518.577.5881

Received on Thu Nov 21 2019 - 12:46:46 EST

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