From: Jakob Ribbing <*jakob.ribbing*>

Date: Thu, 21 Nov 2019 22:32:40 +0100

Great to hear it is now working.

If you want to set the same limits for all power models, you can even =

write this in a more generic form:

*:*-5 = -5

And if you want to apply only for one parameter or one covariate that is =

possible as well, e.g.:

V2:*-5 = -5

Best regards

Jakob

*> On 21 Nov 2019, at 18:46, Singla, Sumeet K <sumeet-singla *

wrote:

*>
*

*> 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 *

<mailto:ayyappach

*> Sent: Wednesday, November 20, 2019 8:27 AM
*

*> To: Singla, Sumeet K <sumeet-singla *

<mailto:sumeet-singla

*> Cc: 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 *

*> 518.577.5881
*

Received on Thu Nov 21 2019 - 16:32:40 EST

Date: Thu, 21 Nov 2019 22:32:40 +0100

Great to hear it is now working.

If you want to set the same limits for all power models, you can even =

write this in a more generic form:

*:*-5 = -5

And if you want to apply only for one parameter or one covariate that is =

possible as well, e.g.:

V2:*-5 = -5

Best regards

Jakob

wrote:

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:

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.

<mailto:ayyappach

<mailto:sumeet-singla

selection

are having but in general:

error

describe the relationships quantitatively

same time?

the issue.

<sumeet-singla

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:

SEARCH”

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.

file, followed by base model for PK 2-Comp looks like:

GOAL dDF SIGNIFICANT PVAL

5-Power

distribution in L

Received on Thu Nov 21 2019 - 16:32:40 EST