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

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