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Modeling Initial Conditions in Monolix without using ODEs

PK/PD Programmer (ASA/ISOP)
#1

Good afternoon everyone,
I have PopPK data where the participants have plasma levels at time=0.

The three compartment model file is:

[LONGITUDINAL]
input = {Cl, V1, Q2, V2, Q3, V3}

EQUATION:
V = V1
k = Cl/V1
k12 = Q2/V1
k21 = Q2/V2
k13 = Q3/V1
k31 = Q3/V3

Cc = pkmodel(V, k, k12, k21, k13, k31)

OUTPUT:
output = Cc

However, the various entries I tried has not worked properly. What do you recommend?

Thanks,
Andy

#2

Dear Andy,

as this model is linear, if there is a non 0 value of Cc at time 0 you just have to add a Cc_init parameter and put another equation Cc_out = Cc+Cc_init

  • Cc_init can be a constant value
  • Cc_init can be an input and defined as a regressor
    Notice that Cc = pkmodel(V, k, k12, k21, k13, k31) +Cc_init will lead to an error as the pkmodel macro should be “alone” on its line.

Hope this helps

Jonathan

#3

Hi Jonathan,
I did what you stated, but the model would not compile.

[LONGITUDINAL]
input = {Cl, V1, Q2, V2, Q3, V3, Cc_init}
regressor = {IC} ; values at time zero

EQUATION:
V = V1
k = Cl/V1
k12 = Q2/V1
k21 = Q2/V2
k13 = Q3/V1
k31 = Q3/V3

Cc = pkmodel(V, k, k12, k21, k13, k31, Cc_init)
Cc_out = Cc + Cc_init

OUTPUT:
output = Cc_out

Any thoughts?

Andy

#4

I was more thinking at

LONGITUDINAL]
input = {Cl, V1, Q2, V2, Q3, V3, Cc_init}
Cc_init = {use=regressor} ; values at time zero

EQUATION:
V = V1
k = Cl/V1
k12 = Q2/V1
k21 = Q2/V2
k13 = Q3/V1
k31 = Q3/V3

Cc = pkmodel(V, k, k12, k21, k13, k31)
Cc_out = Cc + Cc_init

OUTPUT:
output = Cc_out

It should work with the 2016R1 (otherwise the syntax of the regressor part is a little bit different)

Jonathan

#5

Hi Jonathan,
Thanks for the modification…based on what you sent me for version 2016R1, here is the error message I get when I try to compile the model:

<img src="/upload

Description: Incomplete match, remaining unmatched input is:
Then it shows the model you typed….

Andy

#6

Dear Andy, I guess [LONGITUDINAL] is missing

I tired with a simpler case, with the theophylline example.
-> I change the data set and copy the ID column to create a new column IDcopy to create a regressor.
-> For the library model, I created oral1_1cpt_kaVCl_reg.txt as the following

[LONGITUDINAL]
input = {ka, V, Cl, Cc_init}
Cc_init = {use=regressor}

EQUATION:
Cc = pkmodel(ka, V, Cl)
Cc_out = Cc+Cc_init

OUTPUT:
output = Cc_out

When I clicked on “check initial fixed effects”, I can see that the initial condition is well take into account.

Best

#7

Hi Jonathan,
It’s a winner…that is fantastic…the model works well by estimating the initial conditions using the regressor function.

This was outstanding…thanks for your help Jonathan…

Andy

#8

Great

Enjoy MonolixSuite2016R1

Best

#9

Hi Everyone
I am getting a similar error, however rather than being a PK model, its a PD model
with the following structure,
[LONGITUDINAL]
input = {Cc,IC50, gamma, I, Kz,Kx,Ky,AN}
Cc = {use=regressor}
I = {use=regressor}

EQUATION:

if AN==1
Ki=Kz
Kz=0
elseif AN==2
Ki=Kx
elseif AN==3
Ki=Ky
end

E = 1 - Cc^gamma / (IC50*(1+(I^gamma/(Ki^gamma)) + Cc^gamma)
OUTPUT:
output = E

Depending on my categorical Covariate AN, I would like to calculate unique Ki values.

However the error i keep getting is as follows
“Incomplete match, remaining unmatched input is:
:
output = E”