Equilibrate during parameter estimation

I have a reaction network model built using simbiology. This includes reactions for synthesis and degradation of various species. So, generally I run steadystate and update the model state before running any simulations. Now, I would like to estimate some of the parameters in the model using sbiofit. My questions is whether sbiofit equilibrates model state for each parameter sample during fitting?

Thanks and regards.

Answer 1

[Jeremy Huard]

Hi @Anu,

running sbiosteadystate before each simulation in a fit is not supported.

That said, I see two options:

1. If your case is simple enough, you might be able to express the species concentrations at time=0 as a function of parameters: e.g. receptor = ksyn/kdeg. I understand it might not be feasible though.
2. You could shift the times in your data to fit by an offset large enough to reach steady state before the first dose is applied. To shift the time vector, you can add a derived column to the dataset in Model Analyzer and define it as the independent variable. For example:

Best regards,

Jérémy

[Anu]

Thanks Jérémy for your suggestions!

In the past, I did exactly the same as what you suggested, i.e. shifting the time points. It usually works. Do you think whether a flag for equilibartion could be included for sbiofit and sbiofitmixed in the future release of simbiology?

[Jeremy Huard]

Thank you, @Anu!

It does make a lot of sense. I will relay this request to our development team.

[Jeremy Huard]

@Anu, I was assuming that the steady state would depend on the parameters you try to estimate. Can you please confirm?

If not, the solution would be simpler. Namely, you could run a steady state program, save the result in a variant, and then apply this variant in your fit program.

It would help if you could clarify that point.

Thanks!

[Anu]

@Jeremy: Yes, the steadystate depends on the parameters that I am trying to estimate.

Thanks!