Is it possible to combine pooled and unpooled parameter fitting in SimBiology 4.3 (R2013a)?

I have a dataset that combines data from multiple studies, where each study was conducted with a different drug agent. I want to simultaneously fit the entire dataset to a single SimBiology model, such that(a) A subset of the estimated parameters are commonly estimated for all the drug groups (pooled fitting).(b) The remaining parameters are estimated in a drug-dependent manner, i.e. one set of estimated values per drug-group (unpooled fitting).

Answer 1

[MathWorks Support Team]

In order to combine pooled and unpooled parameter fitting please follow the steps below:

1. Load your .sbproj file

2. Load your data

3. If you have several measurement repeats for each drug (e.g. several persons) create a vector specifying to which group a person belongs 

4. Create a vector with initial values for the parameters. For each unpooled parameter the number of entries in the vector must be the same as the number of groups. E.g. if you have 2 drugs, 3 pooled and 1 unpooled parameter the number of entries in the vector will be 3+2*1 = 5;

5. Create your regression function

5.1. For each repeat select the correct parameters out of the parameter list using your vector containing the information to which group a measurement repeat belongs to

5.2. Call SIMULATE to simulate the model for this parameter set

5.3. Create a matrix out of all simulation results

6. Perform your fitting, e.g. using NonLinearModel.fit

Please find an example attached.

[Ingrid Tigges]

As far as I am aware this cannot be done in the SimBiology desktop. If you would like to see this functionality in the SimBiology desktop, please contact technical support. Technical support has a defined procedure to forward enhancement requests to development.

[Arthur Goldsipe]

I just realized that a feature introduced in R2014b helps with this sort of work. I'll post a separate answer below.

Answer 2

[Arthur Goldsipe]

As of R2014b, the SimBiology command-line offers the capability to simultaneously estimate "pooled" and "unpooled" parameters (that is, some parameters that are identical for all groups/patients and other parameters that have group-specific values). The following example shows how to estimate two parameters that are age-specific and two parameters that are sex-specific:

https://www.mathworks.com/help/simbio/ref/estimatedinfo.html?s_tid=srchtitle#bukuiue

I don't know if this particular example mentions it, but if a parameter has the same value for all individuals, then you can set CategoryVariableName to '<None>' to indicate this. You can also specify that a parameter value is specific to each individual by setting CategoryVariableName to 'ID' or '<GroupVariableName>' (where 'ID' is the name of the variable in the data that identifies the individuals).