Adding an Error Model to a Nonlinear Mixed Effects Model

Hello all,
First, I used SimBiology Model Builder to restore the PPK model that had been established in NONMEM. Since SimBiology Model Builder cannot add parameters for inter-individual variation and error models, I added them using code. But I found that the exponential error model has not been added to the model.
I would like to ask how to add the exponential error model to the following code and how to optimize the simulation process code? Thank you for your help!
opts = spreadsheetImportOptions("NumVariables", 3);
opts.Sheet = "Sheet1";
opts.DataRange = "A2:C237";
opts.VariableNames = ["ID", "TIME", "DV"];
opts.VariableTypes = ["double", "double", "double"];
Dose = readtable("Dose.xls", opts, "UseExcel", false)
data = groupedData(Dose);
sbiotrellis(data,@semilogy,"ID","TIME","DV",Marker="+",LineStyle="--");%%@semilogy
% Extract the model overall model file
s = sbioloadproject("Version-2-20241218.sbproj");
model = s.m1;
covModel = CovariateModel;
covModel.Expression = {'V1 = exp(theta1 + eta1)',' V2 = exp(theta2 + eta2)','F1 = exp(theta3 + eta3)','CL = exp(theta4 + eta4)'};
covModel.FixedEffectNames
covModel.FixedEffectDescription
options.ErrorModel = 'exponential';
options.ErrorModelParameters = struct('sigma', 1.0928)
thetas = table(4.0056,-20.3634,-7.9054,7.0873,'VariableNames',["theta1","theta2","theta3","theta4"])
omega = table([2.4432;0;0;0],[0;0.0534;0;0],[0;0;9.4391;0],[0;0;0;0.0729],'VariableNames',["eta1","eta2","eta3","eta4"])
phi = sbiosampleparameters(covModel.Expression,thetas,omega,Dose)
f = createSimFunction(model,covModel.ParameterNames,'Drug_Central',[])
simresults = f(phi,24)
t = sbiotrellis(simresults,[],'Time',' Drug_Central');
t.hFig.Position(3:4) = [800 500];
set(t.plots,'XGrid','on','YGrid','on');
set(t.plots,'YScale','log');
lh = findobj(t.plots,'Type','line');
set(lh,'LineWidth',2);

 Respuesta aceptada

Jeremy Huard
Jeremy Huard el 20 de Mzo. de 2025
Assuming you want to add noise to the simulation data based on the exponential error model, you could use sbiosampleerror:
noisysimresults = sbiosampleerror(simresults, 'exponential', 1.0928);

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R2022b

Preguntada:

el 20 de Mzo. de 2025

Comentada:

el 20 de Mzo. de 2025

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