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model description: the models aim to describe the dynamics of oncolytic virus therapy (OVT) in zebrafish, focusing on tumor-virus interactions. These models range from a baseline logistic growth model to an advanced age-of-infection model that incorporates delays in viral effects and individual variability.
data description: the models use experimental data from a zebrafish study (Mealiea et al. (2021)), where tumor volumes were measured after injecting tumor cells and oncolytic viruses. The dataset includes daily tumor volume measurements for control and treated groups over five days.
fitting and uncertainty analysis: fides was used and with the following hyperparameters
np.random.seed(500)
n_start = 5000
max_iter = 5000
hierarchical=False
the optimization converges and most parameters are identifiable
we fitted all parameters with bounds based on various publications
Yuhong's publication on oncolyte virus therapy in zebrafish has a model in PEtab format, at the moment in the preprint phase.
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