Collaboration and calibration: modelling with experimental and clinical data
Monday, June 14 at 5:45pm (PDT)Tuesday, June 15 at 01:45am (BST)Tuesday, June 15 09:45am (KST)
Adriana Zanca (The University of Melbourne, Australia), Jennifer Flegg (The University of Melbourne, Australia), Helen Byrne (University of Oxford, UK)
An ongoing challenge in mathematical and computational modelling is model validation and uncertainty quantification. Model calibration in the absence of rich clinical and experimental data relies on synthetic data, in turn adding different problems to solve. Conversely, clinical and experimental data can be so voluminous that it can be difficult to manage, interpret and use the data. Even where data allows for model calibration, uncertainty is often not analysed or reported. Without validation and uncertainty analysis, mathematical and computational models may not be clinically or experimentally applicable nor relevant. To help overcome this, there needs to be continual collaboration between clinicians, experimentalists, and modellers. This mini-symposium presents work across different fields and scales to highlight the range of experimental and clinical data available and how they can be best used in conjunction with mathematical modelling. Topics covered in this mini-symposium include angiogenesis, colon cancer, tumor modelling, ischemic heart conditions, lung disease, placental vasculature, HIV reactivation, and drug response.