Collaboration and calibration: modelling with experimental and clinical data

Monday, June 14 at 7:45pm (PDT)
Tuesday, June 15 at 03:45am (BST)
Tuesday, June 15 11:45am (KST)

SMB2021 SMB2021 Follow Monday (Tuesday) during the "MS04" time block.
Note: this minisymposia has multiple sessions. The second session is MS03-IMMU (click here).

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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.

Wafaa Mansoor

(Murdoch University, Australia)
"Modelling hydrogen clearance in the retina"
Two simple mathematical models of advection and diffusion of hydrogen within the retina are discussed to assist in interpretation of the ’hydrogen clearance technique’ that is used to estimate blood flow. The first model assumes the retina consists of three, well-mixed layers with different thickness, two-dimensional model consisting of three regions that represent the layers in the retina. Diffusion between the layers and leakage through the outer edges are considered. Solutions to the governing equations are obtained by employing Fourier series and finite difference methods for the two models, respectively. The effect of important parameters on the hydrogen concentration is examined and discussed. The results contribute to understanding the dispersal of hydrogen in the retina and in particular the effect of flow in the vascular retina. It is shown that the predominant features of the process are captured by the simpler model.

Vijayalakshmi Srinivasan

(Auckland Bioengineering Institute, New Zealand)
"3D analysis of Human placental cotyledon: a step ahead to understand feto-placental vasculature"
The human placenta has extensive branching villus structure, which contains a branching network of fetal blood vessels that are essential for efficient exchange of nutrients from mother to fetus. Reduced vascular density and branching have been linked to functional placental impairments, such as fetal growth restriction (FGR) where the baby’s growth rate becomes dangerously reduced. Currently, we lack clear understanding of origins of FGR for early diagnosis and treatment. Computational models that mimic the structure and function of the feto-placental vasculature have proved useful in predicting the consequences of perturbations to these structures in FGR. However, they have been limited in their anatomical fidelity at the meso-scale (the primary site of resistance), due to challenges in imaging the placenta. Here, we present our approach to simulating feto-placental vascular function in the placenta as a whole, which aims to accurately incorporate structural detail regarding branching properties of the complex vascular tree. We then present new data regarding the complexity of the feto-placental vasculature at the cotyledon (functional unit) scale, and show how mathematical models representing the cotyledon as a branching network of vessels can be used to interrogate function across spatial scales relevant to the key sites of feto-placental vascular resistance.

Yuhuang Wu

(Kirby Institute, Australia)
"Predicting the composition of the HIV / SIV Reservoir and Rebounding Virus"
Human Immunodeficiency Virus (HIV) attacks human immune cells and new free virus is produced via infected cells. Even with a successful treatment of HIV, the population of infected cells does not go extinct. Instead, a number of infected cells stay in an inactive state and once treatment is stopped, reactivation of infected cells may produce virus again. To date, it is still unclear when and how these inactive infected cells (reservoir) are formed. In this work, we try to distinguish whether different virus produced throughout the course of infection contributes equally to the formation of reservoir, or virus strains produced over a certain time period are more important to reservoir formation. Furthermore, we explore how the composition of replicating virus relates to the composition of the reservoir. Additionally, we look at if the reservoir composition determines the production of virus when the treatment is stopped. In this talk, we use both mathematical modelling and statistical analysis, applied to experimental data from an animal study, to show the relationship between the early viral dynamics and the reservoir composition as well as the recrudescent virus. We find dominant viral strains present prior to treatment are more likely to reactivate after cessation of treatment.

Claire Miller

(University of Amsterdam, Netherlands)
"In silico clinical trials for acute ischemic stroke"
The concept of in silico trials is gaining increasing attention in medical research. The end goal of these trials is to refine, reduce the cost of, and partially replace in vivo animal studies and human clinical trials. In our project, INSIST, we are developing in silico trials for acute ischemic stroke (AIS): the occlusion of an artery in the brain. The current standard of care for AIS is thrombolysis (drug) and/or thrombectomy (surgical) intervention. Modelling AIS requires the modelling of the stroke onset, treatment, and resulting injury. This is done by linking models for blood flow through the arteries, blood perfusion in the brain, the two treatment approaches, and tissue injury. It is also necessary to be able to produce large numbers of patients to run these models on; provide trial outcomes that are clinically relevant; and a trial framework that can be practically compared to current traditional clinical trials. In this talk I will discuss the setup of the INSIST in silico trials, how we connect the different models to predict treatment and patient outcome, and the methods we have used to generate populations of virtual patients using clinical data. Additionally I will discuss how the approaches used facilitate the translation of the trial outcomes to a clinical setting.

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Virtual conference of the Society for Mathematical Biology, 2021.