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Robyn Shuttleworth PhD.

My name is Robyn and I use mathematical models to describe and predict behaviours in biological systems.

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Nice to meet you.

Hey, I'm Robyn, a mathematical biologist.

Robyn Shuttleworth (pronouns: she/her) is a Computational Biologist in the Bianco Group at Altos Labs. She received her PhD in Applied Mathematics from the University of Dundee in July 2019 with Dr. Dumitru Trucu and her BSc in Mathematics from the University of Dundee in 2015.

Her research is in applied mathematics and mathematical biology. She uses multiscale models to describe emergent behaviours in different biological systems, ranging from cancer cell dynamics to the optimization of cryopreservation protocols.

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Robyn Shuttleworth

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Optimization of cryopreservation protocols

Cryopreservation is the process of cooling and storing biological samples at very low temperatures. One of the biggest challenges we face is the successful cryopreservation of whole organs; a practise that would allow for prolonged storage and safer transportation. We face several challenges when attempting to cryopreserve organs, such as osmotic damage, solution toxicity and ice formation. We created a moving boundary tissue model to describe the loading of cryoprotective agents (CPAs) to aid in the optimized design of experimental protocols.

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Multiscale modeling of tumour morphology

Local cancer cell invasion is a complex multiscale process that combines the secretion of matrix-degrading enzymes (MDEs) with a series of altered key cell processes, to degrade important components of the surrounding extracellular matrix (ECM) and this way spread further in the healthy tissue. We constructed a model to describe the interactions between cancer cells and the surrounding ECM, incorporating the underlying fibre network and cell adhesion dynamics. We explored the impact on cancer invasion patterns of different levels of cell adhesion in conjunction with continuous ECM fibres rearrangement.

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Agent-based modeling of zebrafish skin patterns

Zebrafish feature black and yellow stripes, while mutants display different patterns. These patterns arise from self-organizing interactions of pigment cells. Using a prior agent-based model, we delved deeper into the mechanisms of these interactions by adapting the model to account for stochastic communication between cells. The aim is to develop a more realistic model of cellular interactions by incorporating cellular protrusions and diffusing signals from individual cells.

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Microenvironment model development

The extracellular environment is a key contributor to many biological systems; however, it is a highly complex structure and can be difficult to describe within a mathematical model. Using the computational package PhysiCell, we aim to develop an add-on, PhysiMeSS, that will enable the user to incorporate specific components of the ECM, along with all of their associated dynamics, to their model.


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Comparison of dilute and nondilute osmotic equilibrium models for erythrocytes

Shuttleworth et al., Cryobiology (2022), DOI: 10.1016/j.cryobiol.2022.09.001

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Cell-Scale Degradation of Peritumoural Extracellular Matrix Fibre Network and Its Role Within Tissue-Scale Cancer Invasion

Shuttleworth. R., and Trucu, D., Bulletin of Mathematical Biology (2020), DOI: 10.1007/s11538-020-00732-z

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Multiscale dynamics of a heterotypic cancer cell population within a fibrous extracellular matrix

Shuttleworth. R., and Trucu, D., Journal of Theoretical Biology (2020), DOI: 10.1016/j.jtbi.2019.110040

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Multiscale modelling of fibres dynamics and cell adhesion within moving boundary cancer invasion

Shuttleworth. R., and Trucu, D., Bulletin of Mathematical Biology (2019), DOI: 10.1007/s11538-019-00598-w

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Two-Scale Moving Boundary Dynamics of Cancer Invasion: Heterotypic Cell Populations’ Evolution in Heterogeneous ECM

Shuttleworth. R., and Trucu, D., Cell Movement: Modeling and Applications, Springer (eds. N. E. Tarfulea and M. Stolarska) (2018), DOI: 10.1007/978-3-319-96842-1



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Mathematical Modelling in Biology

This course explored and developed a number of mathematical modelling tools in the context of biology, allowed the development of mathematical intuition into biological problems, and introduced programming in Python and Jupyter Notebook to enable analysis.

University of Saskatchewan
Winter 2021
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