Abstract
This paper presents the CellCycler, a model of a growing tumour which aims to simulate and predict the effect of treatment on xenograft studies or in the clinic. The model, which is freely available as a web application, uses ordinary differential equations (ODEs) to simulate cells as they pass through the phases of the cell cycle. However the guiding philosophy of the model is that it should only use parameters that can be observed or reasonably well approximated. There is no representation of the complex internal dynamics of each cell; instead the level of analysis is limited to cell state observables such as cell phase, apoptosis, and damage. We show that this approach, while limited in many respects, still naturally accounts for a heteregenous cell population with varying doubling time, and closely captures the dynamics of a growing tumour as it is exposed to treatment. The program is demonstrated using three case studies.
| Original language | English |
|---|---|
| Journal | PeerJ |
| DOIs | |
| Publication status | Published - 31 May 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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