Kit Gallagher
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kitcgallagher.bsky.social
Kit Gallagher
@kitcgallagher.bsky.social
83 followers 100 following 4 posts
PhD student; Oxford University & Moffitt Cancer Center; Mathematical Oncology (treatment scheduling and evolutionary models) and Epidemiology (inference and agent-based modeling).
Lecturer in Applied Maths at St Hilda's College, Oxford.
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kitcgallagher.bsky.social
As featured in the #mathonco newsletter, this inspired an artwork exploring the trade-off between appointment frequency and time to progression (background color). The optimal strategy line separates stable and chaotic outcomes, and we tile this pattern with the highest TTP at each tile's center
When implementing Adaptive Therapy (AT) treatment schedules clinically, patients are monitored (and treatment schedules updated) at discrete time intervals. This leads to a trade-off; more frequent clinical appointments allow greater control of the tumor at a higher average size (leading to longer time to progression, or TTP), but are more costly and logistically challenging to implement. We can derive the optimal threshold size for treatment to be used in an AT protocol, and plot this in white over different time intervals between appointments. This is superimposed over the TTP for all different treatment protocols (given by the coloured background) - super-critical protocols on one side of the optimal line leads to chaotic outcomes while sub-optimal protocols achieve a lower TTP. This pattern is tiled and inverted to create a 'chess board', with the highest TTP at the center of each tile, reflecting the optimal game that clinicians are trying to play against the cancer tumor.
April 10, 2025 at 3:46 PM