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Browse the article contributions of Kit Gallagher below or browse the full blog here.

Learning to Adapt - Personalizing Adaptive Therapy Schedules using Deep Reinforcement Learning

Behind the paper

Written by Kit Gallagher on August 16, 2024

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Recordings from the MathOnco25 conference:

Predicting Treatment Outcomes from Adaptive Therapy - A New Mathematical Biomarker

"Standard-of-care cancer therapy regimens are characterized by continuous treatment at the maximum tolerated dose; however, this approach often fails for..."

Presented by Kit Gallagher, at MathOnco25 on October 30, 2025

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Artworks by Kit Gallagher :

Each week, we feature cover artwork submitted by mathematical oncology researchers around the world. Browse the contributions of Kit Gallagher below. Click to expand each cover, or browse the full collection here.

Issue 356

"The widespread use of cytotoxic drugs has shaped the paradigm of uniformly administering a ‘maximum tolerated dose’ to patients; however,..."

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Issue 346

"High-grade serous ovarian cancer (HGSOC) remains a challenging disease to treat due to high recurrence rates, acquired resistance, and cumulative..."

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Issue 329

"The motif of two Kaplan-Meier curves is familiar to many from clinical trial reporting - here the negative space between..."

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Issue 328

"When implementing Adaptive Therapy (AT) treatment schedules clinically, patients are monitored (and treatment schedules updated) at discrete time intervals. This..."

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Issue 303

"PARP inhibitors have transformed ovarian cancer care, but many patients require dose adjustments or drug holidays due to toxicity. We..."

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Issue 298

"Adaptive Therapy has been developed as an alternative treatment scheduling paradigm, aiming to control rather than try to cure late-stage..."

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