Mimicking cancer therapy in an agent-based model: the case of hepatoblastoma
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Hepatoblastoma is the most common pediatric liver cancer and represents a serious clinical challenge as no effective therapies have yet been found for advanced states and relapses of the disease. In this work, we use a well-established agent-based model of the immune response now equipped with anti-cancer therapy response to study the evolution of the disease and the role of the immune system in its containment, in particular by simulating the course of hepatoblastoma over three years in a population of virtual patients with mortality and symptom onset rates mimicking clinical ones. These results, combined with the ability to observe the dynamics of cellular entities at the microscopic scale and the key chemical signals involved in disease progression, make the model a valuable resource for future research on in silico trials.
