The rapid expansion of immunotherapies in Oncology has increased the need for quantitative models that can understand their mechanisms and limitations. T cell engagers (TCEs) are an emerging therapeutic class that bind both T cell receptors and tumour associated antigens to promote immunological synapse formation and targeted cytotoxicity. Despite growing clinical success, their efficacy is...
Glioblastoma is the most common and deadliest primary brain tumour in adults, with a median survival of 15 months under the current standard of care \cite{Trager2020}. Its tumour microenvironment has been shown to be highly heterogeneous \cite{Karimi2023}, meaning the magnitude of cell-cell interactions might differ due to spatial differences. While ordinary differential equation models can be...
Resistance to the anti-mitotic drug docetaxel is a major challenge in the treatment of solid tumors, including prostate and pancreatic cancers. The stress-response protein NUPR1 has been identified as a key molecular driver of docetaxel resistance, suggesting that inhibition of NUPR1 may restore treatment sensitivity and enable effective combination therapy. In this talk, I develop...
The challenge of stratifying patients for combination therapy is both technically demanding and clinically crucial. We build upon our previous framework for identifying Pareto optimal doses, reconciling competing definitions of synergy through multi-objective optimization to balance synergy of efficacy and potency (a measure of toxicity) such that no further improvement is possible in one...
Virtual clinical trials (VCTs) hold significant promise for improving the drug development process, yet their predictive reliability depends on design decisions that remain poorly understood. This presentation investigates how model complexity, prior parameter distributions, and virtual patient (VP) inclusion criteria interact to shape VCT outcomes.
Using oncolytic virotherapy in murine...
Sometimes! Gleaning insight from a model independent of data is (understandably) rarer and rarer in mathematical biology, and determining parameters from biological data has become an established practice of modern mathematical modelling. Once parameters are estimated (ideally with bounds), an important question remains: whether (and to what extent) are biological parameters conserved? For...
Metastasis to the liver remains a leading cause of mortality in colorectal cancer patients, due largely to the difficulty of treating established metastatic lesions. Spatial transcriptomic (ST) imaging provides highly detailed, spatially resolved data on the cellular composition and interactions within these lesions, offering new insights into how metastases are established and evolve in the...
Chimeric Antigen Receptor (CAR) T-cell therapy has emerged as a promising option for relapsed or refractory lymphoma patients and acute leukemias. Mathematical modeling offers a valuable tool for investigating the interactions among these living drugs, tumors, and heterogeneous patients' immune or inflammatory context. Using longitudinal data from experiments and the clinic, we examine how...
This minisymposium brings together speakers that will highlight advances in the modelling, simulation, and analysis of various treatments for cancer. Novel approaches are required for new drug developments, including bi-specific molecules, nanoparticles immunotherapies, drug combinations and synergies, adaptive therapy, virtual clinical trials, and so on. Speakers in this session will discuss...
