# Core 1: Mathematical Core

> **NIH NIH U54** · H. LEE MOFFITT CANCER CTR & RES INST · 2024 · $311,332

## Abstract

Summary – Mathematical Modeling Core
Understanding the changes in tumor ecology (“∆-Ecology”) that occur during tumor initiation, progression, and
therapy requires careful study of a complex dynamical system involving multiple scales – from molecular to
cellular to tissue to systemic. An important tool in this study is the use of mathematical models, which can
bridge temporal gaps in clinical and experimental data. Ecological histology data from patients is difficult and
rare to obtain, and experimental work, while crucial for teasing apart mechanism and testing hypotheses,
cannot fully reproduce the human setting of disease. Mathematical modeling serves as a link between these
approaches, allowing ecological principles arising from mechanisms studied in vitro and in vivo to play out in
the patient setting, calibrated to available patient data. The Mathematical Modeling Core will develop these
models, using a variety of approaches. Key is the use of spatial agent-based models, which can handle the
rich diversity of cell types and molecules, as well as the multiple scales involved in tumor ecology and
evolution. We have built a platform for developing these models that is fast and flexible, including numerous
add-ons that will serve the science in the two projects of this proposal. In addition, our expertise in non-spatial
models will be applied in parallel, as these approaches can capture the broad dynamics of tumor growth and
the response to treatment in ways that have significant translatable potential, as evidenced by ongoing trials in
Evolutionary Therapy at Moffitt. In addition to constructing these models, we will develop tools for initializing,
calibrating, and analyzing models based on clinical and pre-clinical data collected in each project. This will
involve the use of virtual “Phase i” trials, where virtual patients/mice are generated from a model, taking
parameter uncertainty into account. In summary, the Core models will provide insight into the ecological
processes that occur during tumor growth and treatment.

## Key facts

- **NIH application ID:** 10930176
- **Project number:** 5U54CA274507-02
- **Recipient organization:** H. LEE MOFFITT CANCER CTR & RES INST
- **Principal Investigator:** Alexander Robertson Allan Anderson
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $311,332
- **Award type:** 5
- **Project period:** 2023-09-15 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10930176

## Citation

> US National Institutes of Health, RePORTER application 10930176, Core 1: Mathematical Core (5U54CA274507-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10930176. Licensed CC0.

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