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Paul Macklin, PhD
Associate Professor of Intelligent Systems Engineering
Member, IU Melvin and Bren Simon Cancer Center
Jayne Koskinas Ted Giovanis Foundation for Health and Policy Partnership
Seeking to understand the mechanisms driving cancer progression and metastasis.
A multidisciplinary approach is employed to create a model of tumor growth and invasion to identify druggable targets to prevent metastasis.
This innovative and collaborative effort will provide new modeling tools that will advance research in metastatic breast cancer.
Metastatic breast cancer – breast cancer that has spread to other tissues – is a treatable but incurable disease. New treatments are urgently needed to not only treat existing disease but prevent breast cancer from spreading in the first place. There is much to be learned about the process of metastasis in order to identify targets for treatment or prevention, and an interdisciplinary approach can accelerate the discovery process. Drs. Newton and Macklin, in collaboration with BCRF investigator Andrew Ewald, are combining mathematical and biological methods to create a computational model in which they can study the processes of metastasis.
Full Research Summary
In order for metastasis to occur, tumor cells must be able to leave an actively growing tumor, shut off growth processes while they travel to a distant organ and then switch those growth pathways back on at the new location.
In this project co-funded by BCRF and the Jayne Koskinas Ted Giovanis Foundation for Health Policy, Dr. Newton and colleagues will apply methods of cellular biology, chemical engineering, and mathematical and computational modeling to elucidate the molecular drivers of these transitions in a systematic fashion.
They will create a model system of tumor growth and invasion based on analyses of tumor growth, tumor cell behavior and results from microenvironmental and genetic experiments. This 3D model can then be used to test the effects of selected stimuli on tumor cell behavior that will elucidate points in the metastatic process where interventions are possible.
These studies will accelerate discovery of potential targets to prevent metastasis.
Dr. Paul Macklin is an applied mathematician in the newly-established Department of Intelligent Systems Engineering at Indiana University. Dr. Macklin works with teams of clinicians, modelers, and biologists to develop and validate sophisticated computer models of cancer. These models simulate the dynamics of millions of cells in realistic 3-D tissues, using powerful open source software developed by his lab. Dr. Macklin has pioneered methods to adapt computer models to individual cancer patients and predict response to treatment choices. He founded and co-leads the MultiCellDS project to create a “data language” that will help cancer scientists to share and combine experimental, clinical, and simulation data. His work is creating an open library of digital cell lines: a novel data model of experimental cell line measurements for use in cancer simulators. Dr. Macklin’s overarching goal is to create computational tools that accelerate biological research and assist clinicians and their patients in making treatment decisions.