Computational Cancer Research at Carnegie Mellon University
Cancer is a leading cause of mortality worldwide, directly or indirectly touching the lives of most people. In 2020 there will be an estimated 1.8 million new cases of cancer in the United States and an estimated 600,000 deaths caused by cancer (NCI, 2020).
Modern cancer research and treatment are increasingly dependent on technological advances to address the challenges of gathering and making sense of increasingly complex data needed to understand tumor biology. Carnegie Mellon has been a pioneer in laying the groundwork for the future of cancer research, treatment and surveillance. Our faculty bring together multidisciplinary expertise in areas, including artificial intelligence, biological sciences, biomedical engineering, computational biology, machine learning and statistics and data science to develop tools and make discoveries at the forefront of cancer research.
. . . the development of the computational theory and algorithms that will analyze the explosion of data from genomic, multi-omic and single-cell studies of cancer tumor evolution and heterogeneity, and creating sophisticated models to translate these data into understanding how tumors evolve and adapt.
. . . state-of-the-art bioengineering technologies, including model-based automated experimentation, high-throughput imaging and next-generation in vitro experimental models, that take advantage of data-driven cancer research.
. . . the foundational science work that will lead to the future’s therapies. This includes developing gene editing technologies to fight cancer cells and exploring the physics within the cells that influence cancer growth and propagation.