The 18th Annual Koch Institute Summer Symposium on June 14, 2019 at MIT's Kresge Auditorium will focus on Machine Learning and Cancer.
Both fields are undergoing dramatic changes, and their integration holds great promise for cancer research, diagnostics, and therapeutics. Cancer treatment and research have advanced rapidly with an increasing reliance on data-driven decisions. The volume, complexity, and diversity of research and clinical data—from genomics and single-cell molecular and image-based profiles to histopathology, clinical imaging, and medical records—far surpasses the capacity of individual scientists and physicians. However, they offer a remarkable opportunity to new approaches for data science and machine learning to provide holistic and intelligible interpretations to trained experts and patients alike. These advances will make it possible to provide far better diagnostics, discover possible chemical pathways for de novo synthesis of therapeutic compounds, predict accurately the risk of individuals for development of specific cancers years before metastatic spread, and determine the combination of agents that will stimulate immune rejection of a tumor or selectively induce the death of all cells in a tumor.
Tyler Jacks, PhD
Koch Institute for Integrative Cancer Research at MIT
Phillip Sharp, PhD
Koch Institute for Integrative Cancer Research at MIT
Moderator: Phillip Sharp, PhD
Koch Institute for Integrative Cancer Research at MIT
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Immune checkpoint blockade in cancer therapy: Historical perspective, new opportunities, and prospects for cures James P. Allison, PhD |
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Cell atlases as roadmaps to cancer Aviv Regev, PhD |
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How machine learning changes cancer research Regina Barzilay, PhD |
Moderator: Matthew Vander Heiden, MD, PhD
Koch Institute for Integrative Cancer Research at MIT
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Comprehensive enumeration of immune cells in solid tumors using MIBI Michael R. Angelo, MD, PhD |
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Decoding cancer genomes with deep learning Olga Troyanskaya, PhD |
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Manifolds underlying plasticity in development, regeneration and cancer Dana Pe’er, PhD |
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Measuring and modeling variability in drug response in cells, tissues and clinical trials Peter Sorger, PhD |
Moderator: Susan Hockfield, PhD
Koch Institute for Integrative Cancer Research at MIT
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James (Jay) Bradner, MD |
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Aine Hanly, PhD Amgen |
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Clifford A. Hudis, MD American Society of Clinical Oncology |
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Constance D. Lehman, MD, PhD Massachusetts General Hospital |
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David Schenkein, MD GV |
Moderator: Sangeeta Bhatia, MD, PhD
Koch Institute for Integrative Cancer Research at MIT
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Machine learning for drug design Tommi Jaakkola, PhD |
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Artificial intelligence for pathology: From discovery to AI-powered companion diagnostics Andrew Beck |
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Early detection of pancreatic cancer Brian Wolpin, MD |
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From complex to complicated problems: What are the known unknowns, and unknown unknowns in using wearables to forecast symptom transitions Stephen H. Friend, MD, PhD |
Phillip Sharp, PhD
Koch Institute for Integrative Cancer Research at MIT
Thermo Fisher Scientific
Bayer
Bristol-Myers Squibb
Dragonfly Therapeutics, Inc.
Skyhawk Therapeutics, Inc.
Agilent Technologies, Inc.
Alnylam Pharmaceuticals
Sanofi
Takeda Pharmaceuticals
Calico Life Sciences LLC
Cell Signaling Technology