The David H. Koch Institute for Integrative Cancer Research at MITThe David H. Koch Institute for Integrative Cancer Research at MIT

Massachusetts Institute of Technology

National Cancer Institute Cancer Center

Science + Engineering... Conquering Cancer Together

Summer Symposium 2019

Machine Learning and Cancer

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.

Introductory Remarks


Tyler Jacks, PhD
Koch Institute for Integrative Cancer Research at MIT

Phillip Sharp, PhD
Koch Institute for Integrative Cancer Research at MIT

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Keynote Speakers | Machine Learning in Cancer Research: The Need and the Opportunity 

Moderator: Phillip Sharp, PhD
Koch Institute for Integrative Cancer Research at MIT

Immune checkpoint blockade in cancer therapy: Historical perspective, new opportunities, and prospects for cures

James P. Allison, PhD
MD Anderson Cancer Center

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Cell atlases as roadmaps to cancer

Aviv Regev, PhD
Broad Institute, Koch Institute for Integrative Cancer Research at MIT

How machine learning changes cancer research

Regina Barzilay, PhD
MIT Computer Science and Artificial Intelligence Lab, Koch Institute for Integrative Cancer Research at MIT

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Session 1 | Machine Learning to Deciper Cellular and Molecular Mechanisms in Cancer

Moderator: Matthew Vander Heiden, MD, PhD
Koch Institute for Integrative Cancer Research at MIT

Comprehensive enumeration of immune cells in solid tumors using MIBI

Michael R. Angelo, MD, PhD
Stanford University

Decoding cancer genomes with deep learning

Olga Troyanskaya, PhD
Princeton University

Manifolds underlying plasticity in development, regeneration and cancer

Dana Pe’er, PhD
Memorial Sloan Kettering Cancer Center

Measuring and modeling variability in drug response in cells, tissues and clinical trials

Peter Sorger, PhD
Harvard Medical School

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Panel Discussion | Big Data, Computation and the Future of Health Care 

Moderator: Susan Hockfield, PhD
Koch Institute for Integrative Cancer Research at MIT

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James (Jay) Bradner, MD
Novartis

Aine Hanly, PhD 
Amgen
Clifford A. Hudis, MD
American Society of Clinical Oncology
Constance D. Lehman, MD, PhD
Massachusetts General Hospital
David Schenkein​, MD
GV

Session 2 | Machine Learning into the Clinic 

Moderator: Sangeeta Bhatia, MD, PhD
Koch Institute for Integrative Cancer Research at MIT

Machine learning for drug design

Tommi Jaakkola, PhD
MIT Computer Science and Artificial Intelligence Lab

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Artificial intelligence for pathology: From discovery to AI-powered companion diagnostics

Andrew Beck
PathAI

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Early detection of pancreatic cancer

Brian Wolpin, MD
Dana-Farber Cancer Institute

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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
University of Oxford, 4YouandMe

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Closing Remarks


Phillip Sharp, PhD
Koch Institute for Integrative Cancer Research at MIT

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Thank you to our sponsors


Platinum

Thermo Fisher Scientific

Gold

Bayer
Bristol-Myers Squibb
Dragonfly Therapeutics, Inc.
Skyhawk Therapeutics, Inc.

Silver

Agilent Technologies, Inc.
Alnylam Pharmaceuticals
Sanofi
Takeda Pharmaceuticals

Bronze

Calico Life Sciences LLC
Cell Signaling Technology

With additional support provided by