Program
Please note that this meeting will take place as an in-person event in Montreal and will not live-stream content for virtual participation. The meeting content will be recorded and made available as an on-demand program after the conference.
All presentations are scheduled to be live, in-person presentations at the date and time specified below unless noted otherwise. Program in progress.
Thursday, July 10
Friday, July 11
- Keynote Lecture 2
- Plenary Session 1: ML/AI for Drug Discovery, Repurposing, and Response Prediction
- Plenary Session 2: ML/AI for Genomic and Temporal Predictions
- AI Synergy Forum: Fostering Innovation Through Collaboration
- Plenary Session 3: Multimodal AI for Clinical Applications in Oncology
- Plenary Session 4: Bias and Fairness in AI Research and Deployed Models
- Plenary Session 5: Cancer Applications of Foundation Models
Saturday, July 12
- Keynote Lecture 3
- Plenary Session 6: ML/AI for Single Cell and Spatial Data, H&E, and Molecular Biomarker Discovery
- Plenary Session 7: ML/AI for Radiological Imaging
- Plenary Session 8: How Do We Make AI Research Better for Society
- Closing Remarks
WELCOME AND Opening Keynote Lectures
6:30-7:15 p.m.
- 6:30 p.m. | Welcome and Introduction of Keynote Speaker
- 6:35 p.m. | Computational approaches to mapping cells, tissues, and tumor progression: Where does AI help?
Dana Pe’er, Memorial Sloan Kettering Cancer Center, New York, New York
poster session A/ Opening Reception
7:30-9 p.m.
Continental Breakfast and networking roundtables
7-8 a.m.
Keynote Lecture 2
8-8:45 a.m.
- 8 a.m. | Introduction of Keynote Speaker
- 8:05 a.m.
Marinka Zitnik, Harvard University, Boston, Massachusetts
Plenary Session 1: ML/AI for Drug Discovery, Repurposing, and Response Prediction
8:50-10:10 a.m.
- 8:50 a.m. | Supporting anticancer drug discovery by knowledge graph mining and cancer target-focused cheminformatics modeling
Alexander Tropsha, University of North Carolina, Chapel Hill, North Carolina - 9:20 a.m.
Charlotte Bunne, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
Short talks selected from proffered abstracts
Break
10:10-10:25 a.m.
Plenary Session 2: ML/AI for Genomic and Temporal Predictions
10:25-11:45 a.m.
- 10:25 a.m.
Samantha Riesenfeld, University of Chicago, Pritzker School of Molecular Engineering, Chicago, Illinois - 10:55 a.m.
Raul Rabadan, Columbia University Irving Medical Center, New York, New York
Short talks selected from proffered abstracts
Break
11:45 a.m.-12 p.m.
AI Synergy Forum: Fostering Innovation Through Collaboration
12-12:45 p.m.
- Theme 1: Open science: Data and code sharing and reusability
Shirin A. Enger, McGill University, Montreal, Quebec, Canada - Theme 2: AI using non/minimally invasive modalities for cancer applications
Florian Markowetz, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom - Theme 3: Monitoring model performance/drift in research and clinical settings
- Theme 4: To be announced
Skye Bork, PACT AI
Additional details to be announced
Free time/lunch on own
12:45-2:15 p.m.
Plenary Session 3: Multimodal AI for Clinical Applications in Oncology
2:15-3:45 p.m.
- 2:15 p.m.
Christina Curtis, Stanford University, Stanford, California - 2:45 p.m. | Alignment and integration of spatial multi-omics tumor profiles
Ben Raphael, Princeton University, Princeton, New Jersey - 3:15 p.m. | Inferring genomic properties and histologic subtypes of solid tumors from H&E whole-slide images
Kevin Boehm, MSKCC, New York, New York
Break
3:35-3:50 p.m.
Plenary Session 4: Bias and Fairness in AI Research and Deployed Models
3:50-5:05 p.m.
- 3:50 p.m. | Uncovering and mitigating bias in auto-segmentation models in radiation oncology
Benjamin Haibe-Kains, UHN Princess Margaret Cancer Centre, Toronto, ON, Canada - 4:50 p.m. | A practical framework for operationalizing responsible and equitable AI in healthcare: Tackling bias, inequity, and implementation challenges
Benjamin Grant, Cancer Digital Intelligence, Princess Margaret Cancer Centre, Toronto, ON, Canada
Additional speakers to be announced
Break
5:10-5:25 p.m.
Plenary Session 5: Cancer Applications of Foundation Models
5:25-6:35 p.m.
- 5:25 p.m.
Valentina Boeva, ETH Zurich, Zurich, Switzerland - 5:55 p.m. | Evaluating and overseeing large language models for oncology
Danielle S. Bitterman, Harvard Medical School, Boston, Massachusetts - 6:25 p.m. | Learning the language of somatic mutations: A large language model approach to precision oncology
John-William Sidhom, Weill Cornell Medicine, New York, New York
poster session B/ reception
7-9 p.m.
Continental Breakfast and networking roundtables
7-8 a.m.
Keynote lecture 3
8-8:45 a.m.
- 8 a.m. | Introduction of Keynote Speaker
- 8:05 a.m. | Accelerating oncology drug discovery with the power of microscopy and AI
Anne Carpenter, Broad Institute, Cambridge, Massachusetts
Plenary Session 6: ML/AI for Single Cell and Spatial Data, H&E, and Molecular Biomarker Discovery
8:50-10:10 a.m.
- 8:50 a.m.
Elana J. Fertig, University of Maryland, Baltimore, Maryland - 9:20 a.m.
Eytan Ruppin, National Cancer Institute, Bethesda, Maryland - 9:50 a.m. | Analysis of pathologists’ intraobserver, interobserver and AI agreement in breast cancer HER2 scoring: AI-assessed intra-sample tumor heterogeneity relates to lower agreement among pathologists and with AI
Pedro Simonis S. M. Ferrari, D’Or Institute of Research & Education, São Paulo, Brazil
Break
10:10-10:20 a.m.
Plenary Session 7: ML/AI for Radiological Imaging
10:20-11:40 a.m.
- 10:20 a.m.
Catherine Coolens, University Health Network, Toronto, Ontario, Canada - 10:50 a.m.
Caroline Chung, UT MD Anderson Cancer Center, Houston, Texas - 11:20-11:35 a.m. | Automated segmentation pipeline for radiological imaging using UniverSeg and similarity-guided support set retrieval
Niket Patel, Drexel University College of Medicine, Philadelphia, Pennsylvania
Break
11:40-11:50 a.m.
Plenary Session 8: How do we make AI research better for society
11:50 a.m.-1:20 p.m.
- 11:50 a.m.
Marzyeh Ghassemi, Massachusetts Institute of Technology, Cambridge, Massachusetts - 12:20 p.m.
Jeff Leek, Fred Hutchinson Cancer Center, Seattle, Washington - 12:50 p.m. | The impact of bringing complex data to the point of care
Casey Greene, University of Colorado, Aurora, Colorado
Closing Remarks
1:20 p.m.