AI in Biomedicine (EK2)
May 1-3, 2024  | Virtual Conference
Thomas Hartung, Weida Tong and Yvonne Will
 | Abstract Deadline: Mar. 20, 2024
This meeting will feature a Career Roundtable where trainees and early-career investigators will have the opportunity to interact with field leaders from across academic and industry sectors for essential career development advice and networking opportunities.
* Session Chair † Invited but not yet accepted | Program current as of May 30, 2024 | For the most up-to-date details, visit https://www.keystonesymposia.org
Wednesday, May 1, 2024
Welcome and Keynote Address  (8:00–9:00 AM)
Thomas Hartung, Johns Hopkins University
AI is the End of Biomedicine as we Know it (and I Feel Fine)
Ethical Implementation of AI in Biomedicine & Panel Discussion  (9:00–10:30 AM)
* Thomas Hartung, Johns Hopkins University
Session Chair
Ute Schmid, University of Bamberg
ML and AI Safety, Effectiveness and Explainability in Healthcare
Lomax Boyd, John Hopkins Berman Institute of Bioethics
The Emergence of Organoid Intelligence: Ethical Implications of Integrating Brain Organoids with Artificial Intelligence
Career Roundtable  (11:30–12:30 PM)
Jun Deng, Yale University School of Medicine
Professor & Director
Klaus P Hoeflich, Nested Therapeutics Inc
Chief Scientific Officer and Co-Founder
Nicole Kleinstreuer, NIEHS, National Institutes of Health
Director, NICEATM
AI in Drug Development (1:00–4:00 PM)
* Thomas Hartung, Johns Hopkins University
Session Chair
Vivek Natarajan, Google Health AI
How LLMs Might Help Scale World Class Healthcare to Everyone
Djork-Arné Clevert, Pfizer
AI Relating to Drug Discovery and Safety
Mohan Rao, Neurocrine Biosciences
AI/ML Models for Predicting Drug-Induced Liver Injury (DILI) in Small Molecules
Weida Tong, US Food and Drug Administration
The FDA Artificial Intelligence (AI) Program for Toxicology
Norbert Furtmann, Sanofi
Short Talk: Towards Biologics by Design: AI-driven Optimization of Next Generation Protein Therapeutics
James Shoemaker, Lena Biosciences, Inc.
Short Talk: Path Forward for the AI-guided Mitochondrial Toxicity Predictions for Predictive Toxicology
Sadasivan Shankar, Material Alchemy LLC
Short Talk: Hybrid Machine Learning Methodology for Guiding In Silico Toxicity Assessment
Thursday, May 2, 2024
AI in Medical Treatment & Precision Medicine (8:00–11:00 AM)
* Thomas Hartung, Johns Hopkins University
Session Chair
Frank Emmert-Streib, Tampere University
Digital Twins in Medicine: Opportunities and Challenges
Jun Deng, Yale University School of Medicine
Cancer Patient Digital Twins for Predictive Oncology: The State of the Art
Rui Zhang, University of Minnesota
Artificial Intelligence for Advancing Precision Medicine in Cancer, Aging and Nutrition Applications
Tong Wang, Brigham and Women’s Hospital; Harvard Medical School
Short Talk: Predicting Metabolic Response to Dietary Intervention using Deep Learning
Adriana Tomic, Boston University
Short Talk: PANDORA: AI Platform Accelerating the Discovery of Human Immune Memory Responses to Viruses and Vaccines
Panel Discussion: AI in Medical Treatment and Prevention (11:00–12:00 PM)
AI in Medical Imaging and Diagnostics (1:00–3:00 PM)
* Weida Tong, US Food and Drug Administration
Session Chair
Tuan Pham, Queen Mary University of London
Emerging Methods and Algorithms in Pathology Computer Vision
Yuan Wang, UCB
Short Talk: Computational Evaluation of Human Relevant in vitro Models Enables Cardiomyocyte Phenotype Differentiation
Mohan Kumar Gajendran, University of Missouri School of Medicine
Short Talk: A New Frontier in Early-Stage Glaucoma Detection: Machine Learning and Wavelet-Based ERG Signal Analysis
Poster Session (3:00–4:30 PM)
Friday, May 3, 2024
Future of AI in Biomedicine (8:00–11:00 AM)
* Weida Tong, US Food and Drug Administration
Session Chair
Katrina M. Waters, Pacific Northwest National Laboratory
AI in Infectious Disease (infection)
Alexandra Maertens, Johns Hopkins University
Green Toxicology – Anticipating Hazards by Chemicals (Toxicology)
Martin Hofmann-Apitius, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)
Using AI to understand the Co-Morbidity between COVID and Neurodegeneration
Antonella Prisco, Institute of Genetics and Biophysics, National Research Council (Italy)
Short Talk: Modeling Variations in Antibody Response Longevity Among Individuals
Dogus Dogru, Boston College
Short Talk: A Machine Learning-guided Approach to Uncover Microbiome-derived Autoantigen Mimics in Type 1 Diabetes
Networking Session (12:00–1:00 PM)
AI in Cancer Research and Therapeutics (1:00–2:30 PM)
* Weida Tong, US Food and Drug Administration
Session Chair
Channing Paller, Johns Hopkins University
The Risks and Rewards of AI Image Data in Oncology
Jin Choul Chai, SML Labtree
Short Talk: Analyzing the Knowledge Graph of Chronic Disease and Cancer in a Korean Cohort Using Graph Neural Networks
Baharan Meghdadi, University of Michigan
Short Talk: Machine Learning-based Method to Analyze Metabolic Fluxes of Patient Tumors
Joseph DeBartolo, Auron Therapeutics
Short Talk: AURIGIN: A comprehensive single-cell OMICs atlas of human development and an AI/ML framework to classify and identify the drivers of tumor plasticity and altered cellular state
Argenis Arriojas, University of Massachusetts Boston
Short Talk: AI-Enabled Automated Analysis of Chemotherapy Impact on Mitochondrial Morphology in triple negative breast cancer from transmission electron micrographs
Future of AI in Biomedicine II & Panel Discussion  (3:00–5:00 PM)
* Weida Tong, US Food and Drug Administration
Session Chair
Nicole Kleinstreuer, NIEHS, National Institutes of Health
Augmented Intelligence Along the CompTox Continuum
Pedro Gomez Vilda, Las Rozas de Madrid
Impact of Data Science on Clinical Applicability of Neurolinguistics
You Wu, City University of New York
Short Talk: Harnessing AI for Systems Medicine of Incurable Diseases