Accelerating Discoveries in Biology & Medicine Using AI (Nov. 19)
DATE: Nov. 19, 2024 (Tues.) TIME: 11am – 12pm KEYNOTE: César de la Fuente (University of Pennsylvania) PANELIST: Dionne Aleman (University of Toronto) PANELIST: Artem Babaian (University of Toronto) MODERATOR: Ivan Semeniuk (The Globe and Mail) METHOD: In-person & Online IN-PERSON LOCATION: Sheraton Centre Toronto Hotel (123 Queen Street West, Toronto) NOTE: This event is CPD accredited for physicians.
To register for the panel, you'll use the registration portal for the symposium. Please select your mode of attendance as “virtual” or “live” depending on how you’d like to attend the discussion. Enter the promo code “AIONLY” at checkout so you are not charged the symposium registration fee.
There will be a trainees-only lunch after the discussion to allow students, post-docs, and residents to engage and network with our esteemed speaker and panellists. Space is limited and available on a first-come, first-served basis.
The Emerging and Pandemic Infections Consortium (EPIC), Institute for Pandemics (IfP) and the Temerty Centre for AI Research and Education in Medicine (T-CAIREM) are proud to partner and host a three-part, hybrid speaker series this fall on AI and infectious diseases. Moderated by The Globe and Mail’s Ivan Semeniuk, this series will be a fascinating exploration of how artificial intelligence (AI) is revolutionizing the way we detect and respond to infectious diseases.
Join us on November 19 for the final session of our 3-part speaker series. We’ll hear from keynote speaker César de la Fuente (University of Pennsylvania) as well as panellists Dionne Aleman (University of Toronto), and Artem Babaian (University of Toronto). The Globe and Mail science journalist Ivan Semeniuk will moderate the event.
Following the discussion, trainees will have a chance to have lunch and network with the speakers.
Don't miss out on this opportunity to learn from experts in the field and gain valuable insights into the intersection of technology and public health.
LEARNING OBJECTIVES
• To understand the global health crisis of antibiotic resistance and its impact on public health, as well as the challenges associated with traditional drug discovery methods.
• To explore the role of AI and computational tools in accelerating antibiotic discovery, focusing on the application of machine learning to mine proteomes and genomes for new antimicrobial compounds.
• To learn about molecular de-extinction and how ancient organisms can be explored using AI to uncover new antibiotic candidates from extinct species.
• To identify novel approaches for future antibiotic development by leveraging AI to mine global microbiomes and develop new antimicrobial molecules.
ABOUT THE KEYNOTE SPEAKER
César de la Fuente is a Presidential Assistant Professor at the University of Pennsylvania, where he leads the Machine Biology Group. He completed postdoctoral research at the Massachusetts Institute of Technology (MIT) and earned a PhD from the University of British Columbia (UBC). His research goal is to use the power of machines to accelerate discoveries in biology and medicine. Specifically, he pioneered the development of the first computer-designed antibiotic with efficacy in animal models, demonstrating the application of AI for antibiotic discovery and helping launch this emerging field. His lab has also been in the vanguard of developing computational methods to mine the world’s biological information, leading to the breakthrough discovery of a whole new world of antimicrobials. These efforts explored the human proteome as a source of antibiotics for the first time. De la Fuente’s group was also the first to find therapeutic molecules in extinct organisms, launching the field of molecular de-extinction. Molecular de-extinction has already yielded preclinical antibiotic candidates. Altogether, de la Fuente’s work has dramatically accelerated the time needed to discover preclinical candidates from years to hours. Additional advances from his lab include designing algorithms for antibiotic discovery, reprogramming venoms into antimicrobials, developing autonomous nanorobots to treat infections, creating novel resistance-proof antimicrobial materials, and inventing rapid, low-cost diagnostic devices for COVID-19 and other infections.
Prof. de la Fuente is an NIH MIRA investigator and has received recognition and research funding from numerous organizations. De la Fuente has received over 70 national and international awards. He is an elected Fellow of the American Institute for Medical and Biological Engineering (AIMBE), becoming one of the youngest ever to be inducted. MIT Technology Review recognized him as one of the world’s top innovators for “digitizing evolution to make better antibiotics.” He was selected as the inaugural recipient of the Langer Prize and as an ACS Kavli Emerging Leader in Chemistry, an ASM Distinguished Lecturer, Waksman Foundation Lecturer, and received the Miklós Bondanszky Award, AIChE’s 35 Under 35 Award, Society of Hispanic Professional Engineers Young Investigator Award, and the ACS Infectious Diseases Young Investigator Award. He also received the Thermo Fisher Award, as well as the EMBS Academic Early Career Achievement Award “For the pioneering development of novel antibiotics designed using principles from computation, engineering, and biology.” Most recently, Prof. de la Fuente was awarded the prestigious Princess of Girona Prize, the ASM Award for Early Career Applied and Biotechnological Research, the Rao Makineni Lectureship Award by the American Peptide Society, and was selected as a National Academy of Medicine Emerging Leader in Health and Medicine. De la Fuente serves on the editorial boards of numerous scholarly journals and is currently an Associate Editor of Drug Resistance Updates (IF= 24.3; the premier international drug resistance journal), Nature Communications Biology, Bioactive Materials (IF = 18.9), Bioengineering & Translational Medicine, and Digital Discovery. He has been named a Highly Cited Researcher by Clarivate multiple times. Prof. de la Fuente has given over 250 invited lectures, including numerous Keynote and Named Lectures, and has spoken at TEDx. He has co-authored an influential book on machine learning for drug discovery, and his scientific discoveries have yielded multiple patents and over 150 publications, including papers in Science, Cell, Cell Host Microbe, Nature Biomedical Engineering, Nature Communications, PNAS, ACS Nano, Nature Chemical Biology, and Advanced Materials.
