BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM//UM*Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Detroit
TZURL:http://tzurl.org/zoneinfo/America/Detroit
X-LIC-LOCATION:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20070311T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20071104T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260508T091859
DTSTART;TZID=America/Detroit:20260512T093000
DTEND;TZID=America/Detroit:20260512T103000
SUMMARY:Workshop / Seminar:SCSAP Special Research Seminar
DESCRIPTION:SCSAP Special Research Seminar\nDate: Tuesday\, May 12th\, 2026\nTime: 9:30-10:30 AM EST\nLocation: Virtual ONLY\n\nTITLE: Working toward cancer care in 2030 : AI+X for Precision Medicine 2.0\, Population Health\, Aging and Global Health Impact\n\nFEATURING: Joe Poh Sheng YEONG\, MBBS\, PhD\, FRCPath\, IMCB (A*STAR) and Singapore General Hospital\n\nCancer clinical trials face major recruitment challenges\, with delays in patient matching contributing to high failure rates and billions in annual losses. Immune profiling technologies such as immunohistochemistry (IHC) and multiplex IHC are essential for biomarker discovery and precision oncology\, but their widespread use is limited by cost\, tissue scarcity\, and labor-intensive workflows.\n\nIn this talk\, I will discuss how AI-driven spatial biology approaches\, including our H&E 2.0 platform\, can accelerate patient triage and biomarker screening for clinical trial recruitment. As combination immunotherapies and antibody-drug conjugates expand\, scalable and cost-effective biomarker testing is becoming increasingly important for drug development and clinical decision-making.\nI will also highlight advances in spatial proteogenomics from our recent Nature cover study (April 2025)\, demonstrating how integrated spatial proteomics\, genomics\, and transcriptomics can reveal tumor heterogeneity\, immune interactions\, and noncanonical “dark” proteins involved in cancer progression. By combining AI with longitudinal population-scale data\, we developed predictive models capable of forecasting critical illness years in advance.\n\nFinally\, I will introduce an AI-powered “pseudo-time” framework aimed at supporting more timely\, accessible\, and value-based precision medicine worldwide.
UID:148170-21903180@events.umich.edu
URL:https://events.umich.edu/event/148170
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Agent Based Modelling,Aging And Global Health Impact,Ai In Science And Engineering,Artificial Intelligence,autophagy,Basic Science,Bioinformatics,Biointerfaces,Biology,biomedical,Biomedical Engineering,biomedical research,biomedicine,biophysics,Biosciences,cancer,cells,Chemistry,Complex Systems,Complex Systems Modelling,Computational Science,Drug Discovery,Engineering,epigenetics,Faculty,Free,genetics,human genetics,Human Genetics\, Genetics\, Epidemiology,Information and Technology,Life Science,life sciences,life sciences institute,Medicine,Natural Sciences,Neuroscience,Postdoctoral Research Fellows,Precision Health,Precision Medicine,Public Health,Research,Science,seminar,Talk,Virtual
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
END:VCALENDAR