BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//SciLifeLab - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:SciLifeLab
X-ORIGINAL-URL:https://www.scilifelab.se
X-WR-CALDESC:Events for SciLifeLab
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20270328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20271031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Stockholm:20260417T100000
DTEND;TZID=Europe/Stockholm:20260417T110000
DTSTAMP:20260416T102645
CREATED:20260407T151030Z
LAST-MODIFIED:20260413T150954Z
UID:197339-1776420000-1776423600@www.scilifelab.se
SUMMARY:AI Agent in Drug Discovery - Current Advance and Application
DESCRIPTION:Dinh Long Huynh \n\n\n\nNBIS and SciLifeLab Data Centre arrange an open SciLifeLab AI Seminar Series aimed at knowledge-sharing about Artificial Intelligence and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms\, typically between 10 and 11 am\, with approx. 45 min presentation and 15 min discussion. \n\n\n\nWhen: April 17\, 10:00-11:00 \n\n\n\nWhere:  Zoom http://meet.nbis.se/ainw \n\n\n\nSpeaker: Dinh Long HuynhUppsala University (Ola Spjuth group)Abstract \n\n\n\nArtificial intelligence (AI) has been shaping drug discovery for decades — from the early use of predictive models to the recent explosion of generative AI. Today\, we are entering a third wave: Agentic AI. Together with traditional predictive or generative models\, as well as computational and robot execution tools\, agentic AI embodies autonomy in drug discovery — it perceives its environment\, reasons about goals\, and takes actions with minimal human intervention. This talk explores the evolution from generative to agentic systems and why this shift matters for life sciences. We will unpack the architectural foundations of agentic AI\, showing how they enable closed-loop discovery — where AI not only designs hypotheses or molecules but also plans\, executes\, refines\, and learns from experiments. Through real-world case studies and a short live demonstration\, we will illustrate how agentic AI can transform the research cycle — accelerating hypothesis generation\, optimizing experiment design\, and integrating multimodal data across biology and chemistry. We will also discuss the current challenges and the road ahead for agentic AI systems in biopharma R&D. \n\n\n\nTo stay updated\, you can join our email list by contacting ai-network@scilifelab.se  \n\n\n\n\nJoin Seminar
URL:https://www.scilifelab.se/event/ai-agent-in-drug-discovery-current-advance-and-application/
LOCATION:Online event via Zoom
CATEGORIES:Event
END:VEVENT
END:VCALENDAR