BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//pretalx.com//juliacon-2026//talk//VEWE33
BEGIN:VTIMEZONE
TZID:CET
BEGIN:STANDARD
DTSTART:20001029T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000326T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-juliacon-2026-VEWE33@pretalx.com
DTSTART;TZID=CET:20260812T104500
DTEND;TZID=CET:20260812T110000
DESCRIPTION:In this talk physics informed neural networks are presented to 
 predict the plasma concentration time profiles of preclinical species and 
 human after i.v. bolus administration. The predictions are based on the nu
 merical representation of chemical structures or amino acid sequences and 
 compartmental modeling is used as the physical part to describe the pharma
 cokinetic profiles.
DTSTAMP:20260502T104026Z
LOCATION:Room 4
SUMMARY:Feature based  prediction of preclinical pharmacokinetic profiles u
 sing machine learning and compartmental modeling - Felix Jost
URL:https://pretalx.com/juliacon-2026/talk/VEWE33/
END:VEVENT
END:VCALENDAR