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SUMMARY:VPopMIP: A Mixed-Integer Programming Approach to Virtual Populatio
 n Generation - Ivan Borisov\, Evgeny Metelkin
DTSTART;TZID=Europe/Berlin:20260812T114500
DTEND;TZID=Europe/Berlin:20260812T120000
DTSTAMP:20260812T212619Z
UID:pretalx-juliacon-2026-MGNSFV@pretalx.com
DESCRIPTION:Virtual Populations (VPops) are widely used in Quantitative Sy
 stems Pharmacology (QSP) to represent variability in patient responses to 
 therapy using parameterized dynamical models. Unlike traditional modeling 
 approaches that focus on average treatment effects\, VPop methods aim to r
 eproduce the full distribution of clinical outcomes observed in trials.\nW
 e introduce VPopMIP\, a Julia package implementing a Mixed-Integer Program
 ming (MIP) formulation for generating VPops that match clinical endpoints.
  In contrast to many existing approaches that require individual-level pat
 ient data\, VPopMIP enables calibration to published clinical summary stat
 istics (e.g.\, response rates\, medians\, and confidence intervals)\, whic
 h are more commonly available in practice.\nThe method formulates virtual 
 patient selection as a constrained optimization problem that enforces agre
 ement with multiple outcome measures across therapies.\nWe demonstrate the
  methodology using a solid tumor model with multiple efficacy endpoints ac
 ross treatment regimens. The results illustrate how MIP-based selection pr
 ovides an efficient way to construct clinically consistent virtual populat
 ions.
LOCATION:Muschel — N1
URL:https://pretalx.com/juliacon-2026/talk/MGNSFV/
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