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SUMMARY:From measurement to decision: a tissue-aware digital-twin platform
  for CAR T cell dosimetry - Luciana Luque (Cancer Research UK)
DTSTART:20250919T093000Z
DTEND:20250919T093500Z
UID:TALK235207@talks.cam.ac.uk
DESCRIPTION:CAR T cell therapy is one of the most exciting advances in mod
 ern cancer treatment. In this approach\, a patient&rsquo\;s own immune cel
 ls are reprogrammed in the laboratory with a synthetic &ldquo\;chimeric an
 tigen receptor&rdquo\; (CAR) so that they can recognise and destroy cancer
  cells. However\, relapse and primary resistance remain common\, and we do
  not fully understand why.\nExperimental systems (in vitro and in vivo) ar
 e invaluable for probing CAR T functionality and persistence\, but many me
 chanisms and &ldquo\;what-if&rdquo\; dosing questions cannot be tested dir
 ectly in the lab. Agent-based models (ABMs) complement experiments by enab
 ling exploration of dosimetry strategies and revealing emergent behaviours
 \, while aligning with the 3Rs (Replace\, Reduce\, Refine) to save time\, 
 cost and animals.\nABMs nevertheless require rigorous calibration and vali
 dation\; without them\, models may fail to capture tumour progression and 
 lose predictive power. Progress is further limited by the scarcity of robu
 st\, organ-resolved datasets and by implementations that are computational
 ly intensive and hard to use in clinical workflows.\nTo address these gaps
 \, we are assembling an integrative platform linking dry-lab modelling\, w
 et-lab measurement and translational read-outs. At its core\, our publishe
 d ABM serves as the mechanistic engine\; around it\, an organ-to-organ atl
 as provides concise\, identifiable\, tissue-specific priors for CAR T beha
 viour (initially in the B-cell acute lymphoblastic leukaemia mouse context
 )\, with targeted assays to inform calibration and validation. To make vir
 tual-trial exploration practical and accessible\, we are porting the model
  to a high-performance ABM backend and exposing a simple interface aimed a
 t non-computational users.\nBy calibrating the ABM to patient-specific mea
 surements\, we instantiate a digital twin\, a mechanistic replica on which
  to test dose\, fractionation\, timing and route\, turning the platform in
 to a clinically useful decision aid and closing the loop from measurement 
 to decision.\nIn this poster\, I will present our ABM&rsquo\;s current cap
 abilities and insights\, outline the platform blueprint (including the atl
 as and high-performance deployment)\, and share a clear roadmap for transl
 ating tissue-aware computational twins into practical dosing and route dec
 isions.\n&nbsp\;
LOCATION:Seminar Room 1\, Newton Institute
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