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BEGIN:VEVENT
DTSTAMP:20260614T132904Z
DTSTART;VALUE=DATE-TIME:20160127T130000
DTEND;VALUE=DATE-TIME:20160127T140000
SUMMARY:Complexity Forum: Annabelle Ballesta (University of ÌÇÐÄTV)
TZID:Europe/London
UID:20160127-094d43454c4729f8014c55c989084e3e@warwick.ac.uk
CREATED:20150326T110652Z
DESCRIPTION:A multi-scale systems pharmacology approach for anticancer ch
 ronotherapy personalisation. Cancer management personalisation requires 
 to reliably account for molecular pathways of patient’s response to drug
  administration. In a context where clinical molecular data is usually m
 inimally available in individual patients\, multi-scale physiologically-
 based modelling appears as an adapted solution to describe underlying ge
 ne and protein networks ultimately responsible for treatment antitumor e
 fficacy and side effects. Basing mathematical models on physiology allow
 s the use of in vitro studies to design whole-body preclinical rodent mo
 dels\, to be further scaled to patient population data. The resulting hu
 man model\, that describes an average cancer patient\, may then be used 
 in global parameter sensitivity analyses to generate specific prediction
 s on relevant biomarkers. Partial re-calibration of the population human
  model for a given cancer patient according to individual biomarker reco
 rdings\, patient’s genetic background and therapeutic history further al
 low for chemotherapy personalisation. The patient-specific models then a
 ppeal for clinical validation\, thus initiating a novel trial design\, w
 here each individual patient receives personalised drug combinations/sch
 eduling computed via mathematical models\, informed with a continuous fl
 ow of multidimensional information obtained and tele-transmitted from pa
 tients. I will present how this approach was undertaken for personalisin
 g chronotherapy against digestive cancers with a particular focus on the
  anticancer drug irinotecan [1-3] . Multi-scale models representing irin
 otecan pharmacokinetics-pharmacodynamics (PK-PD) were designed. While PK
  quantifies the transport and metabolism of the drug and its metabolites
  that are driving exposure concentration over time\, PD quantifies drug 
 interactions with cellular targets and subsequent cytotoxicity. Referenc
 es 1. Dulong\, S.\, et al.\, Identification of Circadian Determinants of
  Cancer Chronotherapy through In Vitro Chronopharmacology and Mathematic
 al Modeling. Mol Cancer Ther\, 2015. 2. Ballesta\, A.\, et al.\, A syste
 ms biomedicine approach for chronotherapeutics optimization: focus on th
 e anticancer drug irinotecan\, in New Challenges for Cancer Systems Biom
 edicine. 2012\, Springer. 3. Ballesta\, A.\, et al.\, A combined experim
 ental and mathematical approach for molecular-based optimization of irin
 otecan circadian delivery. PLoS Comput Biol\, 2011. 7(9): p. e1002143. -
 - Lunch Group 2
LOCATION:D1.07
CATEGORIES:forum
LAST-MODIFIED:20160126T123228Z
ORGANIZER;CN=Heather Robson:
END:VEVENT
END:VCALENDAR