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SUMMARY:AI Meets Cancer - Dr Jasmin Fisher - Department of Biochemistry\, 
  University of Cambridge &amp\; Microsoft Research
DTSTART:20170301T161500Z
DTEND:20170301T171500Z
UID:TALK69551@talks.cam.ac.uk
CONTACT:David Greaves
DESCRIPTION:Cancers are pathologies driven by genetic mutations that disru
 pt a multitude of signalling pathways operating across different cell type
 s interacting in highly complex ways. No two cancers\, even of the same ty
 pe\, are the same. The holy grail of cancer treatment is to analyse the pa
 tient’s genome and predict a sequence and combination of therapies that 
 will destroy that patient’s cancer with no adverse side effects. By deve
 loping executable models that can simulate cancer tumours at different lev
 els of abstraction\, we are on the threshold of being able to deliver on t
 his vision. The state-of-the-art in executable biology is the use of forma
 l methods and software verification to describe biological systems and exp
 lore their properties. Using program synthesis methods we can directly bui
 ld such models from patients’ data. This approach has already been used 
 to find new more efficient therapies for Leukaemia in partnership with Ast
 raZenenca.  The next big question\, as we collect more and more patient ge
 nomic data and history of cancer treatments\, is how can we use AI methods
  to drive therapeutic regimes directly from patients’ data? In the talk\
 , I will showcase recent results and share my ambitions in this space.\n
LOCATION:Lecture Theatre 1\, Computer Laboratory
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