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CATEGORIES:Computational and Systems Biology
SUMMARY:DESCRIBING DRUG TOXICITY USING FUNCTIONAL DATA ANA
 LYSIS AND THE MODEL-DRIVEN CLUSTERING OF GENE EXPR
 ESSION BIOMARKERS. (HOW TO TURN YOUR MPHIL INTO A 
 PAYCHEQUE) - Dr Quin Wills (CSO\, Simugen Ltd)
DTSTART;TZID=Europe/London:20061011T140000
DTEND;TZID=Europe/London:20061011T150000
UID:TALK5405AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/5405
DESCRIPTION:To predict the toxicity of a newly developed drug 
 cheaply\, quickly and\naccurately is one of the to
 p concerns for the drug discovery and development\
 nindustry. It is believed that even minor improvem
 ents will save over US$200\nmillion per new drug. 
 The FDA believes that  "a new product development\
 ntoolkit containing computer-based predictive mode
 ls is urgently needed".\n\nToxicogenomics tries to
  understand and predict drug toxicity by studying\
 ngene expression. However\, the state of the art s
 uffers from two very\nimportant setbacks (i) it is
  not model-driven (ii) it doesn't explicitly\nhelp
  industry decide if a drug should canned or taken 
 further.\n\nUsing a human liver cell culture model
 \, SimuGen has demonstrated that with\nthe correct
  choice of biomarkers\, empiric functional data an
 alysis models\,\nand higher level exploratory anal
 ysis such as clustering (based on the\nmodels)\, i
 t is possible to predict and describe liver toxici
 ty with greater\nsensitivity than animal tests. We
  will work through some of the interesting\nproble
 ms that needed to be addressed to get this right.\
 n\nSimuGen is a company inspired by the MPhil Comp
 Bio course -  many of the\nanswers come directly f
 rom methods students will become familiar with.\n
LOCATION:MR5\, DAMTP
CONTACT:Danielle Stretch
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