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SUMMARY:DESCRIBING DRUG TOXICITY USING FUNCTIONAL DATA ANALYSIS AND THE MO
 DEL-DRIVEN CLUSTERING OF GENE EXPRESSION BIOMARKERS. (HOW TO TURN YOUR MPH
 IL INTO A PAYCHEQUE) - Dr Quin Wills (CSO\, Simugen Ltd)
DTSTART:20061011T130000Z
DTEND:20061011T140000Z
UID:TALK5405@talks.cam.ac.uk
CONTACT:Danielle Stretch
DESCRIPTION:To predict the toxicity of a newly developed drug cheaply\, qu
 ickly and\naccurately is one of the top concerns for the drug discovery an
 d development\nindustry. It is believed that even minor improvements will 
 save over US$200\nmillion per new drug. The FDA believes that  "a new prod
 uct development\ntoolkit containing computer-based predictive models is ur
 gently needed".\n\nToxicogenomics tries to understand and predict drug tox
 icity by studying\ngene expression. However\, the state of the art suffers
  from two very\nimportant setbacks (i) it is not model-driven (ii) it does
 n't explicitly\nhelp industry decide if a drug should canned or taken furt
 her.\n\nUsing a human liver cell culture model\, SimuGen has demonstrated 
 that with\nthe correct choice of biomarkers\, empiric functional data anal
 ysis models\,\nand higher level exploratory analysis such as clustering (b
 ased on the\nmodels)\, it is possible to predict and describe liver toxici
 ty with greater\nsensitivity than animal tests. We will work through some 
 of the interesting\nproblems that needed to be addressed to get this right
 .\n\nSimuGen is a company inspired by the MPhil CompBio course -  many of 
 the\nanswers come directly from methods students will become familiar with
 .\n
LOCATION:MR5\, DAMTP
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