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SUMMARY:Describing drug toxicity using functional data analysis and the mo
 del-driven clustering of gene-expression  bio-markers - Dr. Quin Wills Sim
 uGen
DTSTART:20060911T130000Z
DTEND:20060911T140000Z
UID:TALK5292@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
  urgently needed’.\n\nToxicogenomics tries to understand and predict drug
  toxicity by studying\ngene expression. However\, the state of the art suf
 fers 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 demonstra
 ted that with\nthe correct choice of biomarkers\, empiric functional data 
 analysis models\,\nand higher level exploratory analysis such as clusterin
 g (based on the\nmodels)\, it is possible to predict and describe liver to
 xicity with greater\nsensitivity than animal tests. We will work through s
 ome of the interesting\nproblems that needed to be addressed to get this r
 ight.\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\n 
LOCATION:MR5\, DAMTP
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