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SUMMARY:Transforming Drug Discovery using Digital Biology - Professor Daph
 ne Koller (Instiro)
DTSTART;VALUE=DATE-TIME:20221013T133000
DTEND;VALUE=DATE-TIME:20221013T143000
UID:https://talks.ox.ac.uk/talks/id/03f3ee5a-0181-4917-9ad6-3fcdca946797/
DESCRIPTION:Abstract: Modern medicine has given us effective tools to trea
 t some of the most significant and burdensome diseases. At the same time\,
  it is becoming consistently more challenging and more expensive to develo
 p new therapeutics. A key factor in this trend is that the drug developmen
 t process involves multiple steps\, each of which involves a complex and p
 rotracted experiment that often fails. We believe that\, for many of these
  phases\, it is possible to develop machine learning models to help predic
 t the outcome of these experiments\, and that those models\, while inevita
 bly imperfect\, can outperform predictions based on traditional heuristics
 . To achieve this goal\, we are bringing together high-quality data from h
 uman cohorts\, while also developing cutting edge methods in high throughp
 ut biology and chemistry that can produce massive amounts of in vitro data
  relevant to human disease and therapeutic interventions. Those are then u
 sed to train machine learning models that make predictions about novel tar
 gets\, coherent patient segments\, and the clinical effect of molecules. O
 ur ultimate goal is to develop a new approach to drug development that use
 s high-quality data and ML models to design novel\, safe\, and effective t
 herapies that help more people\, faster\, and at a lower cost.\nSpeakers:\
 nProfessor Daphne Koller (Instiro)
LOCATION:Big Data Institute (Seminar Room 0)\, Old Road Campus OX3 7LF
TZID:Europe/London
URL:https://talks.ox.ac.uk/talks/id/03f3ee5a-0181-4917-9ad6-3fcdca946797/
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DESCRIPTION:Talk:Transforming Drug Discovery using Digital Biology - Profe
 ssor Daphne Koller (Instiro)
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