BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Talks.cam//talks.cam.ac.uk// X-WR-CALNAME:Talks.cam BEGIN:VEVENT SUMMARY:Artificial Intelligence for identifying novel therapeutic targets\ , biomarkers and drug repositioning opportunities - Dr Namshik Han\, Head of Computational Biology\, Milner Therapeutics Institute DTSTART:20200528T083000Z DTEND:20200528T093000Z UID:TALK140536@talks.cam.ac.uk CONTACT:Louisa Bellis DESCRIPTION:This talk will be given remotely on Google Meet -meet.google.c om/swu-sycb-tkz\n\n*Abstract:* \nThe challenges in drug discovery\, includ ing high attrition rates in late development stage\, are well documented. This has led to an increased interest and need for applying machine learni ng and artificial intelligence across the drug discovery pipeline from tar get identification to chemical lead selection and optimisation. It has als o been demonstrated that drugs with human genetic validation data are more likely to succeed in the clinic. To address this\, it is essential to unr avel genetic networks to identify new or better targets for which the unde rlying mechanism is clear. Despite the significant advances in next genera tion sequencing technologies and evolving databases of patient cohorts\, t he sheer complexity of these datasets makes their integration and interrog ation a daunting task. Through the development and application of cutting- edge computational approaches\, such as artificial intelligence\, machine learning and mathematical modelling\, to pharmacogenomics and drug discove ry\, we identify novel therapeutic targets\, biomarkers and drug repositio ning opportunities. In this talk I will focus on (1) systematic integratio n and harmonisation of biomedical big data (2) multi-omic disease associat ion study and (3) network theory-based analysis of targetable pathway whic h have significant potential to provide unprecedented insights into vital biological processes and the control hubs that underpin disease. LOCATION:Online - Google Hangouts END:VEVENT END:VCALENDAR