Tuesday, 26 November 2013

The 3rd IMO Workshop on Personalized Medicine


Last week I attended an interdisciplinary workshop at Moffitt organised by the Integrated Mathematical Oncology department. It was the third incarnation of the event and this time the focus was on personalised medicine. The structure of the workshop was as follows: the participants were divided into four teams with roughly 10 people in each, containing clinicians, experimentalists and theoreticians. Each team was assigned a specific type of cancer (in line with the knowledge of the clinicians and experimentalists), and the aim was to construct, analyse and present a clinically relevant model, all within 4 days.

I ended up in the "lung team" as one out of three team leaders (the others being Lori Hazlehurst and Ben Creelan), and we decided to work on the problem of drug resistance in stage IV non-small cell lung cancer. Four days is a very short time to achieve the goals described above, and the workshop was an intense experience. Reaching across disciplines, trying to talk the same language, define a reasonable question, formulate a mathematical model, simulate it, get nice graphical results and create a nice looking presentation. Our team probably averaged 12 hours of work per day, and the last evening we didn't get to bed until 3 am. As tough as it might seem it was also rewarding, and I learned a lot.

In contrast to most academic events there was also a competitive element. Three external judges picked a winning team based on a number of criteria (originality, success, data utilisation etc.), and the winning team leaders were awarded a $50K pilot grant. The idea being that the project started at the workshop will develop into a full scale interdisciplinary research project.

All four teams (blood, lung, urogenital, breast) did a great job, but apparently the judges thought that our team was the most accomplished and awarded us the grant. What up to then had seemed abstract and remote all of a sudden became very real, and I'm now looking forward to spending the grant on refining and validating our model.







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