This year’s conference kicked off with an interesting Data Science panel that included Tanya Cashorali (TCB Analytics), Jerald Schindler (Alkermes), John Reynders (Alexion Pharmaceuticals), and Lihua Yu (H3 Biomedicine). Without a doubt, data science is important and involves much more than big data, including the entire workflow of data creation, to insight generation, and decision-making. One key message that came across is that not all data is big data, and that we need improvements in data collection and infrastructure support for data analysis and management. Other key take-home messages: breaking down data silos, educating about responsibility, being responsible to not act independently on data, creating an environment that motivates everybody within a team to share, not rewarding bad data behavior, and being insensitive to data sharing to get more out in return. The big issue here is the culture. If the culture rewards Continue reading
The 15th annual Bio-IT conference – with the theme “Building a global network for precision medicine by uniting the Bio-IT community” – clearly had as its underlying theme the many different aspects of data that need to be addressed to make precision medicine a true reality, as echoed throughout the many talks and discussions. This was reflected in both the keynotes, as well as the panel discussions that focused on data regulations, security, and getting patients to feel good about sharing their data. The first hackathon launched by Bio-IT World had the focus on FAIR [findable, accessible, interoperable, and reproducible] data. Many commercial announcements or recent advancements in artificial intelligence revolved around new and improved data analysis solutions. This year’s Best in Show award selections featured Starfish Storage’s Starfish V4, SciBite LaunchPad, SolveBio’s Operating System for Molecular Information, Dana Farber Cancer Institute / The Hyve’s MatchMiner v1.0, and Seven Bridges’ CAVATICA.
Coinciding with Bio-IT were a number of major announcements as listed below: Continue reading