Bio-IT World Conference 2018 – Data Science Has Replaced Bioinformatics

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

Bio-IT 2017 – Data Security, Data Sharing, Data Access, Data Integration, Data …

 

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

PMWC 2017 Silicon Valley: Data sharing, privacy, and security

pmwc2017sv-logoThis year’s Precision Medicine World Conference (PMWC 2017 Silicon Valley) was comprised of many exciting sessions and presentations (almost 300 speakers across four tracks) in the area of next-generation sequencing, different diagnostics applications, precision medicine, big data analysis, the microbiome, large cohort studies, biobanking, and data interpretation/knowledge extraction. In addition to providing a great set of overview talks on latest developments and achievements across the health care sector, in pharma, and related to regulatory aspects, this latest rendition of PMWC also featured a government presence (the former FDA Commissioner Dr. Robert Califf and the former Cancer Moonshot Task Force Director Greg Simon) and Elizabeth Baca (Health Advisor to Governor Brown’s Office of Planning and Research) among others that shared with the audience their respective Continue reading

Repositive Wants to Overcome Data Analysis and Sharing Challenges to Facilitate the Advancement of Science

Repositive-logoLast month I had a chance to meet Fiona Nielsen, CEO of Repositive, when she was visiting San Francisco for the BlackBox Connect program. I took this opportunity to learn more about Repositive, the platform the company has built, its intended application, and why data sharing is so important. This blog addresses genomic data questions related to data sharing, challenges encountered with analysis and sharing platforms, and what Repositive is focusing on to mitigate these issues.

The following summarizes questions and answers from my dialogue with Fiona Nielsen.

EB:  What are some of the biggest challenges when it comes to working with genomics data both in the research and the clinical setting, and what are suggested solutions to address these challenges? What are the promises and challenges of sharing clinical and research genomics data?

FN: All research in a data-intensive science is challenging and hard work. There are high demands put on research data management and efficient analysis tools. In addition, within genomics linked to studying human genetic diseases, you have to deal with the extra Continue reading