BioTeam has reached a significant milestone: our 20th anniversary. From the beginning, our mission has been to accelerate scientific discovery by utilizing advanced technologies as the foundation for making data-intensive science easier for scientists to do. Through the years, our IT consulting company has evolved to help our clients achieve their scientific missions by strategically partnering with them in a holistic and collaborative manner at the intersection of science, data, and technology.
One of the most pressing issues in life sciences and biomedical research is the lack of unified data ecosystems throughout the community. Data production is at an all-time high, but data consumption is costly, requires a level of effort that isn’t scalable, and is significantly blocked by a lack of common data standards. For many years, the industry has focused on the ideals of making data findable, accessible, interoperable, and repeatable (FAIR), but has yet to make significant progress in implementing it across the board. As a result, the transition from the information age to the analytics age has been slow and arduous.
BioTeam found itself working with our clients on the entire spectrum of services spanning from the laboratory/clinic to the datacenter, and we created our team to match those needs. It became clear that the primary asset we were focusing on was data. Data is certainly the currency of science, and if currency doesn’t flow, economies collapse. So, we reimagined our engagements to be centered around the various aspects of creating viable scientific data ecosystems so that organizations can make better use of their data assets and consume community datasets more easily. The acceleration of AI/ML research in the last few years added pressure to create data ecosystems since having well understood and well-annotated data is key to successful adoption of modern ML methodologies.
“We’ve had the privilege of engaging in groundbreaking projects with hundreds of biotech, pharma, government, academic, and non-profit organizations throughout our 20 years,” said Ari Berman, CEO of BioTeam. “We’re grateful for the trust our clients place in our team of experts to help them solve their unique problems in ways that unify and align their scientific and IT cultures with the business.”
“When my father died of pancreatic cancer five weeks after being diagnosed, I knew I was devoted to increasing the speed of science,” said Stan Gloss, Co-Founder and Fellow, BioTeam. “When we launched BioTeam, we had a sole purpose: to accelerate science research. I am gratified that today our commitment to move science forward by solving problems at the intersection of biomedicine, data science, and technology remains stronger than ever.”
“Scientists must execute large-scale simulations and analytics throughout their ecosystem without downtime,” said Chris Dagdigian, Co-Founder and Sr. Technical Director, BioTeam. “This is why we’ve developed interdisciplinary expertise to build systems that allow petabytes of data to move seamlessly back and forth on converged infrastructures that interconnect resources on distributed devices, commercial clouds, and HPC centers.”
“Since inception, we have been dedicated to delivering best-fit leading-edge solutions, always putting our clients’ needs first, and building solid partnerships with clients,” stated Bill Van Etten, Co-Founder and Sr. Scientific Consultant, BioTeam. “Today, we continue to believe that deep collaboration with our clients is critical to delivering the best outcomes.”
Join us on December 7 at 1pm EST for our webinar: 20 Years of BioTeam: Lessons Learned and Future Insights in Scientific Digital Transformation.
In this webinar, BioTeam shares lessons learned and future insights from 20 years of helping scientific organizations accelerate scientific discovery by applying advanced technologies and data science strategies.
Scientists, scientific leaders, and IT leaders are invited to join founders Stan Gloss, Bill Van Etten, and Chris Dagdigian, together with CEO Ari Berman, for a lively discussion about the importance of scientific data as the foundation of modern scientific discovery. Learn about:
- How scientific computing in life sciences changed in the past 20 years
- How to solve the current problem: lack of unified scientific data ecosystems
- The concept of data supply chains in modern scientific research, and why they are important
- Pitfalls and solutions to making your data analysis-ready
- Choosing the right infrastructure to support connected data ecosystems