Leading Biotech Data Teams

With hundreds of startups founded each year, the relatively new field of data-focused biotech—or TechBio—is growing rapidly. But without enough experienced practitioners to go around, most organizations hire data scientists with minimal biotech experience and lab scientists who've taken a crash course in data science. This arrangement is problematic.

The way lab scientists and data scientists think and work is fundamentally different. But there is a solution. This report introduces biocode principles to help these scientists reframe the way they think about their role, their team's role, and the tools they use to fulfill those roles. Lab and data scientists alike will learn how to address the underlying issues so they can focus on solving these technology problems together.

Each of the following chapters presents a vital biocode principle

"Defining Objectives" explores how to broaden the way teams view their work, shifting from purely technical objectives to organizational-level scientific objectives
"Building Collaborations" encourages teams to focus their energy on collaboration with partner teams rather than guard their time for technical work
"Deploying Tooling" covers ways to coordinate each team's work with the cadence of experiments and lab work