The life science industry is shifting to a new model to support the next generation of therapeutic development. In order to stay competitive, life science companies need data systems that help address a new set of challenges:
- With teams more distributed and specialized than ever, how can they remain in close collaboration?
- As vast amounts of highly complex data are generated, how can data remain centralized and interlinked to enable analysis?
- As scientific platforms rapidly evolve, how can processes be able to adapt quickly to capture the relevant data?
To better understand the nature of these challenges, we spoke with scientists and R&D leaders throughout the industry. In this white paper, we discuss the six questions that emerged as common themes as well as suggestions for how you can address them in your own R&D organizations.