Scientific discovery is perceived to be a singular, lone endeavor. The sole committed scientist toiling away in the laboratory into the middle of the night striving relentlessly towards a noble mission. To some extent, this vision is somewhat accurate: the ‘Eureka’ moment is the result of intelligent, hard-working scientists who are committed to a sole purpose. However, often ignored in this story is the network of people and providers that make the R&D machine work.
Defining the R&D ecosystem
At TetraScience, we believe that the best way to describe this collection of people and providers is ecosystem. Ultimately, the core of any scientific endeavor is people.
Scientists use instruments to produce data and advance our understanding of the natural world. Lab managers ensure laboratory infrastructure operates efficiently and optimally. R&D IT managers support systems for managing ever-increasing amounts of data.
Problems within R&D ecosystems
These constituents work towards a common mission - advancing science. However, they struggle with disparate workflows that lack real-time visibility into the laboratory. A scientist has to babysit their experiment in-person to prevent errors. A lab manager has little visibility of instrument usage and servicing requirements. R&D IT fights with software to accommodate new types of experimentation.
All of these problems are interrelated.
The problem is that the ecosystem is disconnected. The experiment doesn’t enable remote monitoring, lab managers can’t see instrument utilization, and R&D IT lacks a customizable software platform.
How to fix a fragmented ecosystem
Today it is still customary for organizations to deploy individual point-solutions for each separate challenge within the ecosystem. Instead of unifying people and systems, they are pushed further into specialized technology silos.
A superior approach to improving the ecosystem is to solve R&D problems holistically. With TetraScience, researchers can digitize and automate their experiments, lab managers can view their entire equipment fleet, and R&D IT can use a single set of APIs for data integration.
Ultimately, by uniting the fragmented ecosystem, personnel across the laboratory can more efficiently move the forefront of innovation forward.