Novome Biotechnologies

At Novome, our success as a science-driven company is inherently linked to our ability to extract insights from the experimental data we generate. As a result, we strive to build platforms that allow our researchers to go from raw data to insights as efficiently and reproducibly as possible while maintaining accessibility and transparency across the organization as we scale. Ultimately, we want to empower researchers to be limited not by the tools at their disposal, but by their imagination to ask questions of their data.

Towards this goal, we started a concerted effort to bring Python and Data Science tools into our analytics ecosystem a few years ago. We recognized that while Python-driven analysis workflows were an extremely powerful paradigm, they created a high barrier to entry since users needed to know how to code. We’ve made some solid progress despite this learning curve by combining low/no-code solutions and our in-house data capture and analytics system, but we often found that key results would get “stuck” in notebooks.

This would lead to insight silos where key stakeholders from different R&D teams (or even outside of R&D all-together) would find it difficult to observe, track, and act upon metrics of interest.

So we set off to find a platform that could provide two key features:

1. An enterprise-level Data Science platform that was accessible and easy to maintain

2. A dashboarding framework for rapidly prototyping and deploying data applications

Of all the solutions we explored, Hex struck this exquisite balance of providing the technical flexibility you’d want as a data scientist with low technical overhead for effortlessly publishing interactive apps across our organization at just the click of a button. The two of these combined really make it a magical tool for us to go from prototype to deployment quickly.

We’ve truly been amazed at the progress we’ve made within our first few months of adopting Hex. We’ve used Hex to build interactive dashboards to communicate the results of our Phase I clinical trial (taking just a few days from prototype to deployment), demonstrate the productivity of our operations teams, and track the status of R&D projects and experiments.

This progress has been driven by several key features of Hex: (1) low overhead for onboarding the platform and connecting to our data sources, (2) flexible and intuitive framework for combining code and UI elements as part of a dashboard, and (3) streamlined deployment process (literally just a button click!).