The Data Bottleneck That Was Slowing Drug Discovery—And How They Fixed It

The Data Bottleneck That Was Slowing Drug Discovery—And How They Fixed It
Post by
Basiic Maill iicon

Let’s call him Dr. James—one of the lead researchers at a fast-growing RNA therapeutics startup. Like many scientists, he wasn’t just working against time; he was battling inefficiencies that slowed research and delayed insights.

Every experiment generated a flood of Surface Plasmon Resonance (SPR) data from Biacore 8K and ProteOn XPR36 instruments. But instead of analyzing results, James and his team were stuck in a cycle of exporting, formatting, and uploading data manually.

Every small error meant delays. Every delay slowed discoveries. And worst of all? Their in-house bioinformatics platform was rigid—any workflow tweak required developer support. A simple change? A week-long wait.

James wasn’t just struggling with data. He was struggling to move research forward.

The Breaking Point

One night, staring at another spreadsheet filled with raw data, James finally asked himself:

  • Why are we still doing this manually?
  • How much time are we wasting on non-research tasks?
  • What could we achieve if this process wasn’t holding us back?

Something had to change.

The Turning Point: Automation with Scispot

When the team implemented Scispot, everything shifted. Scientists like James could finally control their workflows—without waiting on developers.

And it wasn’t just about control. Automated data processing transformed their entire research operation:

✅ SPR data ingestion was fully automated—no more manual exports.
✅ Data flowed seamlessly through Jupyter Hub—eliminating reformatting headaches.
✅ Structured data was instantly uploaded to CDD—error-free and ready for analysis.

For the first time, James and his team weren’t waiting. They were leading.

The Results: Speed, Scale, and Scientific Freedom

The impact was immediate:

  • 50% Faster Data Processing – SPR data analysis time was cut in half.
  • 3x Experiment Capacity – The team processed three times more data without extra effort.
  • Full Workflow Control – Scientists adjusted workflows in real-time—no coding required.

From Stagnation to Acceleration

Today, James and his team no longer see data as a bottleneck—it’s a fuel for discovery. The question isn’t whether they can keep up with their data, but how fast they can push the next breakthrough.

How much time is your team wasting? What could you achieve if your scientists focused on research instead of spreadsheets?

Scispot improved our data workflows. Our scientists can now adjust workflows without waiting on developers, drastically cutting the time from data collection to actionable insights.
- R&D IT Director, Leading RNA Therapeutics Startup

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