Data is the invisible bottleneck holding back AI-powered drug discovery. Here's how our integration with Benchling turns raw instrument output into actionable science — automatically.
Every scientist in biotech knows the feeling: you've just run a beautiful experiment, the robots did their job perfectly, and now you're spending the next three hours wrestling data out of a proprietary instrument format, formatting it in Excel, and manually dropping it into your ELN. Somewhere between the bench and the spreadsheet, the science gets lost.
That gap between where data is generated and where it becomes useful is what the Benchling and HighRes partnership is built to close.
THE REAL BOTTLENECK
Across the biotech and life sciences industries, the conversation has shifted decisively toward AI. Better molecule design, faster cycle times, increased productivity — the gains are real and well-documented. But as Benchling has observed in its own customer research, there's a less-discussed truth underneath all of it: none of those gains are possible without high-quality, contextualized, accessible data.
Large biopharma companies are already seeing the consequences. Benchling’s 2026 Biotech AI Report found that data volumes at major companies are growing at a staggering pace with the challenge only intensifying as automation and AI pipelines generate even more output.
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3× Year-over-year data growth at large biopharma |
18 hrs Avg. time per week scientists spend on data logistics |
61% Of large biopharma reporting that 3× data growth |
Eighteen hours a week. That's nearly half a scientist's working time spent fighting to get data off instruments, reformatting it, moving it between systems — time that could be spent doing actual science.
THE PARTNERSHIP
HighRes excels at what it was built for: orchestrating automated lab systems, scheduling complex workflows, and keeping sophisticated robotic platforms running smoothly. Benchling excels at capturing scientific context, managing research data, and increasingly, powering the analytical and AI layers that make that data meaningful.
Together, the integration creates something neither could offer alone: a continuous, automated pipeline from robot to insight.
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HOW THE INTEGRATION WORKS A scientist initiates an experiment from within Benchling. That request is automatically handed off to HighRes' Cellario OS™ platform, which schedules and executes the run on the robotic system. Once complete, the experimental data flows back into Benchling automatically. No manual export, no spreadsheet shuffling, no data re-entry. By the time a scientist returns to their desk, structured results, fitted models, heat maps, and charts are waiting in their notebook. |
A CLOSER LOOK
Here's what that looks like in practice, following a real ELISA workflow demonstrated live by Benchling (Video 1):
1. Experiment Setup in Benchling. A scientist designs an experiment and initiates a workflow in Benchling. A checklist enforces required human verification for safety-critical steps.
2. Automated Handoff to HighRes Cellario OS™. Benchling passes structured experiment parameters to Cellario OS via API, such as sample information, plate barcodes, layout, everything the experiment needs to get started on a workcell.
3. Robotic Execution via Cellario OS. HighRes schedules and runs the assay. Scientists can check in on progress within Cellario OS, but the system operates autonomously through completion.
4. Automatic Data Return. Results flow back into Benchling's Automation Designer automatically. A pre-configured data pipeline workflow, including concentration modeling, plate heat maps, curve fitting, and custom Python visualizations, runs without any human intervention.
5. Results in the Notebook. Everything lands directly in the scientist's original Benchling notebook: charts, fitted models, processed data, and all analytical outputs. Immutable, contextualized, and ready for the next decision.
THE FOUNDATION
The integration is made possible in part by a commitment to open data standards. Both HighRes and Benchling are designed to work with a wide range of instruments. Benchling instrument connectors normalize vendor formats into the Allotrope Simple Model (ASM), a JSON-based standard.
This matters for the long game. Proprietary formats come and go. When data is captured in an open, machine-readable standard, it remains useful for analysis, model training, and compliance for years to come — regardless of what happens to the original vendor software.
HighRes brings the same philosophy to lab automation. Our open API architecture and library of over 500 instrument drivers mean that robotic systems and analytical instruments from virtually any vendor can be connected, orchestrated, and integrated into a unified workflow, without proprietary lock-in or custom engineering for every new piece of equipment. Whether you’re running a liquid handler from one manufacturer alongside a plate reader from another, our drivers handle the translation layer so your data pipeline doesn’t have to. When Benchling and HighRes are connected, that openness compounds: instruments talk to robots, robots talk to data pipelines, and data pipelines talk to your scientists, all through open, documented interfaces built to last.
WHAT'S NEXT
The Design-Build-Test-Learn cycle is the heartbeat of modern drug discovery. But that loop only delivers value when it actually closes; when the lessons from one experiment are automatically available to inform the next one, without a human spending days cleaning and reformatting data in between.
The HighRes integration is a core part of making that vision real. When robots generate data that flows automatically into analytical and AI systems, the DBTL/DMTA loop stops being a metaphor and starts being infrastructure.
That infrastructure is here. If you're ready to stop fighting your data and start learning from it, we'd love to talk.
Register for our upcoming webinar to see the integration in action!
Learn more about Benchling.