Automated pipetting powers world’s largest single-cell atlas
The Tahoe Therapeutics team. Credit: Tahoe

Pipettes

Automated pipetting powers world’s largest single-cell atlas

17 Feb, 2026

Tahoe Therapeutics – a biotech start-up based in San Francisco, California – is creating the largest ever atlas of cell-chemical interactions to inform drug discovery. Combining automated pipetting systems from Integra Biosciences with Parse Biosciences’ Evercode™ single-cell RNA sequencing (scRNA-seq) products, and its own proprietary AI algorithms, the company already has several drug discovery programs running in parallel across multiple cancer types, and is expanding into other therapeutic areas.

Workflow automation is essential for the Tahoe Therapeutics team’s aim of generating some of the largest scRNA-seq datasets in the world. The company invested in an ASSIST PLUS pipetting robot with VIAFLO handheld electronic pipette to automate its research workflows. Integra’s partnership with Parse Biosciences means these tools work seamlessly with the Evercode products to provide a validated, turnkey solution covering every stage of scRNA-seq sample preparation. These tools enable the company to scale up its operations while improving reliability and reducing hands-on time by up to 75 percent.

The company aims to use the speed and accuracy of these automated systems to generate a dataset fifty times larger than its already record-breaking Tahoe 100 million single-cell atlas. Johnny Yu, Co-founder and Chief Scientific Officer at Tahoe Therapeutics, explained: “We quickly realised that, as we were generating more and more data and pushing the limits of the field, we were missing robotic and high throughput solutions. Automation with the ASSIST PLUS has increased our throughput for single-cell preparation more than 5-fold. The most important thing is that it’s highly accurate: you’re not relying on the inherent variability of manual processing. The combination of Integra’s instruments and Parse Biosciences’ kits allows us to leapfrog many biopharmaceutical companies and generate larger datasets using less instrumentation, reagents and capital.”

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