SEATTLE -- Parse Biosciences, a leading provider of accessible and scalable single cell sequencing solutions, announced that Tahoe Therapeutics has selected Parse’s GigaLab to generate data for its upcoming 300M cell project. Tahoe will use its proprietary Mosaic technology to generate samples consisting of 300M cells from large arrays of disease models, genetically or chemically perturbed. Under this agreement, Parse will apply its Evercode™ chemistry and high-throughput automation to these samples to deliver the largest perturbation-focused single cell dataset ever produced.

Parse’s GigaLab, designed specifically for million- to hundred-million-cell projects, has rapidly become an industry benchmark for large-scale, reproducible single cell data generation. The facility integrates high-capacity liquid handling, standardized workflows, and end-to-end QC to enable dataset sizes previously unattainable for most research organizations. The Tahoe project represents one of the largest sequencing initiatives undertaken at GigaLab to date and underscores the increasing industrial demand for massive single cell atlases capable of training modern AI systems.

“This collaboration demonstrates how scalable single cell technology can meet the demands of modern drug discovery,” said Charlie Roco, PhD, Chief Technology Officer and Co-founder at Parse Biosciences. “By combining our GigaLab platform with Tahoe’s perturbation engine, we are enabling a dataset that can power the next generation of AI models, changing how therapies are discovered.”

The 300-million-cell project expands Tahoe Therapeutics’ lead in building foundational perturbation datasets that capture how drugs, targets, and disease contexts interact across diverse biological systems. These high-dimensional datasets are made uniquely possible by Tahoe’s Mosaic platform and form the next-generation foundational datasets that power virtual cell models, enabling more accurate predictions of therapeutic response, mechanism of action, and patient variability.

Today’s drug discovery pipelines are constrained by datasets that lack drug discovery focused perturbations and biological diversity needed to train predictive AI systems. By contrast, Tahoe’s foundational datasets will incorporate:

· Multiple tissue types and disease states
· Thousands of compounds and genome-scale perturbations
· Pathway- and cell-type-specific signatures at unprecedented scale
· High-resolution views of mechanism, plasticity, and drug response

These features allow Tahoe to identify unexpected drug/cell interactions, uncover new biology, and explore therapeutic avenues that traditional in vitro systems often miss.

“Scaling single cell perturbation data is essential for building AI models that understand human biology,” said Johnny Yu, CSO of Tahoe Therapeutics. “Leveraging Parse’s GigaLab, we’re able to perform single cell sequencing on samples generated from our Mosaic technology at unprecedented depth and diversity, moving us closer to scale of foundational datasets that power our virtual cell models, which can predict therapeutic outcomes across patients and diseases.”

With this agreement, Parse and Tahoe together highlight a new reality in the life sciences: the next generation of therapeutic discovery requires data at a scale that only a small number of expert entities, equipped with highly automated, industrial-grade platforms, can produce.

By delivering sample preparation and sequencing for this dataset through its GigaLab, Parse continues to set the standard for what is technically feasible in large-scale single cell biology, while enabling innovators like Tahoe to build AI systems rooted in far richer biological context than was previously possible.