SPT Labtech and Alithea Genomics partner to automate ultra sensitive single-cell RNA sequencing
SPT Labtech has partnered with Alithea Genomics to automate single-cell RNA sequencing workflows, combining the firefly liquid handling platform with Alithea’s FLASH-seq single-cell RNA-seq protocol.
The collaboration aims to make single-cell transcriptomics more scalable, reproducible and cost-efficient. Manual library preparation steps often limit throughput and introduce variability, but automation with firefly’s low-volume precision dispensing is designed to address those challenges. The integrated workflow is now available globally through both companies’ application support teams.
Single-cell transcriptomics is rapidly gaining importance in cell biology, immunology and drug discovery, but workflow complexity remains a barrier to widespread adoption. Alithea’s FLASH-seq protocol enables high gene detection sensitivity from ultra-low input samples, while firefly supports precision and modular scalability across a range of experimental designs.
Riccardo Dainese, chief executive officer and co-founder of Alithea Genomics, said: “Our mission has always been to make high-throughput and high-quality RNA-seq accessible and scalable for any lab. By combining FLASH-seq and Total DRUG-seq with SPT Labtech’s firefly, we’re removing key bottlenecks in library preparation workflows. This partnership simplifies complex processes, drives down costs, and empowers researchers to focus on discovery.”
SPT Labtech’s chief commercial officer Morten Frost added that the collaboration extends automation deeper into RNA workflows: “This collaboration represents a step toward broader automation of complex RNA workflows, supporting the growing integration of transcriptomics into translational and clinical research. Implementing this workflow on firefly, laboratories can achieve a new level of efficiency, reproducibility, and throughput.”
Both companies said the combined solution will help laboratories manage higher sample volumes while maintaining data quality and consistency, supporting the growing role of transcriptomics in drug discovery and development.




