Kelly Parliament, staff application scientist at Beckman Coulter Life Sciences, discusses how automation is improving the efficiency of single-cell transcriptomic workflows.
Single-cell transcriptomics is rapidly evolving from a niche research tool to a cornerstone of biomedical innovation. That’s because this emerging technology is a major step up from traditional RNA sequencing, which averages gene expression across a population of cells. Single-cell transcriptomics provides a much more detailed view of cellular heterogeneity, enabling researchers to uncover the unique characteristics and behaviours of individual cells within complex tissues – insights that might otherwise be masked in bulk analyses. This promises to drive breakthroughs in cancer, immunology, cell and gene therapy (CGT) and more.
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The increasing demand for single-cell transcriptomic technologies is raising plenty of challenges, however. Traditional single-cell workflows require laborious manual processes that make it difficult for researchers to handle more than 24 samples per day. To improve the efficiency and accessibility of single-cell transcriptomics for researchers across the biopharmaceutical development spectrum, industry players must collaborate to develop scalable, high-throughput solutions that simplify workflows and accelerate turnaround times.
With those goals in mind, Beckman Coulter Life Sciences and 10x Genomics have been collaborating since 2023 to improve single-cell gene expression workflows with automation. Our goal is to automate manual processes such as library preparation, and to do so in ways that are as consistent and robust as what is traditionally achieved with manual processes. Our experience working with Single Cell Discoveries (SCD) B.V., a contract research organisation (CRO) specialising in single-cell sequencing, demonstrates how automation can improve single-cell transcriptomic workflows.
Automating library preparation
For traditional single-cell transcriptomic workflows, library preparation requires precise manual processes and reagents that must be kept at stable temperatures to ensure consistent results. Running just 24 samples per day can significantly delay large projects. Improving the efficiency of single-cell transcriptomic workflows with automation reduces hands-on time, freeing up researchers to spend more time analysing their results and significantly accelerating project completion.
As SCD’s customers began requesting larger sample sizes, the CRO sought technology that would allow it to run more than 24 samples per day while maintaining a turnaround time of four to six weeks. To reach that goal, SCD worked with Beckman Coulter Life Sciences and 10x Genomics to automate library preparation, with the goal of being able to process up to 96 samples per day.
SCD opted for a system that automates library preparation with flexible pipetting and workflow management. The system allows for single- and dual-arm configurations with multichannel heads and Span-8 pipetting. This allows for pipetting with different types of labware at varying volumes and the freedom to pipette the precise number of samples that need to be analysed, rather than full plates. An integrated cooler helps modulate temperatures throughout the workflow.
“In addition to running three times as many samples per day as it could with manual library preparation, SCD has seen the hands-on time for lab scientists plummet from more than five hours to one hour”, said Michiel Fokkelman, PhD, automation scientist for SCD, during a webinar in May 2025. Another big advantage of automating single-cell transcriptomic workflows is a reduction in errors, Fokkelman added.
“We do see less variability in the data,” he said. “Robots typically don’t make pipetting mistakes, whereas a human, of course, could potentially make mistakes. So we get a lot of standardisation in the workflow and a lot more consistency in the final product.”
The future of single-cell research
Automation will continue to improve single-cell workflows. Technology developers are working on automating other processes, including cDNA synthesis and cell-surface protein assays. Another rapidly advancing area is Variable Diversity Joining (VDJ) profiling, which allows researchers to analyse immune cells – T and B cells – at the single-cell level. Increased automation of these processes improves traceability and consistency across sample sets, reducing the need for researchers to replicate experiments multiple times.
The granular detail uncovered by research focused on single-cell transcriptomics will ultimately benefit patients. Improving the ability of researchers to understand T and B cell activity could result in more effective immunotherapies for cancer and other diseases. In drug development, single-cell transcriptomics is revealing new details about how medicines affect all the diverse cells of the body, uncovering insights into the mechanism of action, side effects and more.
With increased automation, single-cell transcriptomics is rapidly evolving into an invaluable tool for understanding the complexity of human cells. This technology is on a similar trajectory as next-generation sequencing, moving from the realm of specialised labs to the mainstream of biomedical research. Collaborations between CROs, technology developers and biopharmaceutical innovators will continue to move single-cell transcriptomics forward, helping researchers answer questions they couldn’t before, with more clarity and reproducible results.
