BD and Opentrons Partner to Automate Single-Cell Multiomics Research for Drug Development
核心洞察
BD (搜索) and Opentrons announced a multi-year collaboration to integrate robotic liquid-handling capabilities into BD single-cell multiomics instruments, automating critical experimental steps to accelerate disease research and drug development.
The partnership will integrate the BD Rhapsody System (搜索) with the Opentrons Flex (搜索) platform and develop verified protocols for hands-free single-cell multiomics workflows.
A key component involves developing an automation-compatible module for the BD Rhapsody System (搜索) to automate next-generation sequencing library preparation and cell capture steps.
BD (搜索) (Becton, Dickinson and Company) and Opentrons Labworks (搜索) have announced a multi-year collaboration to integrate robotic automation into single-cell multiomics research, a move that could significantly accelerate drug development and disease research capabilities across the pharmaceutical industry.
The partnership combines BD (搜索)'s expertise in single-cell multiomics instruments with Opentrons' robotic liquid-handling technology, which has been deployed in more than 10,000 systems worldwide. Together, the companies will automate critical experimental steps that have traditionally required manual intervention, potentially transforming how researchers conduct large-scale cellular analysis.
Automation Integration Strategy
The collaboration centers on integrating the BD Rhapsody System (搜索) with the Opentrons Flex (搜索) platform, creating verified protocols that enable hands-free workflows for single-cell multiomics experiments. This integration addresses a key bottleneck in current research methodologies, where manual processes limit both speed and reproducibility.
"By revealing the multiple layers of biological information within cells, the field of single-cell multiomics is quickly transforming research in oncology (搜索), immunology (搜索) and beyond – and automation can further accelerate adoption especially in translational and biopharma settings," said Ranga Partha, PhD, VP/GM of Global Marketing and Strategic Growth Areas at BD (搜索) Biosciences.
A cornerstone of the partnership involves developing an automation-compatible module for the BD Rhapsody System (搜索) that will enable automated next-generation sequencing library preparation and cell capture. This development could eliminate manual handling errors and increase throughput for researchers conducting million-cell studies using instruments like the BD Rhapsody HT Xpress System (搜索).
Industry Impact and Accessibility
The collaboration aims to democratize access to advanced single-cell sequencing technologies across research settings. James Atwood, PhD, CEO of Opentrons Labworks (搜索), emphasized the partnership's potential to reduce costs and complexity: "This collaboration brings together the long-standing expertise of BD (搜索) in the field of single-cell multiomics with the flexible and open automation ecosystem of Opentrons. By combining our hardware platforms, we are making it easier and more cost-effective for labs everywhere, across basic and translational research, to perform cutting-edge single-cell sequencing at scale."
Opentrons currently serves laboratories at the top 20 academic universities in the United States and 14 of 15 leading global biopharmaceutical companies, indicating the broad potential reach of this collaboration. The company has achieved unicorn status with over $200 million in funding, reflecting strong market confidence in lab automation technologies.
Implementation Timeline
Early access opportunities for interested laboratories will be available soon, with both companies planning to showcase the collaboration at the American Society of Human Genetics Annual Meeting in Boston from October 14-18, 2025. The companies will be present at Booth 635 (Opentrons) and Booth 447 (BD (搜索)) during the conference.
The integration of robotic automation into single-cell multiomics represents a significant step toward scaling cellular analysis capabilities, potentially enabling researchers to process larger sample sizes with greater consistency and reduced labor requirements. This advancement could prove particularly valuable for pharmaceutical companies conducting drug discovery research and translational studies requiring high-throughput cellular characterization.