High-quality sample preparation underpins every molecular workflow, determining whether downstream analyses accurately reflect biological reality. Laboratories now demand workflows that go beyond yield, emphasizing consistency, traceability, and the ability to handle challenging sample types. Automation plays a pivotal role by standardizing processes and supporting both high-throughput and smaller-scale operations.
Michael Scheffler, PhD
Vice President Head of Global Sample Technologies
QIAGEN
In this Innovation Spotlight, Michael Scheffler, the vice president and head of Global Sample Technologies at QIAGEN, discusses how automation is helping researchers meet modern expectations by minimizing variability and streamlining operations. The result is a shift toward more standardized and scalable approaches for generating dependable molecular insights.
Why is high-quality sample preparation so critical for generating reliable molecular insights?
It is the first and most essential step in many molecular workflows, and it sets the foundation for everything that follows. When extraction and cleanup are robust, reliable, and reproducible, the nucleic acids entering PCR, digital PCR, or NGS truly reflect the biology of the sample rather than technical variability. Any inconsistency introduced at this stage can reduce sensitivity, distort quantification, and complicate interpretation. So, reliable sample prep is fundamental for generating dependable molecular insights.
Over time, how have you seen expectations around sample preparation change in both research and clinical laboratories?
Over the last decade, expectations have moved beyond simply getting enough DNA or RNA. Research and clinical labs increasingly expect standardized workflows that deliver consistent performance, along with stronger requirements for traceability, especially as molecular methods shift into more routine and regulated settings. At the same time, sample types and downstream applications have become more demanding, including liquid biopsy and advanced NGS, which pushes sample prep to handle inhibitor-rich and otherwise challenging specimens with high reproducibility.
How is automation transforming sample preparation in terms of reproducibility, efficiency, and scalability?
Automation is transforming sample preparation by reducing operator-to-operator variability and making workflows more standardized, traceable, and reproducible. It also improves efficiency by freeing up valuable hands-on time, either for scientists who want more time for interpretation and experimental design or for laboratories that need to increase throughput and operational efficiency. Importantly, automation can serve both ends of the spectrum, supporting high-volume labs processing thousands of samples per day and smaller labs where simple “load and go” operation helps avoid non-routine errors.
What are the most common challenges to adopting automation in the lab, and how can they be addressed?
A common challenge is finding the right fit between a lab’s real-world needs and the perceived complexity or investment of automation. Throughput requirements can vary dramatically, from a few samples per week to thousands per day, and if a workflow is not routine, usability becomes just as important as performance. These barriers are best addressed with automation that is reliable and straightforward to operate, offered across different throughput tiers, and supported with clear implementation guidance while still supporting customers who choose to remain manual for specific applications.
How is QIAGEN meeting the changing needs of both large and small molecular biology and clinical labs?
QIAGEN is evolving to support the shift toward automation while maintaining the quality and breadth that customers associate with our Sample Technologies foundation. We’re bringing three new automation launches in 2026 that cover distinct needs: QIAsprint Connect as a high-throughput platform for routine testing and biopharma, QIAsymphony Connect as a trusted platform for liquid biopsy workflows with improved connectivity and traceability, and QIAmini as an attractive entry model for smaller labs. In parallel, we continue to fully support manual kits because many laboratories will keep a mix of manual and automated workflows.
QIAGEN recently showcased the QIAsymphony Connect platform. How does this system support emerging oncology workflows and what makes it stand out?
Oncology often pushes sample prep to its limits because the material can be scarce, fragmented, or mixed with inhibitors, and the signals you need to detect can be extremely low. Workflows frequently involve preserved tumor tissue, such as formalin-fixed paraffin-embedded and circulating cell-free DNA (cfDNA) from blood in liquid biopsies, and each has different technical constraints. As oncology expands into therapy selection, minimal residual disease and relapse monitoring, and early cancer detection, sample preparation must deliver highly reproducible yield and purity with tight traceability to support sensitive downstream analysis.
QIAsymphony Connect supports emerging oncology workflows, especially for liquid biopsy analysis, by combining widely trusted cfDNA chemistry with a next-generation, connected automation experience. It can deliver more than a 50 percent throughput increase for certain liquid biopsy protocols and strengthens end-to-end process confidence through improved automated traceability using 2D barcodes for both samples and eluates. With early access having started in October and full commercialization on track for mid-2026, it is designed to help labs scale sensitive oncology testing while maintaining consistency and control.
