In a webinar supported by Thermo Fisher Scientific, Steven Stone highlighted the crucial role of next-generation sequencing (NGS) in precision oncology. Noting operational challenges such as complex workflows and resource constraints, he discussed laboratory factors that can limit efficiency and scalability of NGS testing.
To demonstrate the interplay of these factors in the real world, Stone presented a study comparing two NGS workflows – amplicon-based NGS versus hybrid-capture – for analysis of the same set of solid tumor samples.
The study demonstrated tangible efficiency gains from redesigning workflows, showing where labs can cut bottlenecks without compromising quality. The amplicon-based Oncomine Dx Express Test was found to be more cost-effective and efficient than the other system, demonstrating labor savings and benefits of enhanced automation to the NGS workflow.
Meet the presenter
Stephen Stone, Managing Director at Argent Global Services, has over 25 years’ experience working in healthcare and diagnostic environments with emphasis on measuring and improving patient care pathways.
In 28 years with Argent, Stone has used his strong leadership and problem solving skills to provide clients with realistic solutions that have reduced costs and improved operations. He has been instrumental in developing many of Argent’s engineering and continuous improvement services for the healthcare industry, and has managed numerous projects in the manufacturing and supply chain sectors, providing world class processes to his customers’ operations.
Key learning objectives
Learn how NGS automation can reduce touchpoints, shorten turnaround time, and support sustainable scaling.
Gain an understanding of:
Hands-on time versus turnaround time: what actually changes when workflows are redesigned
How automation supports efficiency in precision oncology testing
Where labs can cut bottlenecks without compromising quality
Ways to optimize resources as testing volumes grow
NGS in precision oncology
By targeting treatments to patients who are most likely to benefit, precision oncology enables individualized care. With its potential to improve treatment effectiveness, the demand for precision oncology is rapidly increasing.
“As oncology testing demands grow, labs are under pressure to deliver accurate results faster, with fewer hands and tighter budgets,” warned Stone.
NGS is the primary method of testing used for precision oncology, and labs need to ensure their workflows are as efficient as possible to meet the rising demand.
Challenges in the NGS workflow
“Efficiency is about performing a task or function in the best possible manner with the least amount of wasted time, effort or resources,” said Stone. “It's about achieving the expected outputs with the fewest possible inputs.”
With the rising demands for NGS testing, laboratories face operational challenges – compounded by complex workflows, skilled labor requirements, and resource constraints – that can limit both efficiency and the scalability of testing.
It’s essential for labs to address factors affecting efficiency in NGS workflows, including numerous manual activities, separate steps, and lack of integration. Priorities should include:
Achieving the ideal balance of hands-on time and turnaround time
Using automation to support workflow efficiency
Identifying where bottlenecks can be eliminated without compromising quality
Optimizing resources to accommodate rising testing volumes.
Comparative assessment of NGS workflows
Argent partnered with the University of Pécs in a comparative study of two NGS systems: the Oncomine Dx Express Test amplicon-based NGS, and a hybrid-capture workflow. The study aimed to quantify workflow demands and assess the impact on efficiency and labor requirements in a real-world laboratory setting (1).
Argent Global Services Engineers shadowed members of the university’s laboratory team, conducting the study via direct observations and time-and-motion studies, documenting every step and resource utilized.
Stone explained, “During a week and a half in the laboratory, we observed routine work that was conducted by the actual laboratory staff, following their established SOPs for both workflows. We were doing real-world testing in their lab, with no influence on how the work was conducted.”
Each workflow was used to test the same set of six formalin-fixed, paraffin-embedded patient samples, plus one control.
Workflow details
The Oncomine Dx Express Test workflow involved automated steps for nucleic acid purification, library preparation, and sequencing, with analysis performed by the bioinformatics team (Figure 1).
Nucleic acid quantification on the Oncomine Dx Express Test is carried out as part of the purification step on the extraction and purification platform. However, in this study, the laboratory opted to repeat quantification using the same method and system used for the hybrid-capture workflow.
The hybrid-capture workflow included additional manual steps for quantification and library preparation, before being loaded onto the sequencing platform.
Study results
Total turnaround time
“Turnaround time was reduced by 62 hours with the Oncomine Dx Express Test,” reported Stone.
As shown in Figure 2, the Oncomine Dx Express Test turned around six samples in 26.8 hours, including 22.5 hours of hands-off, or walk-away time.
Running the same samples on the hybrid-capture system took 88.9 hours, including overnight idle periods and more than double the amount of attentive time compared with the Oncomine Dx Express Test.
Test timelines
The study developed a 24-hour timeline to understand the timing of testing activities for both workflows (Figure 3).
“We see that on Day One of the workflow for the Oncomine Dx Express Test, the automated sequencing system can be loaded roughly around 17:00,” explained Stone. “The technologists can go home for the day and the platform runs overnight. Around 10:00 the next morning, the results will become available for the bioinformatics team.”
“This results in a slightly over 24-hour processing time, and a two-day turnaround to get to results.”
He explained that, with the hybrid-capture system, the extraction and purification step ended at around 15:00 on Day One, not leaving enough time to start the manual quantification step required by the workflow. A period of idle time ensued until the step could be started at the beginning of Day Two.
The hybridization step ended at 23:00 on Day Two, followed by another idle, overnight period, until the manual library preparation on Day Three.
Sequencing ran overnight on Day Three, finishing around 23:00 on Day Four. The results were then picked up and processed on Day Five, after another idle period.
“With the hybrid-capture workflow, we needed a five-day turnaround to get to results,” concluded Stone.
Hands-on time and attentive labor
The hybrid-capture workflow required 451 minutes hands-on time, whereas the Oncomine Dx Express Test required only 41 minutes (Figure 4).
“That’s a 91 percent reduction in hands-on time with the Oncomine Dx Express Test,” said Stone.
Attentive labor – defined as all labor or waiting time for which the technician had to be present – was reduced by 61 percent with the Oncomine Dx Express Test (260 minutes) compared with the hybrid-capture workflow (661 minutes).
“Importantly, the key steps of library preparation and sequencing showed a 77 percent reduction in attentive labor time with the Oncomine Dx Express Test,” concluded Stone.
Manual pipetting events and bench setup
Stone discussed the number of manual pipetting events required for each workflow, explaining, “Rather than counting the number of pipette tips, which would be a much higher count, we recorded the actual number of manual pipetting motions.”
While the hybrid-capture workflow required 537 manual pipetting events for the library preparation and sequencing, the Oncomine Dx Express Test involved only 57 events for the same steps (Figure 5).
The study also observed the number of times technicians had to move from their benches to restock consumables between steps.
“The Oncomine Dx Express Test required bench resets three times, while the hybrid-capture workflow required seven times,” Stone reported.
The study also observed the number of times technicians had to retrieve and return reagents, with the Oncomine Dx Express Test requiring three trips and the hybrid-capture workflow requiring 29.
Lab design and modeling costs
Stone highlighted the impact of traditional lab design on NGS efficiency, with compartmentalized rooms and benches creating barriers and congestion. ”The study showed that manual workflows, with multiple steps and bench changes, are most impacted by lab design, with many more hindrances,” he said.
The study also modeled different batch sizes to understand the impact on labor costs and efficiency. “From our six-sample study, we were able to model different batch sizes by applying fixed and variable times to the protocols and the SOPs for the two different workflows,” Stone explained.
First the model was applied to attentive time for the workflows including only the manufacturer’s required steps – removing the manual quantification from the Oncomine Dx Express Test, and the bioinformatics time from both workflows.
Attentive labor time totaled 615 minutes for the hybrid-capture workflow and 184 minutes for the Oncomine Dx Express Test – a difference of 431 minutes.
Annual labor costs and full-time equivalents were modeled for both workflows, showing the Oncomine Dx Express Test to be more cost-effective, driven primarily by reductions in hands-on and attentive time.
Conclusions and key takeaways
Stone summarized the study's findings, saying, “The results of the study showed that the Oncomine Dx Express Test requires significantly less labor and overall cycle time to prepare and sequence patient samples, and provides a much faster overall analytical turnaround time.”
He emphasized the advantages of the enhanced automation in the Oncomine Dx Express Test, which increased efficiency throughout the workflow, compared with the hybrid-capture method, and reduced opportunities for errors, delays, and waste.
“Automation simplified the workflow and reduced the impact of lab design and other barriers,” he said, “which could provide a valuable route into NGS for resource-strapped, community-based hospitals.”
The key takeaways were:
Effective implementation of genomic profiling is critical so that patients can benefit from precision oncology.
Complex workflows, skilled labor requirements, and resource constraints limit efficiency and scalability of NGS, and remain key barriers.
An automated NGS assay, such as the Oncomine Dx Express Test, can help remove these barriers by reducing labor requirements, simplifying the workflow, and removing bottlenecks.
In conclusion, the presentation demonstrated that automating NGS can greatly improve diagnostic turnaround times in oncology, providing scalability via measurable workflow efficiencies.
For In Vitro Diagnostic Use.
PMR-001419
Watch the full webinar here:
Event Summary - How to increase efficiency in Routine Oncology NGS Workflows - The Pathologist
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References
- S Stone et al., “Results of a time and motion study of two next-generation sequencing workflows in a routine oncology biomarker profiling setting,” Poster G066, presented at the Association of Molecular Pathology Annual Meeting (2025).
