Catharine Aquino’s Post

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Group Leader Genomics Analytics at the Functional Genomics Center Zurich, ETH Zürich and the University of Zürich

There’s a lot of hype around Roche SBX pre-AGBT, largely driven by social media. After learning more, here are my thoughts. Take note that I’m approaching this as a genomics technologist focused on operations and implementation. The key questions I asked (and my SB would surely want to know 😅): What value does it bring? What unmet needs does it address? How stable will it be? Do we really need an instrument with these specs? Which research projects will benefit? Which workflows will it replace? SBX’s biggest strength is scalability and speed. The dream has been a machine functioning as both a small sequencer and a high-output system. That said, SBX is not portable—it’s two large boxes. Generating billions of reads quickly sounds great, but NovaSeq X is also fast, and we’re already struggling with data transfer and demultiplexing (DMX) taking longer than the run. Speed is useless if IT can’t handle it. The tech seems over-engineered (impressive but still...), making me skeptical about real-world robustness. Broad got good data fast, but the Broad is not an average lab. Illumina’s success came from reliability. I saw firsthand how the HiSeq 2000 outperformed SoLiD, 454, and Ion Torrent because it was simply easier to use. Sequencing platforms win or lose in the lab, not on paper. The silent determinant of an instrument’s success is the wet lab experience. No matter how good the chemistry sounds, SBX sounds complicated. I suspect SBX will struggle with complex samples beyond cDNA, human WGS, and 10X libraries. This reminds me of PacBio—it works well but has stringent sample requirements. Is 1,000+ bases long enough? Better than PE150, but NovaSeq X can now do PE300. What can SBX do that we can’t already do? We still need long-read sequencers. Mid-length reads don’t change the game—they’re just another option. For new applications, Constellation is more exciting than SBX, with potential in structural variants, methylation and DNA interactions. Based on AGBT trends, my fearless forecast is SBX will take at least two years to hit the market. Would I consider it if it weren’t from Roche? Probably not. But Roche has the resources to refine it, so I’m watching. If I had to buy an instrument today—factoring in all the roadmaps I’ve seen this week and assuming limited resources—I’d still buy a NovaSeq X 😅. PS. Waiting for my flight back home. Nothing else to do other than reflect about the past week #agbt25

Catharine Aquino

Group Leader Genomics Analytics at the Functional Genomics Center Zurich, ETH Zürich and the University of Zürich

1w

Also, I don’t think it will be a budget friendly option. They spent billions developing it! Also, Swiss products are never budget friendly ! 😂

Giles Hall

Principal Software Engineer at Broad Institute of MIT and Harvard

1w

Catharine Aquino I remember when our core lab at DFCI got its first SoLID sequencer—I thought colorspace sequencing might have an edge in somatic applications, but that never really materialized. In your analysis, you don’t mention structural variants (SVs). I believe SBX has an advantage in resolving long SVs when considering cost, fidelity, and turnaround time. What’s your take on that?

Seth Gergel, MBA

Finance Business Partner at Roche

1w

Valid points but in terms of market success , must consider Illumina lost over another billion dollars in 2024 as well as 2023. Almost no growth projected for 2025 so what does success really look like?

Griffin White

Technology-Focused Founder

1w

At least the hype lets me get a deeper $ILMN position for a better price 😎

Lester Poon

Precision Oncology. Health IT.

1w

Thanks Catharine. Could you share your biggest challenges? And what are the biggest challenges for your customers? I think you already mentioned one about the IT bottleneck. Can I assume that the DRAGEN pipeline solves that problem for you if it was implemented by your IT team?

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Mohammed Kanchwala

Senior Bioinformatics Scientist | Genomics Data Analytics | Cloud & HPC Pipeline Engineering | Nextflow | ML & AI in Life Sciences

1w

Catharine Aquino Start using Dragen for demultiplexing.

Jack Beierle

Chief Scientific Officer, Consultant

1w

Good thoughts, Catharine Aquino. There’s a consistent over focus on whole genomes, Q scores and coverage in these early releases and those metrics just don’t extrapolate to the majority of practical day-to-day sequencing that most labs I work with are familiar with and care about. These practical insights are key IMO. I also love your comments about use and robustness. Some people didn’t appreciate how helpful it was for early ILMN users to just avoid emulsion PCR in sample prep and clustering. The early data from Roche is compelling but the execution will be key.

Rachid Ounit, Ph.D.

Genomics | Research | Machine Learning | Biotech Innovation

1w

“Speed is useless if IT can’t handle it.” That’s a good reminder that the infrastructure should fit the instrument, and the instrument the infrastructure.

Peter Riccelli, Ph.D.

life sciences and biotech professional with extensive experience in pre-clinical, translational, and clinical molecular diagnostics industry and precision medicine

1w

My sense is that considering that Roche played the long game and allowed this technology development program to carry on and succeed, i think they are allowing the scientists and engineers to enjoy the success and accolades now, and lets face it, they deserve it but, i agree with you, and if roche wants to compete, they will have to address all your points, especially if they want to go clinical, where workflow, access, sample needs and cost per sample are key

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