The biggest opportunity in your lab is everything upstream of the sequencer.
Your real cost per sample is set by everything that happens before a single read is generated. I help molecular and genomics labs find the variables that constrain profitability and scale — and address them quickly, so the science can move forward.
Those compromises live upstream of the sequencer. Each is rational in the moment — together they compound, and as labs face mounting pressure to deliver cutting-edge testing at a viable cost per sample, they quietly cap the one thing that matters most: the ability to scale profitably.
12 years across every layer of the molecular workflow. Vendor-neutral — no referral fees, no implementation revenue. Diagnosis before you commit.
The next unlock in the unit economics of genomics lies upstream of the sequencer.
For fifteen years the industry drove down the cost of sequencing — first through chemistry, then through dry-lab automation. The largest gain still on the table isn’t in either: it’s everything that happens before a single read is generated.
I’ve watched the impact of this throughout my career — labs regressing to send-out testing when the unit economics stopped working, technology implementations stalling for months, and in some cases labs closing their doors. The cause usually isn’t the technology itself; it’s an operations problem. E2E sample tracking held together by a spreadsheet, manual data entry between systems, overlapping system boundaries, custom code force-fitting platforms into work they were never designed for, a standing reliance on professional services — all of this drives the cost per sample/read well above what anyone estimated.
Three things drive it:
- Procurement requirements that were never properly scoped — the lab wrote a spec based on the need for one component and didn’t model how that component fits into their E2E workflow, both today and in the future.
- A workflow and total cost of ownership nobody modeled at the process level — high-level estimates leave out the nuance of a fully burdened cost analysis.
- Molecular labs are highly variable and constantly changing — which often results in custom code and shadow systems to fill the gap between system capability and operational needs.
Nobody chose these intentionally. They accumulate quietly — and compound until they choke a lab’s ability to grow and erode its profitability.
I spent 12 years at every layer of the molecular workflow working to support the wet lab, and in the process developed a deep passion for the work labs do. Unusually, I had the opportunity to hold product responsibility for most of it at once — not as a bench scientist or a software engineer, but as the person who had to make the whole system make sense. I’m excited to bring that experience to HelixWrks.
Two ways to close the gap.
Advisory — bring me in
Fixed-scope, outcomes-not-hours engagements that diagnose the gap and de-risk the decision — before you commit. We work the problem together, and the deliverables are yours to keep.
Explore Advisory →HelixWrks Lab
The same thinking, productized into self-serve tools. The LIMS Readiness Assessment scores your implementation readiness across 10 domains; BenchForge models your lab’s unit economics so you can prove a change pays before you spend. Alpha members get first access and a hand in what ships next.
Explore HelixWrks Lab →
Featured thinking
Three featured articles. The full library — including interactive frameworks — lives on the Content & Resources page.
Why LIMS Implementations Fail
Six patterns that play out repeatedly across genomics, molecular diagnostics, and clinical lab environments. The culprit is almost never the technology.
Read →Laboratory Technical Debt
High-throughput platforms sitting well below capacity. Leadership won’t approve expansion. The overhead per sample makes growth uneconomical. How technical debt accumulates — and the path out.
Read →End-to-End Workflow Strategy in Clinical Labs
How to right-size your E2E architecture for your stage of growth, find your rate-limiting steps before you buy anything, and reframe your lab as a profit center.
Read →