Solutions for the Molecular Lab

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.