He glances at the numbers scribbled on the back of his hand. Ethanol drips slowly over the faint black ink—his makeshift record of cell concentrations. Is that a 2 or a 5? he wonders. Probably a 5. It must be. He proceeds to seed his cells into fresh flasks. Walking out of the tissue culture room, he snaps off his purple gloves and tosses them—along with his data—toward inevitable incineration.

Back in the main lab, he sits at the bench, fingers drumming gently on the melamine worktop, pondering the morning’s remaining tasks. He opens the fridge, wincing at the familiar, acrid scent of stale agar and bacterial overgrowth.
Was it plate 4 I needed today? Maybe. But is this plate 4 the right plate 4? He holds it up to the light. It looks fresher than the others. Probably fine.

This might read like a scene from a sitcom—some tragicomic tale of scientific incompetence. But for many highly intelligent biological scientists, these scattered moments of confusion, born from poor record keeping, are all too familiar.

The key data scrawled on a tissue. The fungus-infected cell flask with no clue which media batch you used. The dusty PCR machine last validated when Northern blots were still cool.

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Biological research is complex—and messy—from the DNA up. Keeping track of everything is hard. Writing down every minor detail adds friction to already overloaded workflows, and so important fragments drift away, lost in the lab's ether. It’s a universal frustration. Managers groan. Scientists sigh. Yet we keep circling the same problem.

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At its core, the issue is this: it’s still often easier and quicker to record your data on a scrap of paper.  

And that’s where everything breaks down—where the link between a digital design and its physical realization dissolves. Where transferring handwritten notes into a database feels like double the work. Where bringing a laptop into a lab sends the health and safety officer into cardiac arrest.

But maybe—just maybe—things could be different.
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A Better Lab Workflow: A Vision

To quote Martin Luther King Jr., “I have a dream.” Mine may not be as profound as his, but it’s a dream worth having nonetheless.

It starts in the office. A cup of English Breakfast tea in one hand, my laptop waking from slumber. I open my lab management software and review my tasks for the day.  Scrolling through a plasmid design, I spot the exact site for a modification—a small tweak to my DNA. I turn to April, the highly capable (and, in my dreams, disarmingly attractive) scientist beside me.  "Got a reporter plasmid with GFP I can borrow?"

With a twinkle in her eye, she says, “Of course,” and shares it with two clicks.

Tea finished and plasmid cloning strategy ready, I walk into the lab—no laptop in tow. At my bench, I grab a tablet, load my cloning plan, and hit Start restriction digest. A pre-filled form pops up with all the right details—plasmid name, buffer type, enzyme volumes—everything I need.  Setup is faster. Accuracy is better. And five times more metadata is recorded, effortlessly.

A cascade of processes follows—restriction, ligation, transformation, plating, colony screening—all tracked, timestamped, and automatically linked to the right project. Everyone who needs access has it.

In parallel, I’m culturing cells. Passaging, freezing, infecting, testing. All logged using pre-configured forms. No calculators, no scribbled notes. Just clear, accurate records.

And then, inevitably, my dream turns dark.

Our professor demands answers. Why are April’s cells growing better than mine?
I shrug—no clue.

He runs a quick report, pulling standardized data from across our workflows. Turns out she’s been seeding 20% higher densities every time. Problem solved. Nightmare over.

Why We Built Lab Thread

I first imagined Lab Thread years ago, while running a biotech and struggling to track samples and data.  I tested every system out there. None were quite right.  Most were expensive, complex, and slow to deploy—testing them became a full-time job.  In the end, I patched together a Frankenstein mix of custom scripts and Microsoft tools. It worked, but it wasn’t elegant.

Lab Thread was born from that frustration.  Our goal? Make lab software:

• Easy to test
• Simple to implement
• Deep in capability

We hope you—and your team—feel that in every click.

Going Digital Is a Shift, But a Worthwhile One

Digital lab management isn’t about change for change’s sake. It’s about sanity. Accuracy. Efficiency.

Yes, transitioning means adapting workflows. Yes, there will be hiccups. But science is expensive. And getting it wrong is even more so.

When I see a server at a busy restaurant effortlessly taking complex, customized orders on a tablet, I wonder:
Can’t we do better in bioscience?

At Lab Thread, we think the answer is yes. We’ll try, fail a bit, and then try again—until we make digital lab work easier than paper.