A medicinal chemist finishes a promising batch and needs three things: a solubility assay, a screening run, and — for a new scaffold — a docking analysis from the comp chem group. She emails the biology team about the assay. She walks the vials down the hall and hands them to whoever’s at the bench. She pings the comp chem lead on Slack about the docking run. Three requests, three channels, zero tracking.
Two weeks later she’s sending “any update?” to three different people. One assay is finished, but the results are sitting in someone’s inbox. The vials are in a fridge behind an unlabeled rack. The docking request got buried under a conference deadline. Nothing failed, exactly. It just quietly dissolved.
Now multiply that by every scientist in the building.
Emails, samples, and results scatter across a dozen channels — and vanish into the request black hole.
The gap nobody owns
Requests are the connective tissue of research. Samples move between teams. Analyses get handed off. Work goes out to CROs and comes back. Every one of those handoffs is a request that someone made and someone else has to fulfill — and in most organizations, no single system owns them. They live in inboxes, in Slack threads, in a spreadsheet one person maintains and three people ignore. Which means the answer to “where is this and who has it?” is almost always a shrug.
The false choice
Faced with that chaos, teams tend to believe they have two options. Option one: keep limping along with email and spreadsheets — cheap, familiar, and completely blind the moment volume picks up. Option two: buy a full LIMS.
A LIMS is the right call for regulated, high-volume sample management, and when that’s what you need, nothing else will do. But standing one up is a serious commitment — six-figure implementations and multi-month rollouts are the norm, and enterprise systems are frequently overkill for a smaller or narrower scope. Here’s the part that gets missed: a lot of what sends teams shopping for a LIMS isn’t actually a LIMS problem. It’s a request-and-tracking problem wearing a LIMS-shaped costume.
Why the generic tools don’t fit either
The obvious next thought is, “we already have a ticketing tool — can’t we just use that?” You can try. But Jira, Asana, and their cousins were built for software tickets, not science. They don’t know what a sample is. They can’t link a request to a registered compound. They don’t speak assay, don’t track chain-of-custody for a physical vial, and don’t talk to your registration or assay databases. You end up with a status board that’s disconnected from every system that actually holds your data.
It’s not a LIMS problem. It’s a tracking problem.
The question was never “LIMS or no LIMS.” It’s “what does this workflow actually require?” And for a huge share of scientific handoffs, the honest answer is: a structured way to submit a request, route it to the right person or team, watch its status, and close it out — connected to the systems of record you already have. That’s a right-sizing decision, not a compromise.
A layer built for how requests actually move
That’s exactly the gap Workflow Request and Tracking (WRT) is built to fill. Scientists submit requests through configurable forms; the request gets assigned and routed — to an internal resource, an assay, or an external CRO — and everyone can see where it stands from intake to completion. When the request involves samples, you get sample tracking. When it’s a docking analysis, a data-visualization build, or any other ask, you get the same submit-assign-track-close backbone without pretending a sample is involved.
Because WRT is configured and deployed into your environment rather than bolted on as one more SaaS silo, it integrates with the chemical registration and assay databases you already run — so the request board and your real data finally speak to each other. And if you do already have a LIMS, WRT isn’t a rival to it: it can sit alongside it as the request-and-routing layer, and pick up all the non-sample work a LIMS was never meant to handle.
Right-size the tool
The teams that get this right aren’t the ones who spend the most or the least. They’re the ones who match the tool to the actual shape of the work. If your requests are disappearing into inboxes and fridges, the fix probably isn’t a bigger platform — it’s a purpose-fit tracking layer that closes the loop.
Request tracking isn’t a concept for us — it’s running in production today. One of our customers, a clinical-stage drug discovery organization, has been building on WRT for several years, on a foundation that now spans multiple groups and processes across the company.
What started as a way to manage requests for physical samples and experiments has grown steadily ever since. Scientists submit assay requests against whatever identifier fits the work — a sample-specific ID or an ELN experiment ID — and the system routes and tracks each one through fulfillment, whether the work is handled by an in-house group or an external CRO. A team of Workflow Informatics consultants supports the platform and its surrounding infrastructure, and the next expansion is already underway: managing compound libraries requested for high-throughput screening.
The takeaway: when a request-and-tracking layer genuinely fits how a team works, it doesn’t stay in one corner — it becomes the connective tissue for how work moves across the organization.
WRT is a complete request-to-fulfillment system built specifically for drug discovery — not a generic tracker with lab labels pasted on. It delivers LIMS-grade sample tracking at a fraction of LIMS cost and complexity, and because Workflow Informatics configures and deploys it into your environment (local or AWS), it integrates with your existing chemical registration and assay databases rather than forcing you into yet another disconnected system.
Built on proven, maintainable foundations — Python or Pipeline Pilot, PostgreSQL, with IAM integration — it’s engineered to grow with your workflows, not lock you into someone else’s.
Learn more at workflowinformatics.com/wrt, or reach out to info@workflowinformatics.com to schedule a discussion.
Workflow Informatics has joined the Pistoia Alliance — the global nonprofit that brings life sciences organizations together to lower the barriers to R&D innovation through pre-competitive collaboration. Its 200+ members span pharma, biotech, academia, and technology providers, working on data standards, interoperability, FAIR data, and the responsible use of AI in research.
That mission sits close to how we think about our own work — getting scientific data and workflows to move freely instead of stalling at the seams. We’re looking forward to contributing to that community.
Learn more at pistoiaalliance.org.