The challenge
Good Laboratory Practice (GLP) studies run on paperwork as much as on science, and GLP study management software exists to keep that paperwork in order. Every step, from the moment a test item arrives to the day its raw data is archived, has to be recorded, approved and traceable.
For a contract research organization, that discipline sits on top of a commercial process: sponsors inquire, studies are quoted, and long studies are billed in stages.
This contract research organization in Gujarat runs GLP studies for outside sponsor companies. Each study passes from the test item control office to a study director, study staff, quality assurance and finally the archivist, and every hand-off needs a formal record and an approval.
Leads, quotations, invoices and study stages were kept in separate places. Nobody could see, at a glance, where a given study stood or what it was waiting on.
The lab needed GLP study management software that joined both halves of the business: the sponsor journey and the study itself.
The GLP study management software we built
We built the lab's GLP process software as a single web application on React, Node.js, Express.js and MongoDB. It has two sides that share one set of records.
The commercial side. Sales staff move each sponsor lead through a visual funnel, log calls and schedule follow-ups. Quotations cover the studies a sponsor needs, with editable terms, and a canceled quote keeps its reason. Accounts raises proforma and final invoices from the same records, and splits long studies into milestone invoices as each stage is reached.
The study side. Once a study is won, the test item control office acknowledges the material in the system, and that acknowledgment starts the study record. The system prepares the allotment letter and tracks the study plan through approval.
During the live phase, staff raise sample requests and update status. At the end, final report inspection and the request to archive the raw data run through the same record.
Twelve role dashboards, from the sales head to QA and animal resources staff, so each person sees their own queue.
A Gantt chart that shows estimated and actual dates side by side for every study.
Email and in-app alerts for deadlines and plan changes.
Sponsor access to fill in forms, upload documents and follow study status.
How it works day to day
Take a study director starting the week. Their dashboard lists the studies assigned to them and the steps waiting on their approval.
A study whose actual dates have slipped behind the plan stands out on the Gantt chart before anyone has to ask. When QA finishes its review, the study moves on to report inspection without an email chain to chase.
On the commercial side, a sponsor's details are entered once. When a quotation is accepted, the same record becomes the study and, later, the invoices. Nothing is retyped between sales, accounts and the lab floor.
As more staff started using the system, small requests built up. We set up a dedicated team of a project manager, a frontend developer and a backend developer. The lab sends requests by email or WhatsApp, and the project manager confirms each one before work starts. Larger changes, such as ad-hoc invoicing, are scoped separately.
The result
A sponsor now moves from inquiry to quotation, invoice and study without data being retyped, and each role sees the studies and tasks waiting on them. In the first two weeks of support, the dedicated team closed more than 30 tracker items, mostly in quotations and inquiry management.
What the research says
Email makes a poor task list. Microsoft's 2025 Work Trend Index analysis found the average worker receives 117 emails a day and is interrupted every 2 minutes during core hours, 275 times a day (Microsoft WorkLab, 2025). Role dashboards and alerts show each person the studies and tasks waiting on them, so work does not depend on an inbox.
Coordination crowds out skilled work. Asana's Anatomy of Work Index, a survey of more than 10,000 knowledge workers by the work management vendor, found that 60% of time at work goes on work about work rather than skilled work (Asana). A sponsor moves from inquiry to quotation, invoice and study here without anyone retyping the data.
Breaches keep getting dearer. IBM's 2026 Cost of a Data Breach report puts the global average cost of a breach at $4.99 million, a 12% rise on the year and a record high (IBM, 2026). Keeping sponsor, study and billing records in one system, with a defined role for each user, leaves one place to secure instead of many.
Where AI fits next
None of the following is built yet; each is an idea the study records already support. A model could draft study quotations from past quotes for similar studies, for the sales head to check. It could flag studies whose actual dates are drifting from plan, and summarize QA findings before final report inspection.
Planning something similar?
Before you build GLP or lab process software, it helps to answer four questions:
Which hand-offs need a formal approval, and who signs each one?
Does billing follow the study, for example by milestone, or run separately?
What must be archived, for how long, and under which regulator's rules?
Which parts should sponsors see, and what should stay internal?
Read how we handle custom software development for regulated teams and workflow automation, weigh custom software against an off-the-shelf package, or browse our healthcare projects.
