Software engineering for connected life sciences operations
Build and connect applications across laboratory, quality, manufacturing and supply-chain workflows without turning each function into another data silo.
Tailored software
Connected operations
Rarely inside a single function. Laboratories, quality, manufacturing and supply chain each tend to run capable systems that were bought separately and integrated afterwards, if at all. The cost shows up in the gaps between them, results retyped from an instrument into a spreadsheet and then into a quality system, a deviation raised in one system and investigated in another, a batch record assembled by hand from four sources before it can be reviewed.
Most of what we build sits in those gaps: applications that carry a workflow across systems that were never designed to talk to each other, and integrations that let a result move from where it was produced to where it is used without a human retyping it.
Validation lifecycle
Validation is documented evidence that a system does what it is specified to do, consistently, and that it has not silently changed since that was established. It is not a testing phase at the end of a project; it is a way of building that produces evidence as a by-product.
What the system must do, in the business's words, traceable to everything that follows
Which functions carry patient safety, product quality or data integrity risk, and therefore how much rigour each needs
How the system meets those requirements
Evidence the system is installed as specified, in the right environment
Evidence each function behaves as specified across its range, including failure cases
Evidence the system performs in its real operating context with real users and real data
The thread from each requirement through its specification to the test that proves it
The matrix is the artefact an inspector reaches for first. A system with excellent tests and no traceability is difficult to defend; a system with modest tests and complete traceability usually is not.
GxP regulations
GAMP 5 is the industry guidance rather than a regulation, and it sets the risk-based approach that most inspectors now expect: effort proportional to risk, software categorised by how much it has been configured or customised, and supplier assessment used to avoid re-testing what a vendor has already proven.
21 CFR Part 11 governs electronic records and electronic signatures for products regulated in the United States, audit trails, record retention, copies for inspection, signature manifestation, and controls over who can do what.
EU Annex 11 is the European counterpart, covering much of the same ground with a stronger emphasis on risk management, supplier arrangements and data lifecycle.
Computer Software Assurance is the newer FDA-aligned thinking that shifts effort away from documenting low-risk testing and towards critical thinking and assurance activity where risk actually is. It reduces paperwork, not rigour.
Data integrity expectations are usually expressed as ALCOA+: data should be attributable, legible, contemporaneous, original and accurate, and also complete, consistent, enduring and available. Most findings in this area are not sophisticated, shared logins, audit trails that were never reviewed, a spreadsheet doing work a validated system should be doing.
Validation delivery
By running alongside the build rather than after it. Validation applied at the end of a project validates a system that has already moved on, and the rework is where the cost and the delay come from.
User requirements specification drafted with the people who will use the system
Risk assessment, GAMP 5 software categorisation, supplier assessment
Design specification maintained as the design settles; test protocols written against requirements
IQ and OQ executed against the release candidate, not against a moving build
PQ in the real operating context; validation summary report
Change control, periodic review, revalidation where changes warrant it
The point of the release candidate is that qualification is executed against something that will not change underneath it. A build that is still moving cannot be qualified, and attempting it is the most common reason validation overruns.
Systems integration
Sample registration, test results, specifications, out-of-specification flags
Deviations, CAPA, change control, training records
Materials, batches, production orders, inventory movements
Interface design carries more weight here than in most environments, because an interface that moves GxP data is itself in scope for validation. Deciding late that two systems should exchange data automatically means re-opening qualification, which is why integration boundaries are settled during architecture.
Batch records, equipment usage, in-process results
Direct result capture, avoiding transcription
Controlled SOPs, specifications, reports
Single sign-on and directory integration, so access control is managed once
Scope decisions
A great deal of what a life sciences organisation runs does not touch product quality or patient safety, and treating everything as regulated is expensive and slows the work that matters. Research tools, facility systems, scheduling, laboratory logistics and administrative workflow mostly sit outside GxP scope. We build those as ordinary software, on ordinary timelines, and say so plainly when a system does not need the treatment.
Explore AdventSys services →Specialist validation
Validation itself is delivered by our GoVal team, GAMP 5 risk-based CSV, computer software assurance, equipment qualification and data integrity work, with or without the GoVal platform.
Visit govalidation.com →Case studies
A role-based onboarding platform routing tasks across HR, department heads, lab cluster heads and verification users, with controlled archival and automated reminders.
View project →
A web-based colony-management system for animal inventory, genealogy, breeding, genotype records, cage tracking, billing, alerts and reporting.
View project →
Design and front-end delivery for a remote-patient-monitoring platform that surfaces at-risk patients from continuous wearable and self-reported data.
View project →FAQ
No, and treating it that way wastes money on systems that carry no product quality or patient safety risk. The risk assessment decides it. A laboratory information system holding release results is in scope; a meeting room booking tool is not; systems in between are judged on what a failure would actually affect.
Less than most teams expect when it runs alongside the build, and considerably more when it is left to the end. Requirements and risk assessment happen during work that is happening anyway. The qualification execution itself is usually weeks rather than months for a system of moderate complexity, provided the release candidate is stable.
Yes. It starts with an assessment of what documentation exists, what the system actually does versus what it was specified to do, and where the gaps are. Retrospective validation is more work than doing it alongside a build, and it is a normal situation with systems that have been in production for years.
Change control decides it. Each change is assessed for whether it affects validated functionality, and what that requires, anything from a documented assessment to partial re-qualification. A system that has been enhanced for two years without change control is no longer in a validated state, whatever the original documentation says.
Yes, most of our clients ship to both markets and design to satisfy both. The requirements overlap substantially on audit trail, access control and record retention; where they differ, the stricter expectation is usually the one to build to, since meeting it satisfies the other.
You own them, and we draft them with you during discovery. A URS written by a vendor in isolation tends to describe the system the vendor intends to build rather than what the business needs, which is a problem that only becomes visible at performance qualification.
