In many manufacturing companies, equipment qualification and computer system validation sit in different teams. Engineering qualifies the autoclave, the bioreactor and the filling line. Quality or IT validates the MES, the LIMS and the historian. Each team has its own templates, its own vocabulary and its own view of what risk means.
That split made sense once. It makes much less sense now, when almost every piece of equipment is controlled by software and almost every computerised system talks to equipment.
Where the split causes problems
The problems appear at the boundary. A modern bioreactor has a control system with recipes, alarms, user accounts and an audit trail. Is that part of equipment qualification or computer validation? In practice it is often half-covered by both, and fully covered by neither.
Data integrity is the clearest example. Equipment teams historically focused on whether the equipment performs: does it hold temperature, does it reach pressure. Data integrity questions, such as who can change a recipe, whether the audit trail can be switched off, and whether data is backed up, sit more naturally with computer validation. When nobody owns both, these questions fall through.
Change control suffers too. A software update to an equipment controller may be treated as an engineering change, without the impact assessment a computerised system change would get. Or the reverse, with a minor configuration change triggering a full requalification because nobody was sure.
Different languages, same idea
The frameworks are not as different as the teams think. Annex 15 asks for qualification proportionate to risk, and allows supplier and commissioning evidence to be used. ASTM E2500, revised in 2025, is built around science and risk. GAMP 5 and the CSA guidance say the same about software. Instruments have USP <1058>, grouped by what they do.
Each uses its own terms, and they should keep them, because each describes a different kind of asset accurately. But underneath, they share one approach: understand what matters, test that properly, use good evidence from suppliers, and keep the asset in its qualified state.
What a joined-up practice looks like
One risk method that covers the whole asset, including its software. Clear ownership of the control system, its configuration and its data, written down for each type of equipment. Change control that asks both questions: does this change affect performance, and does it affect data?
Shared periodic review, so that the review of a piece of equipment includes its software, user access and audit trail, not just calibration and maintenance.
And a single view of the qualified state, so that someone can answer, for any asset, what was tested, what has changed since, and what is due.
Why now
Equipment is becoming more connected and more software-driven every year. Inspectors increasingly ask data integrity questions on the shop floor, not only in the laboratory. Companies that keep the two disciplines apart will keep finding gaps between them, usually during an inspection.
Bringing them together does not mean merging the teams. It means agreeing one approach to risk, one owner for every boundary, and one record of the state of every asset.
For the practical detail, see equipment qualification.
Where to go next
Explore GxP Copilot for AI-native validation, TraceDraft for source-traceable clinical documentation, or book a demo to see either on your own data.