Your study database grows every week, and your team spends real time measuring, testing, and entering results. Can any of that work be included in an SR&ED claim?
Sometimes. The answer depends less on the tool or task than on why the data was collected.
Why routine data is treated differently
The Income Tax Act excludes routine data collection and routine testing from SR&ED. It also allows certain data collection and testing when that work directly supports eligible research and is reasonable for what the research needs.
Those rules can apply to the same activity in different ways. A blood draw, scan, assay, or software test may be routine in one project and direct support for an experiment in another.
The purpose of the work is what separates them.
The same assay, two different reasons
Imagine two afternoons in a translational lab.
On the first afternoon, the team runs a validated ELISA on banked samples to keep a departmental registry up to date. The assay works as expected. The results are useful, but the team is following an established process for normal reporting. That is routine data collection.
On the second afternoon, the antibody behaves unpredictably in a new sample type. The team tests whether a different blocking step will restore specificity. They change one variable, compare the results, and revise the next test based on what they observe.
The instrument, staff, and reagents may be identical. The reason for the work is different. The second set of measurements was collected to help resolve a scientific or technological uncertainty, so it may support the experiment.
Data can still be excluded even when it later proves useful to eligible research. If it was originally gathered for ordinary clinical care, quality control, reporting, or operations, later usefulness does not change its original purpose.
Look inside the protocol
A study protocol can appear fixed from beginning to end, but the real work is often less tidy. Assays drift. A segmentation pipeline breaks on data from a second scanner. A protocol is amended because an established method no longer gives a reliable answer.
The work done to understand and resolve that problem may qualify even if most of the study remains routine. At the same time, the fact that a trial is scientifically important does not turn every visit, draw, and data-entry task into SR&ED.
Start with the specific uncertainty and the tests used to address it. Then identify the amount of supporting data collection the experiment actually required. This makes the boundary easier to explain and avoids treating the entire database as one kind of work.
Make the reason visible in your records
You do not need a new documentation system. You need a record that explains why a measurement was taken.
A protocol amendment can describe what stopped working. A notebook entry can record what you expected and what happened. A software commit can name the parameter that changed and the reason for the change.
These ordinary research records help someone reading the file later understand whether the team was maintaining a process or testing an unknown. If part of your team's time was spent measuring specifically to resolve a real uncertainty, a short conversation can help separate that work from routine clinical and operational data collection.