Application Security for Regulated Research Software

Not every piece of code a biotech client uses sits inside a validated system under 21 CFR Part 11 or an equivalent framework; a marketing site or an internal scheduling tool usually doesn't. Start by mapping which repos support a validated process and which don't, since that map determines whether a routine dependency update needs to go through formal change control or can ship on a normal engineering cadence.

Get this map reviewed and signed off by the client's quality team directly, rather than relying on your own engineering team's best guess at what counts as validated.

For code inside a validated system, a scanning tool's output needs to become part of the record a quality team can review, not just a developer-facing alert. Whichever tool you use, export findings and remediation history in a format your client's quality or regulatory team can attach to their own documentation, since a scanning result that only lives inside a developer dashboard doesn't help their audit trail.

Ask to see a sample of an existing validation record before you build the export, so you're matching a format the quality team already trusts rather than guessing.

A usable record for a validated system includes:

• Exported findings from the scanning tool, in a format the client's quality or regulatory team can actually review.
• Remediation history showing when each finding was raised, fixed, and closed.
• A note of which repos support a validated process under the client's framework and which sit outside it.
• Any change-control cycle a fix needed before it could ship, so the timeline shows the delay honestly.

A dependency update inside a validated system may need to go through the client's change-control process before it ships, even for a routine security patch. Build that into your remediation timeline honestly: if a fix realistically needs a change-control cycle to reach production, don't promise a two-day turnaround you can't actually hit, and instead document the interim risk-acceptance decision the client's quality team makes while the change works through their process.

Snyk's dependency and container scanning works well as an input to a validated system's documentation because its reporting is not tied to any single source control platform, which matters if the client's validated environment is hosted somewhere other than GitHub for compliance reasons. GitHub Advanced Security fits well for the parts of a biotech client's stack that aren't under the same validation burden, like an internal tool or a public-facing site, where the lighter-weight, in-pull-request workflow keeps things moving without the documentation overhead.

Not everything a life sciences client builds needs the validation treatment, and applying it everywhere slows down work that doesn't require it. Reserve the heavier documentation process for genuinely in-scope systems, and let everything else run on a normal engineering cadence with standard dependency and code scanning, so the regulated workflow doesn't become the excuse for shipping slower across the board.

A system that started outside validation scope can drift into it as a client's use of it changes, for instance when an internal reporting tool starts feeding data into a validated process it never touched before. Revisit the scope map periodically rather than treating the initial classification as permanent, since a client's quality team may not think to tell your engineering team when a system's role has quietly expanded.

Build a short, recurring check into the engagement: ask the client's quality lead once a quarter whether any system your team maintains has taken on a new role that might pull it into validation scope. That conversation is far cheaper than discovering the drift during an actual regulatory inspection, when the gap becomes the client's problem and, by extension, yours.

Keep a short written log of each scope review, even a single line noting the date and the outcome, so the history survives a change in who's assigned to the account. A quality team auditing your process later will ask for exactly that kind of trail, and reconstructing it from memory after the fact is far harder than keeping it as you go.