The digital transformation in GxP-regulated fields.
Digital transformation in a GxP-regulated environment changes the organization as a whole. It extends to ways of working, methods and tools whose outcomes ultimately affect patients; digitalizing individual use cases is a building block, not the goal. What slows it down is rarely regulation and more often a pair of misconceptions: that more documentation means better cover in an inspection, and that inspectors expect the most comprehensive paper-based evidence possible. Neither assumption holds up. We place people and the processes they are responsible for at the center and establish methods that enable innovation rather than prevent it.
Technology follows the process - not the other way around.
New technologies shift costs, benefits and the effort evidence requires. Bringing those three into balance means questioning long-established quality approaches, and that rethink needs the whole quality organization behind it. The process is the starting point: it defines a tool's intended use, which in turn determines the requirements, risks and depth of evidence needed. Tools and systems support the ways of working that emerge, without dictating them.
What really holds transformation back?
Rarely the regulations. Usually it is two assumptions from within the organization, and neither has a regulatory basis:
This is exactly where the lever sits: record-based, tool-supported methods create the evidence where it originates, as records in the tool instead of in downstream documents. The evidence goal stays the same; the route becomes more efficient. And only such methods make innovative ways of working possible: AI-supported work, agile development, CI/CD. Where every piece of evidence is transferred into documents after the fact, short release cycles cannot be sustained. Record-based methods sustain them.
The regulations confirm the path.
In pharma and medical devices alike, the regulations themselves are taking the risk-based, digital path. Four examples show how much they explicitly enable: the use of tools, digital records and an orderly framework for AI.
| Framework | What it enables |
|---|---|
| FDA Computer Software AssuranceGuidance for production and quality system software · final 09/2025, QMSR revision 02/2026 | turns risk-based, tool-supported assurance into a program: the framework explicitly covers automation, data analytics and AI/ML tools as well as cloud computing. As evidence the FDA recommends digital records (system logs, audit trails, data generated by the tool) over paper documentation, screenshots and duplicate filing |
| EU GMP Annex 11Pharma · in force since 2011, revision in draft (2025) | provides for tool-supported testing today: "automated testing tools and test environments" have been in the text since 2011, with documented evidence of suitability as the requirement; the current draft revision of Annex 11 stays on this line and, in its own wording, labels tools for requirements traceability and audit trail review "encouraged" |
| EU GMP Annex 22Pharma · new, draft (2025) | gives AI in GMP a solid framework for the first time: with static models and deterministic output, AI can be planned for even in critical applications; generative AI remains possible in non-critical ones, always with human review of the results (human-in-the-loop, HITL). Responsibility for its use remains with the regulated company |
| EU AI ActEU law · in force, obligations phase in over time | aims to protect the health, safety and fundamental rights of people in the EU and at the same time explicitly promote trustworthy AI. It applies across all sectors. Only a narrowly circumscribed set of practices is prohibited, some with defined exceptions. Everything else the AI Act stratifies by risk, from high-risk obligations to transparency rules, making the requirements predictable. The Digital Omnibus (in force from 27 July 2026) further simplifies implementation and eases the timelines |
None of these frameworks prohibits innovation. They all stratify innovation by risk. Build your methods around that risk logic, and regulation is no longer a hurdle in front of you. It becomes confirmation that you are on the right track.
Requirements first, then the tool.
Maturity before roadmap.
Digital transformation starts with culture, not with technology: culture shapes people, people shape processes and put tools to work within them. Your honestly assessed maturity decides how big the next step may be. Only then is the technology decision made.
- Status analysis: assessing maturity, strengths, gaps and ability to deliver
- A quality culture that makes room for critical thinking and involves people directly
- An intended use and risk-based evidence for every tool, derived from the process
We have walked the road from document to record ourselves.
For more than two decades we have validated the use of computerized systems, from ERP, DMS, LIMS and MES to systems on cloud platforms. Document-based at first, record-based today. To us, modernization is not a concept paper but a craft.
That craft shows in the S/4HANA Conversion case study: the global conversion of a production SAP system, validated and taken live without local outages.
How AI is changing validation is something we recently described in Pharmaceutical Engineering: "How AI Will Transform Computerized System Validation" (Herrmann/Henrichmann, Jan/Feb 2026).
Over-documentation provides no cover, and fear is not a compliance strategy. Evidence gains strength not through volume but through precision: record-based, tool-supported, aligned with risk.
The goal is unchanged: robust confidence in processes and products. Only the route there is more efficient today.
Transformation, responsibly led.
We guide your digital transformation on the three levels of people, processes and tools, from the initial maturity assessment through strategy to rolling out new technologies.
Frequently asked questions about digital transformation.
No. The regulations demand risk understanding and controlled processes. None of them asks for the maximum amount of documentation. What slows transformation down is usually a pair of homegrown assumptions: over-documentation as supposed cover, and fear of inspections. The regulations themselves are taking the risk-based path, from the FDA's CSA guidance to the drafts of Annex 11 and Annex 22.
Yes. No regulation prohibits tool-supported validation, quite the opposite: the current Annex 11 already named automated testing tools in its 2011 version, the FDA confirms the route with the CSA guidance, and the draft Annex 11 stays on this line. It expressly calls tools for requirements traceability and audit trail review "encouraged". What counts is the quality of the evidence: record-based methods create the evidence where it originates, and they are more efficient than downstream documentation. The prerequisite is documented evidence of each tool's suitability, scaled to the risk of its use.
Yes. AI-supported work is not prohibited outright, but it does require an orderly framework: governance, defined use cases and risk analyses. The EU AI Act follows the same logic with its risk-based tiering, and the draft Annex 22 is the first to spell out GMP expectations for AI. Limits exist, and they follow from risk, not from a blanket ban: under the draft Annex 22, generative AI should not be used in critical GMP applications. For non-critical applications the draft ties the use of generative AI to a human-in-the-loop, meaning a human review of every output. Our topic area Artificial Intelligence in GxP shows what this looks like in practice.
Not every one, and never the tool alone. What is validated is the application in the process: the process defines the intended use, and risk and depth of evidence follow from it. The deciding factor is the chain from data to product to patient. Pure infrastructure tools, from network monitoring and antivirus to configuration management, sit far from that risk: they are controlled and managed, not validated. Version and correct installation are recorded, and the tool's adequacy for use is assessed. A critical tool needs targeted evidence. Maximum formality is no substitute.
The groundwork for every investment decision. It gives you an unvarnished view of where culture, processes and systems stand and what ability to deliver exists. The result is a roadmap that fits your maturity.
Start with an honest maturity assessment.
In an initial conversation we take stock of your maturity and pinpoint where record-based, tool-supported methods will get you to your goal faster. The technology decision comes after that. Free of charge, about 30 minutes.
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