{"id":17443,"date":"2026-11-03T16:08:21","date_gmt":"2026-11-03T15:08:21","guid":{"rendered":"https:\/\/q-finity.de\/ai-in-pharma-2026-krakow-bericht\/"},"modified":"2026-11-03T16:53:05","modified_gmt":"2026-11-03T15:53:05","slug":"ai-in-pharma-2026-krakow-report","status":"publish","type":"post","link":"https:\/\/q-finity.de\/en\/ai-in-pharma-2026-krakow-report\/","title":{"rendered":"AI in Pharma 2026 in Krak\u00f3w: AI-Supported Validation Between Vision and Reality"},"content":{"rendered":"

AI in Pharma 2026, the fourth edition of the conference run by ISPE Poland and its GAMP Community of Practice, brought practitioners from pharma, technology and the regulatory field together in Kraków on October 26 and 27. Frank Henrichmann opened the track on trustworthy and regulated AI for QFINITY with a reality check. AI-supported validation of computerized systems is achievable today, within the applicable regulations and guidance, with the draft Annex 22 outlining the AI-specific additions.<\/p>\n

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From requirement to test evidence<\/b>Frank Henrichmann shows which steps in the validation workflow AI can take on.<\/figcaption><\/figure>\n

The program covered four tracks over two days, from “Trusted, Safe & Regulated AI” to “Sustainable & Responsible AI”. A student hackathon at AGH Kraków had already taken place the day before. At the Novotel Kraków Centrum, one question stood at the center, the question many quality organizations are working on right now. How do computerized systems with AI support get from pilot status into validated operation? Frank Henrichmann, Senior Executive Consultant at QFINITY and Chair of the ISPE GAMP Global Steering Committee, showed on day one how that question can be answered from a validation point of view. The vision of AI-supported CSV can be measured against what 21 CFR Part 11 and Annex 11 require, what GAMP 5<\/a> and the FDA’s CSA guidance describe as the way to get there, and what the draft Annex 22 outlines for AI in GMP.<\/p>\n

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Why validation is seen as a bottleneck<\/h2>\n
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The bottleneck<\/b>Manual effort between compliance and innovation speed, the starting point of the talk.<\/figcaption><\/figure>\n

The talk started from the everyday reality of many validation teams. Risk assessments and test scripts are written by hand. Ambiguous requirements lead to ineffective tests and compliance gaps. Traceability lives in static spreadsheets that nobody likes to maintain. As a result, validation, a cornerstone of compliance, is perceived as a brake on innovation. This is where AI comes in, at drafts and routine steps.<\/p>\n

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What may an AI draft in the validation workflow, and what remains a human decision?<\/p>\n

Three approaches from the talk<\/h2>\n
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1<\/div>\n
An adoption model in three stages.<\/b> The model follows the stages Crawl, Walk and Run. First, AI assists with drafts of requirements and test scripts; next, it serves as a tool in risk-based assessment; finally, it carries end-to-end traceability from requirement to test evidence. Each stage has its own scope of controls, and approval by the subject matter expert remains in place at every stage.<\/div>\n<\/div>\n
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2<\/div>\n
A comparison matrix of two routes.<\/b> The matrix sets out the advantages and disadvantages of supporting validation with a general-purpose language model versus an AI-enabled digital validation tool. ALCOA<\/a>++ and auditability apply to AI-generated records on both routes just as they do to manually created ones.<\/div>\n<\/div>\n
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3<\/div>\n
A way to calculate the business case.<\/b> Using a typical system as the example, the talk showed how the effort of initial validation and revalidation can be compared with and without AI drafts, and which review steps remain in both cases. The underlying pattern stays the same: the AI produces drafts, a human reviews and approves them. It carries over to other system landscapes once the intended use and the risk assessment of the system are in place.<\/div>\n<\/div>\n<\/div>\n

What QFINITY takes home from Kraków<\/h2>\n

Four tracks, a hackathon and talks from users such as GSK, Roche and Polpharma show that the discussion has arrived at the question of how AI in validation is controlled in a way that can be demonstrated. As Chair of the ISPE GAMP Global Steering Committee, Frank Henrichmann bridged the Polish GAMP community and the global GAMP work, which includes the GAMP Guide Artificial Intelligence. For users, the conclusion is that the path to AI-supported validation runs through controls the current regulations already require.<\/p>\n

Our topic area Artificial Intelligence in the GxP Environment<\/a> shows how we use AI in your validation without losing the evidence. What the EU expects of AI in GMP is explained in our article on the draft EU GMP Annex 22<\/a>. If you would like to talk to us directly, book an appointment<\/a>.<\/p>\n

Trust is not reviewed into a system. It is designed into it.<\/p><\/blockquote>\n

AI in Pharma 2026, ISPE Poland Affiliate (ispe.org.pl)<\/span>↗<\/span><\/a><\/p>\n

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Impressions<\/span>From Kraków<\/span>1<\/b> \/ 5<\/span><\/div>\n
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A full room for the opening of the “Trusted, Safe & Regulated AI” track.<\/figcaption><\/figure>\n
\"Moderator
Q&A after the talk.<\/figcaption><\/figure>\n
\"Frank
The audience joined the discussion as well.<\/figcaption><\/figure>\n
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Round table on the fringes of the conference.<\/figcaption><\/figure>\n
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Conversations during the break.<\/figcaption><\/figure>\n<\/div>\n