1. Introduction – A New Era of AI Regulation in Pharma
The new GMP regulations open another chapter in the history of pharmaceuticals, where artificial intelligence ceases to be a curiosity and becomes an integral part of critical processes. In 2025, the European Commission published a draft of Annex 22 to EudraLex Volume 4, introducing the world’s first provisions dedicated to AI in GMP. This document defines how technology must operate in an environment built on accountability and quality control. For the pharmaceutical industry, this means a revolution – every AI-driven decision can directly affect patient safety and must therefore be documented, explainable, and supervised. In other words, artificial intelligence must now pass its GMP exam in order to “put on a white coat” and enter the world of pharma.
2. Why Do We Need AI Regulation in Pharma?
Pharma is one of the most heavily regulated industries in the world. The reason is obvious – every decision, every process, every device has a direct impact on patients’ health and lives. If a new element such as artificial intelligence is introduced into this system, it must be subject to the same rigorous principles as people, machines, and procedures.
Until now, there has been a lack of coherent guidelines. Companies using AI had to adapt existing regulations regarding computerised systems (EU GMP Annex 11: Computerised Systems) or documentation (EU GMP Chapter 4: Documentation). The new Annex 22 to the EU GMP Guidelines brings order to this area and clearly defines how and when AI can be used in GMP processes.
3. AI as a New GMP Employee
The draft regulation treats artificial intelligence as a fully-fledged member of the GMP team. Each model must have:
- job description (intended use) – a clear definition of its purpose, the type of data it processes, and its limitations,
- qualifications and training (validation and testing) – the model must undergo validation using independent test datasets,
- monitoring and audits – AI must be continuously supervised, and its performance regularly assessed,
- responsibility – in cases where decisions are made by a human supported by AI, the regulations require a clear definition of the operator’s accountability and competencies.
In this way, artificial intelligence is not treated as just another “IT tool” but as an element of the manufacturing process, with obligations and subject to evaluation.
4. Deterministic vs. Generative Models
One of the key distinctions in Annex 22 to the EU GMP Guidelines (Annex 22: AI and Machine Learning in the GMP Environment) is the classification of models into:
- deterministic models – always providing the same result for identical input data. These can be applied in critical GMP processes,
- dynamic and generative models – such as large language models (LLMs) or AI that learns in real time. These models are excluded from critical applications and may only be used in non-critical areas under strict human supervision.
This means that although generative AI fascinates with its capabilities, its role in pharmaceuticals will remain limited – at least in the context of drug manufacturing and quality-critical processes.
5. The Transparency and Quality Exam
One of the greatest challenges associated with artificial intelligence is the so-called “black box” problem. Algorithms often deliver accurate results but cannot explain how they reached them. Annex 22 draws a clear line here.
AI models must:
- record which data and features influenced the outcome,
- present a confidence score,
- provide complete documentation of validation and testing.
It is as if AI had to stand before an examination board and defend its answers. Without this, it will not be allowed to work with patients.
6. Periodic Assessment – AI on a Trial Contract
The new regulations emphasize that allowing AI to operate is not a one-time decision. Models must be subject to continuous oversight. If input data, the production environment, or processes change, the model requires revalidation.
This can be compared to a trial contract – even if AI proves effective, it remains subject to regular audits and evaluations, just like any GMP employee.
7. Practical Examples of AI Applications in GMP
The new GMP regulations are not just theory – artificial intelligence is already supporting key areas of production and quality. For example, in quality control, AI analyzes microscopic images of tablets, detecting tiny defects faster than the human eye. In logistics, it predicts demand for active substances, minimizing the risk of shortages. In research and development, it supports the analysis of vast clinical datasets, highlighting correlations that traditional methods might miss.
Each of these cases demonstrates that AI is becoming a practical GMP tool – provided it operates within clearly defined rules.
8. International AI Regulations – How Does Europe Compare Globally?
The draft of Annex 22 positions the European Union as a pioneer, but it is not the only regulatory initiative. The U.S. FDA publishes guidelines on AI in medical processes, focusing on safety and efficacy. Meanwhile, in Asia – particularly in Japan and Singapore – legal frameworks are emerging that allow testing and controlled implementation of AI. The difference is that the EU is the first to create a consistent, mandatory GMP document that will serve as a global reference point.
9. Employee Competencies – AI Knowledge as a Key Element
The new GMP regulations are not only about technology but also about people. Pharmaceutical employees must acquire new competencies – from understanding the basics of how AI models function to evaluating results and overseeing systems. This is known as AI literacy – the ability to consciously collaborate with intelligent tools. Organizations that invest in developing their teams’ skills will gain an advantage, as effective AI oversight will be required both by regulators and internal quality procedures.
10. Ethics and Risks – What Must Not Be Forgotten
Beyond technical requirements, ethical aspects are equally important. AI can unintentionally introduce biases inherited from training data, which in pharma could lead to flawed conclusions. There is also the risk of over-reliance on technology without proper human oversight. This is why the new GMP regulations emphasize transparency, supervision, and accountability – ensuring that AI serves as a support rather than a threat to quality and safety.
10.1 What Does AI Regulation Mean for the Pharmaceutical Industry?
For pharmaceutical companies, Annex 22 is both a challenge and an opportunity:
- Challenge: it requires the creation of new validation, documentation, and control procedures.
- Opportunity: clearly defined rules provide greater certainty in AI investments and can accelerate the implementation of innovative solutions.
Europe is positioning itself as a pioneer, creating a standard that will likely become a model for other regions worldwide.
11. How TTMS Can Help You Leverage AI in Pharma
At TTMS, we fully understand how difficult it is to combine innovative AI technologies with strict pharmaceutical regulations. Our team of experts supports companies in:
- analysing and assessing the compliance of existing AI models with GMP requirements,
- creating validation and documentation processes aligned with the new regulations,
- implementing IT solutions that enhance efficiency without compromising patient trust,
- preparing organizations for full entry into the GMP 4.0 era.
Ready to take the next step? Get in touch with us and discover how we can accelerate your path toward safe and innovative pharmaceuticals.
What is Annex 22 to the GMP Guidelines?
Annex 22 is a new regulatory document prepared by the European Commission that defines the rules for applying artificial intelligence in pharmaceutical processes. It is part of EudraLex Volume 4 and complements existing chapters on documentation (Chapter 4) and computerised systems (Annex 11). It is the world’s first regulatory guide dedicated specifically to AI in GMP.
Why were AI regulations introduced?
Because AI increasingly influences critical processes that can directly affect the quality of medicines and patient safety. The regulations aim to ensure that its use is transparent, controlled, and aligned with the quality standards that govern the pharmaceutical sector.
Are all AI models allowed in GMP?
No. Only deterministic models are permitted in critical processes. Dynamic and generative models may only be used in non-critical areas, and always under strict human supervision.
What are the key requirements for AI?
Every AI model must have a clearly defined intended use, undergo a validation process, make use of independent test data, and be explainable and monitored in real time. The regulations treat AI as a GMP employee – it must hold qualifications, undergo audits, and be subject to evaluation.
How can companies prepare for the implementation of Annex 22?
The best step is to conduct an internal audit, assess current AI models, and evaluate their compliance with the upcoming regulations. Companies should also establish validation and documentation procedures to be ready for the new requirements. Support from technology partners such as TTMS can greatly simplify this process and accelerate adaptation.