Artificial intelligence may soon become more deeply embedded in the European pharmaceutical regulatory framework.
The proposed European Biotech Act contains a dedicated chapter on artificial intelligence and data as biotechnology enablers.
Its significance goes beyond another set of general responsible-AI principles.
The proposal foresees three concrete elements with direct relevance to pharmaceutical companies:
-
[]EMA guidance on AI across the medicinal-product lifecycle;
- data-quality accelerators supporting AI training, testing and validation.
[]trusted testing environments for AI-enabled biotechnology;
The proposal is still moving through the EU legislative process and is not yet final law.
However, discussions continued within the Council Working Party on Pharmaceuticals and Medical Devices in September 2026, while EMA reported on 1 October that preparations for implementation of the Biotech Act are already influencing its future regulatory infrastructure.
For pharmaceutical companies, this is an important signal:
AI governance in Europe may evolve from individual guidance documents toward a coordinated regulatory and technical infrastructure for developing, validating and using AI across the medicines lifecycle.
EMA Could Receive a Broader AI Guidance Role
The proposed legislation would require EMA to develop and publish guidance, in cooperation with the European Commission and national competent authorities, on the deployment and use of advanced technologies including artificial intelligence.
The intended scope is broad.
It covers AI across areas such as:
-
[]medicinal-product development;
- post-authorisation activities.
[]manufacturing;
[]clinical trials;
[]regulatory evaluation and authorisation;
This is important because current pharmaceutical AI guidance remains distributed across multiple documents and regulatory initiatives.
Examples include:
-
[]the EMA reflection paper on AI in the medicinal-product lifecycle;
- digital technology qualification guidance.
[]FDA/EMA Guiding Principles of Good AI Practice;
[]draft EU GMP Annex 22;
[]planned AI guidance for pharmacovigilance;
The Biotech Act could provide a legal framework for bringing these activities into a more coherent lifecycle approach.
AI Guidance Would Not Be Limited to One Technology
The proposal refers not only to conventional machine-learning systems but also to:
AI systems and general-purpose AI models.
This distinction is increasingly important.
Pharmaceutical companies are moving beyond narrowly trained predictive models toward:
-
[]foundation models;
[]large language models;
[]Generative AI;
[]multimodal systems;
[]AI agents;
[]hybrid AI architectures.
A future EMA guidance framework may therefore need to address very different technological characteristics and risk profiles.
The regulatory question becomes less:
“Is this an AI system?”
and more:
“What does this AI do, what decision does it influence, and what level of assurance is required for that Context of Use?”
Trusted AI Testing Environments Could Be More Important Than Another Guidance Document
One of the most interesting elements of the proposed Biotech Act is the concept of trusted testing environments for advanced biotechnology innovations.
These environments would support technologies that are enabled or significantly enhanced by AI or advanced computational methods.
Their purpose would be to provide controlled environments where organisations can develop, test and validate innovations while operating under applicable regulatory requirements.
Potential applications identified in the proposal include advanced biotechnology areas such as:
-
[]immunology;
- AI-supported biotechnology and biomanufacturing.
[]ATMP and gene-therapy development;
[]advanced computational methods;
[]New Approach Methodologies;
This creates a potentially important model:
Develop → Experiment → Validate → Generate Evidence → Inform Standards and Regulation
under controlled conditions.
For pharmaceutical AI, this could be particularly valuable because many current barriers are not purely technical.
Companies also need to understand what evidence regulators will consider sufficiently credible.
A Possible Bridge Between Innovation and Regulatory Acceptance
AI development often moves faster than formal pharmaceutical guidance.
This creates a familiar problem.
A company may develop a technically successful AI system but still face uncertainty regarding:
-
[]regulatory acceptability;
- data requirements.
[]validation expectations;
[]documentation requirements;
[]acceptable performance criteria;
[]change management;
[]human oversight;
Trusted testing environments could create a more structured way of addressing these questions before large-scale regulatory deployment.
Instead of waiting until a marketing application, manufacturing change or regulatory submission is ready, developers could potentially generate regulatory learning earlier.
Conceptually, this creates a bridge between:
innovation experimentation
and
regulated pharmaceutical implementation.
Data Quality Accelerators Are the Third Pillar
The proposal also recognises a problem that is becoming increasingly obvious:
AI performance depends fundamentally on the quality of the data used to train, test and operate the system.
The proposed biotechnology data-quality accelerators would support the development of datasets that are:
-
[]high quality;
[]appropriately annotated;
[]standardised;
[]curated;
[]provenance verified;
[]suitable for AI training, validation and testing.
This may become particularly important in pharmaceutical environments where data are distributed across:
-
[]laboratory systems;
[]clinical systems;
[]manufacturing systems;
[]Quality Management Systems;
[]regulatory repositories;
[]real-world data sources.
The challenge is often not lack of data.
The challenge is whether those data are sufficiently structured, controlled and contextualised to support a regulated AI application.
Data Provenance Could Become Part of AI Validation
Traditional computerized-system validation often focuses strongly on application functionality.
AI adds another layer.
The credibility of the output can depend on the entire data chain:
Source Data
↓
Curation and Transformation
↓
Training / Validation Dataset
↓
AI Model
↓
AI Output
↓
Regulated Decision
This means that validation of an AI-enabled pharmaceutical process may increasingly require evidence not only about the model, but also about:
-
[]where the data originated;
- whether data quality remains suitable during operation.
[]how the data were transformed;
[]which version was used;
[]whether important populations or conditions were represented;
The proposed emphasis on provenance-verified datasets is therefore particularly relevant for GxP environments.
The Biotech Act Could Help Connect the AI Act with Pharmaceutical Regulation
Another important aspect is the relationship with the EU AI Act.
The Biotech Act proposal foresees interaction between pharmaceutical AI testing environments and AI testing or regulatory mechanisms established under Regulation (EU) 2024/1689.
This is strategically important.
Pharmaceutical companies may need to manage two regulatory dimensions simultaneously:
horizontal AI regulation
and
sector-specific pharmaceutical regulation.
These frameworks ask different questions.
The AI Act focuses on the governance and risks of AI systems.
Pharmaceutical regulation focuses on:
-
[]patient safety;
- regulatory decision-making.
[]product quality;
[]clinical evidence;
[]manufacturing control;
The challenge will be to avoid creating two disconnected assurance systems for the same AI application.
Relevance to GMP Manufacturing
The proposal explicitly includes manufacturing within the future lifecycle AI-guidance framework.
For GMP organisations, this is particularly important.
AI applications may increasingly support:
-
[]process monitoring;
- manufacturing knowledge management.
[]predictive process modelling;
[]deviation analysis;
[]maintenance;
[]Quality System analytics;
[]advanced process control;
Draft Annex 22 is currently the most visible European GMP-specific AI initiative.
The Biotech Act suggests that Annex 22 may eventually sit inside a broader European AI regulatory architecture rather than functioning as an isolated GMP document.
The Regulatory Model Is Becoming Multi-Layered
A future European pharmaceutical AI framework could increasingly consist of several layers:
EU AI Act
↓
European Biotech Act
↓
EMA Lifecycle AI Guidance
↓
Domain-Specific Guidance such as GMP Annex 22
↓
Testing Environments and Regulatory Sandboxes
↓
Company AI Governance and Validation
For global pharmaceutical companies, understanding how these layers interact may become as important as understanding each document individually.
Current Regulatory Status
The European Biotech Act remains a legislative proposal.
It is currently being considered by the European Parliament and Council and its final wording may change.
Council working-party discussions on the proposal continued during September 2026.
EMA has also confirmed that it is preparing for potential implementation of the legislation while progressing its broader data and artificial-intelligence activities.
Therefore, pharmaceutical companies should not treat the proposed AI provisions as current binding requirements.
They should instead be viewed as a strong indication of the future direction of European pharmaceutical AI regulation.
Why This Matters
Most pharmaceutical AI regulation to date has focused on principles and guidance.
The Biotech Act introduces something different:
regulatory infrastructure.
The emerging model is not only:
write guidance → ask industry to comply.
It increasingly looks like:
Guidance → Trusted Testing → High-Quality Data → Regulatory Learning → Validation → Deployment.
If implemented, this could significantly influence how pharmaceutical companies develop and validate AI systems in Europe.
It also reinforces a broader message:
Trustworthy pharmaceutical AI will depend not only on the algorithm, but on the regulatory, data and testing infrastructure surrounding it.
Sources
European Commission – European Biotech Act:
https://health.ec.eu … opean-biotech-act_en
EUR-Lex – Proposal for the European Biotech Act:
https://eur-lex.euro … ri=CELEX:52025PC1022
Council of the European Union – Working Party on Pharmaceuticals and Medical Devices, 16 September 2026:
https://www.consiliu … evices-%28369737%29/
EMA – Management Board highlights, September 2026 meeting: