A new systematic analysis of FDA regulatory correspondence provides a more balanced picture of artificial-intelligence enforcement than individual headlines may suggest. Researchers reviewed all 3,011 FDA Warning Letters issued between 1 January 2022 and 28 September 2026 and found only seven that referred to AI. Just one letter directly treated a company’s use of AI as a current Good Manufacturing Practice violation.
The study, published on 31 October 2026 in Discover Pharmaceutical Sciences, also examined publicly released Form FDA 483 observations and Establishment Inspection Reports containing AI-related references.
Artificial intelligence is increasingly being used to support toxicological literature searches, data extraction and preparation of Health-Based Exposure Limit assessments. A new paper published on 12 October 2026 argues that these tools should be governed according to their actual influence on the HBEL decision rather than automatically subjecting every supporting AI application to a full computerized-system-validation package.
The article, Risk-based governance of AI-tools used in health-based exposure limit derivation, was published in Regulatory Toxicology and Pharmacology.
It addresses a highly practical GMP question:
What level of validation and governance is appropriate when AI assists qualified toxicologists in establishing PDEs, ADEs or occupational exposure limits?
The European Union has reached an important milestone in the practical implementation of the Artificial Intelligence Act.
On 14 October 2026, the European Commission published in the Official Journal of the European Union the reference to EN 18286:2026 – Artificial Intelligence – Quality Management System for EU AI Act Regulatory Purposes.
It is the first harmonised standard formally cited in support of the EU AI Act.
The standard translates the quality-management-system requirements of Article 17 of Regulation (EU) 2024/1689 into an operational and auditable framework for providers of high-risk AI systems.
For pharmaceutical and life-sciences organisations, the most important message is not that every AI application now requires a new QMS.