AI & Digital Health Technologies

Standalone Module - Fall 2026 - 4 ETCS - CHF 4'200

  

This module provides you with specialized knowledge regarding the regulation of medical device software in Europe and the USA. Since it is difficult to regulate a technical domain, one has scant knowledge of, the module will introduce the foundations of modern software engineering with a special focus on which aspects to watch for to ensure smooth approval of even the most complex software-based medical devices. The module offers an overview of the regulatory framework for medical device software, software development lifecycle, and software quality management. You will also gain understanding of specialized regulations regarding the safety and cybersecurity of devices based on artificial intelligence.

Learning objectives

  • You can explain the foundational concepts and limitations of artificial intelligence (AI), including distinctions between rule-based systems, machine learning (ML), and large language models (LLMs), and assess their implications for regulatory evaluation.
  • You can differentiate between categories of digital health technologies, including:
    • Software as a Medical Device (SaMD),
    • Software in a Medical Device (SiMD),
    • and non-device digital tools such as Electronic Medical Records (EMRs), Laboratory Information Management Systems (LIMS), and Manufacturing Execution Systems (MES).
  • You can describe the emerging role of autonomous AI agents in medtech, pharma, and biotech, and critically assess their potential impact on product development, regulatory workflows, and compliance oversight.
  • You can interpret the regulatory requirements for AI-based medical technologies under the Proposed Regulatory Framework for Predetermined Change Control Plans (PCCP) by the FDA and the EU AI Act.
  • You can compare and contrast the regulatory approaches to AI in healthcare across major jurisdictions, including the United States (FDA), European Union (EU AI Act and MDR), and United Kingdom (UK MHRA), and assess their implications for global regulatory strategy.
  • You can access the regulatory challenges of AI model lifecycle management, including data quality, algorithm transparency, bias mitigation, real-world performance monitoring, and change control.
  • You are able to collaborate effectively with technical and clinical teams by interpreting key software development concepts (e.g., training data, validation, versioning) in the context of regulatory submissions and audits.
  • You apply regulatory principles to evaluate AI-enabled digital health products, identifying compliance risks and proposing mitigation strategies aligned with international standards (e.g., ISO 13485, IEC 62304, GxP).
  • You can analyze emerging regulatory strategies for novel AI and digital health technologies, including recent approvals, experimental oversight models (e.g., regulatory sandboxes and living labs) and anticipating future trends

Scope & duration

4 ECTS points
This is equivalent to roughly 100-120 working hours (incl. appr. 16-20 in person hours)

Start

The module takes place in fall term each year.

For next term, the module will be hold between 04.11.2026 and 20.12.2026.

You will have few on-site events and weekly assignments, such as reading, writing, presentation or short online webinars.
Please feel free to contact the School if you have any more detailed questions or are in need of exact dates.

Fee

This module can be attended as single course at a fee of CHF 4'200.-
👉 Contact the School if you are interested in this module as a single course.

Module leaders & lecturers

Prof. for MD Regulatory Science in the Faculty of Medicine at Dresden University of Technology

Stephen Gilbert

Guidance comes from Prof. Dr. Stephen Gilbert Professor for Medical Device Regulatory Science in the Faculty of Medicine at Dresden University of Technology. With a background in bioinformatics and regulatory affairs, he is uniquely positioned to connect clinical realities with technological and regulatory demands. His perspective shows how digital products can be developed in a way that is both safe and ready for regulatory approval.

Head of the Center for AI in Radiation Oncology at the University of Bern and Inselspital

Prof. Dr. Sara C. Brüningk

Teaching with respect to foundational concepts and limitations of AI is guided by Prof. Dr. Sara C. Brüningk, Head of the Center for AI in Radiation Oncology at the University of Bern and Inselspital. With a background in physics, computational biology, and biomedical data science, she is uniquely positioned to connect clinical challenges with technological innovation. Her perspective shows how artificial intelligence and mechanistic modeling can be harnessed to make therapies more precise, interpretable, and personalized.