AI, Regulatory Affairs & Transformation in Medical Technology (MBA)

Module Coordinator: to be announced
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Introduce students to scientific methods, research, statistics, and academic writing, preparing them to independently conduct and evaluate research in social sciences and medical technology contexts.

Key Content:

1. Scientific Working – research process, evaluating scientific work.
2. Research Methods – qualitative and quantitative social research.
3. Statistics – fundamentals, descriptive stats, probability, inductive stats, data preparation.
4. Literature Research & Academic Writing – define topics, structure papers, find and evaluate sources, present results.

Module Coordinator: to be announced
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Prepare students to lead digital transformation initiatives in healthcare and medical technology by developing vision, adaptability, and evidence-based strategy skills.

Key Content:

1. Leadership vs. Management – transformational leadership, empowerment, collaboration.
2. Digital Transformation – integrating technology, AI, and organizational culture.
3. Tools & Methods – OKRs, agile approaches, strategic foresight.
4. Challenges – resistance to change, fragmented digital capabilities, complexity management.
5. Self-Assessment – evaluating personal leadership style and development paths.

Module Coordinator: To be announced
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Introduce students to how healthcare systems operate, how digital technologies integrate into workflows, and how digital transformation shapes care delivery across Europe. Focus on practical, ethical, and economic factors affecting adoption.

Key Content:

1. Healthcare Systems & Workflows: Organisation of care, varying levels of digitalisation, workflow integration.
2. Digital Tools: Electronic health records (EHRs), telemedicine, AI decision support, wearable devices; benefits and limitations.
3. Digital Transformation Challenges: Ethical considerations, organisational resistance, infrastructure limits, reimbursement models, economic and political context.
4. Case Studies & Comparisons: Minimally, typically, and highly digitised EU systems; stakeholder perspectives (patients, clinicians, managers, policymakers, industry).
5. Evaluation Skills: Analyse real-world examples, assess barriers and opportunities, and understand context-dependent success factors.

Module Coordinator: To be announced
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Provide students with a clear understanding of how innovative medical technologies develop from research to clinical use, emphasizing the technical, regulatory, clinical, and commercial factors that influence success. Introduces both low-risk digital health tools and high-risk, complex hospital technologies, including AI-enabled systems.

Key Content:

1. Medical Technology Development: From early concepts to clinical adoption, including product design, validation, approval, and integration into health systems.
2. Digital & AI Health Technologies: Diagnostics, SaMD, wearable/home monitoring, disease management apps, digital therapeutics, and predictive tools.
3. High-Risk Clinical Systems: Radiotherapy (proton therapy), MR-linac, AI decision support—highlighting regulatory, quality, and risk-management frameworks.
4. Human-Factors & Usability: Ensuring safety, clinical effectiveness, and usability in digital and AI-enabled devices.
5. Emerging Frontier Technologies: Brain–computer interfaces, AI robotics, agentic AI models, hospital-at-home care.
6. Interoperability & Ecosystems: Integration of technologies, clinical workflow implications, ethical, economic, and regulatory considerations.
7. Innovation Strategy: Designing development and regulatory strategies aligned with technology adoption pathways.

Module Coordinator: Juliane Wober
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Provide students with a practical and critical understanding of medical device regulatory frameworks, focusing on the EU (MDR, IVDR, AI Act), their impact on innovation, and the structure of regulatory affairs and quality management in companies.

Key Content:

1. EU Regulatory Frameworks – structure, requirements, clinical evidence, and challenges.
2. Regulatory Affairs & Product Development – company organization, strategies, and the role of quality management and risk assessment across devices, software, diagnostics, and AI.
3. Software & High-Risk Devices – life-cycle processes, benefit–risk analysis, in-house development considerations.
4. International Perspectives – US FDA comparison, global harmonisation, regulatory trends, and barriers for startups.
5. Critical Analysis – regulatory burden, impact on competitiveness, digitalisation, and innovation.
6. Practical Application – develop implementation strategies in companies based on technology and business needs.

Module Coordinator: Prof. Dr. Stephen Gilbert
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Provide students with a practical and critical understanding of how digital and AI-enabled technologies are transforming healthcare delivery. Focus is on opportunities, constraints, ethical considerations, and the integration of AI into clinical, operational, and population-health contexts.

Key Content:

• AI & Digital Health Technologies: Telemedicine, predictive analytics, AI-assisted diagnostics, large language models, agentic AI, wearables, virtual patients, digital twins, and FemTech applications.
• Healthcare Integration: How technologies are applied in hospitals, home care, and population-health management, improving personalisation, efficiency, and patient engagement.
• Frameworks & Governance: Development of technology-enabled, collaborative, and ethically aligned AI frameworks for oversight, safety, and clinical integration.
• Risks & Challenges: Patient privacy, algorithmic bias, clinician workload, safety considerations, professional autonomy, and unintended consequences.
• Regulatory & Economic Context: Health technology assessment, reimbursement, return-on-investment, evidence generation, and regulatory approaches for AI-driven tools.
• Critical Analysis: Evaluate promises vs. limitations of digital transformation, including interoperability, data governance, and ethical constraints.

Module Coordinator: Prof. Dr. Stephen Gilbert
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Provide students with a clear understanding of how digital and AI-driven technologies are transforming medical device development, from design and testing to post-market activities, including regulatory, quality, and safety considerations.

Key Content:

• AI & Digital Technologies in Device Development – impact on design, simulation, testing, and lifecycle management; connected and automated workflows.
• AI-Assisted Software Development – LLM-assisted coding, low-code/no-code approaches, regulatory constraints, and opportunities.
• Digital Clinical Studies – fully remote studies, embedded trials, placebo-device designs, and regulatory implications.
• Quality & Risk Management – regulatory frameworks, pre-determined change plans (PCPs), algorithmic oversight, and monitoring for AI-enabled devices.
• Living Labs & Real-World Evaluation – practical testing environments for innovation and evidence generation.
• Critical Perspective – assess benefits, limitations, and challenges of AI integration in medical technology.

Module Coordinator: Prof. Dr. Stephen Gilbert
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Introduce students to the digital and AI transformation of regulatory and quality-management processes in medical devices. Focus on how emerging technologies reduce documentation burden, support regulatory intelligence, enhance post-market surveillance, and shape future conformity-assessment workflows.

Key Content:

• Digital & AI Tools in Regulatory Processes: AI-assisted regulatory submissions, risk assessment, post-market surveillance, and computer-system validation.
• Quality Management Systems (QMS): Digital QMS platforms, regulatory information management, and evolving regulatory ontologies.
• Conformity Assessment: Current AI applications, simulation and model-based evidence, future scenarios for 2040.
• Innovation vs. Oversight: SMART standards, regulatory sandboxes, assurance case-based risk assessment, and market surveillance analytics.
• Practical Examples: Real-world applications, opportunities, and limitations of digital and AI-enabled regulatory tools.

Module Coordinator: Prof. Dr. Stephen Gilbert
Duration: 1 semester
Credit Points: 5 ECTS

Purpose:
Equip future healthcare leaders with foundational technology competencies to make strategic decisions in digital health, AI-enabled systems, and health-IT environments. Focuses on understanding, not deep technical specialization.

Key Content:

• Core Digital Technologies: Data literacy, cybersecurity, cloud computing, interoperability, AI fundamentals, and ethical AI application.
• Health-IT Systems: Electronic health records, telematics infrastructures, FHIR/SMART standards, wearables, apps, and wireless communication.
• Technology Roles in Healthcare: Product owners, system architects, DevSecOps specialists, data scientists, clinical AI administrators, IT security leaders; insight into team collaboration and responsibilities.
• Practical Understanding: How digital systems operate, interconnect, and are safely managed; examples like German electronic patient file and OpenEHR models.

Module Coordinator: Prof. Dr. Stephen Gilbert
Duration: 4 months (master’s thesis) + ~4 weeks (colloquium)
Credit Points: 15 ECTS

Purpose:
Enable students to independently research and develop a complex topic within their field, apply scientific methods, and present and defend results in a structured academic format.

Key Content:

• Master’s Thesis – independently select and develop a topic in consultation with the supervisor; create an exposé for registration with the examination board.
• Scientific Work – apply theoretical, analytical, and methodological skills to derive new knowledge.
• Interdisciplinary Assessment – evaluate relationships, design theories, and propose practical solutions.
• Colloquium – present and defend thesis findings; justify methods and conclusions.

This MBA is one of the few programmes worldwide that systematically combines artificial intelligence, digital medical technologies, and international regulatory frameworks. It prepares professionals to lead innovation while mastering requirements such as the EU AI Act, MDR, and IVDR.

The MBA is designed for experienced professionals and emerging leaders from healthcare delivery, the MedTech industry, regulatory authorities, and health organizations who want to take on strategic roles in digital transformation and AI-enabled innovation.

Yes. The MBA follows a coherent, lifecycle-based learning journey, covering the entire pathway—from healthcare system analysis and digital maturity, through product development and regulatory approval, to quality management and future care models.

The program is a modular, part-time, hybrid format over 4 semesters (about 24 months), combining online learning with on-site block sessions in Dresden. This structure offers maximum flexibility while maintaining strong personal interaction and support.

The MBA awards 60 ECTS credits in total. The workload is structured across four semesters with a mix of self-study, online sessions, on-site workshops, and the master’s thesis, requiring roughly 1,500–1,800 hours overall.

You will gain deep practical insight into key European and international frameworks, including the MDR, IVDR, and the EU AI Act, as well as quality and compliance requirements for digital and AI-based medical technologies.

The programme places a strong emphasis on modern leadership and strategic decision-making, equipping you to lead AI-driven transformation in a complex and rapidly evolving VUCA healthcare environment.

Participants come from diverse roles such as regulatory affairs, quality management, product development, compliance, legal affairs, health technology assessment, clinical innovation, consulting, and healthcare system leadership—creating a rich ecosystem for peer learning.

Highly practice-oriented. Modules integrate participants’ professional experience through case studies, project work, interactive workshops, simulations, and real-world regulatory and innovation scenarios, supported by experts from academia and industry.

Graduates are prepared for strategic leadership roles in areas such as digital health innovation, AI-enabled medical device development, regulatory strategy, quality and compliance management, transformation projects, and healthcare technology leadership.

You can request detailed programme information or schedule a personal consultation via DIU's Study Advisory team. The team will guide you through admission requirements, timelines, and next steps. Get in contact with us: studyadvisory@di-uni.de