Current Models of Medical Technology Development

Understand how innovative medical technologies move from early research concepts to clinical use. This module explores the development of digital, data-driven, and AI-enabled medical technologies, with a focus on design, validation, regulatory pathways, quality management, risk management, reimbursement, and adoption in healthcare systems.

Key Facts

Qualification

5 ECTS credits 
upon successful completion of the module exam

Course start

Spring 2027

Duration

tba

Course location

Online

Course format

Hybrid: synchronous and asynchronous study

Credit points

5 ECTS

Language

English

Course fee

€1,668

This module is designed for professionals who want to understand how innovative medical technologies are developed, validated, approved, and prepared for adoption in healthcare systems.

It is particularly suitable for:

• Professionals in medical technology, digital health, healthcare innovation, and product development
• Specialists working at the interface of engineering, clinical science, regulatory affairs, and quality management
• Professionals involved in digital and AI-enabled medical devices, software as a medical device, diagnostics, monitoring technologies, or clinical decision support
• Managers, project leads, and experts who want to better understand development pathways for complex and safety-critical medical technologies
• Professionals interested in how emerging technologies can be translated into regulated, clinically usable, and reimbursable healthcare solutions

The module is especially relevant for those who want to assess medical technology development not only from a technical perspective, but also in relation to clinical workflows, risk management, human factors, regulatory strategy, reimbursement, and adoption.

The module introduces key development areas in modern medical technology, including diagnostics, AI-enabled in vitro test interpretation, software as a medical device, disease management applications, remote monitoring, wearable health technologies, and outcomes-based care tracking applications.

Further topics include complex and safety-critical technologies such as proton therapy, MR-linac systems, AI decision support, brain–computer interfaces, AI-enabled robotic surgery, agentic medical AI models, and hospital-at-home care supported by advanced digital tools.

Curriculum at a Glance

Medical Technology Development: research concepts, product design, validation, approval, adoption, and reimbursement
Digital and AI-Enabled Technologies: diagnostics, software as a medical device, AI tools, disease management apps, remote monitoring, and wearables
Complex Clinical Systems: proton therapy, MR-linac systems, AI decision support, risk management, and tertiary hospital implementation
Human Factors & Quality: usability, safety, clinical effectiveness, quality management, and risk-management frameworks
Frontier Technologies: brain–computer interfaces, robotic surgery, agentic medical AI models, and hospital-at-home care

Content

The module covers current models of medical technology development, with a focus on digital, data-driven, and AI-enabled technologies. Students examine how innovation evolves across engineering, clinical science, regulatory affairs, quality management, and healthcare adoption.

A further component is the analysis of emerging digital health technologies and their role within larger technological ecosystems. Students explore how these technologies interact with patient data, clinical workflows, external digital platforms, and healthcare delivery models.

The module also addresses high-risk and safety-critical clinical technologies. Students examine how engineering decisions are connected with regulatory, quality management, and risk-management frameworks in tertiary hospital settings.

Qualifications

Participants who successfully complete the module will be awarded 5 ECTS points. The credit points are awarded after passing the module examination.

The general admission requirements set out in the examination regulations must be met. In preparation for face-to-face events, literature recommendations may be provided. The content of this literature may be assumed as prior knowledge or should be acquired during the module.