SBRI19010U Ethics in Translational Medicine II: Participant Related Issues
BRIDGE - Translational Excellence Programme
Translational research presents new organizational, ethical, and legal challenges. Equally, it calls for collaboration and communication between different fields of omics, big data analytics and drug development and attention to the respect for involved participants. A number of dialogical situations in the translational journey of knowledge as well as the ethical questions pertaining to the complex nature of public-private partnerships in health will be identified and discussed in Ethics II.
The course is divided into three major subject areas. The first reflects the dilemma between how to protect private data and how to exchange data; the second reflects the ethics of big data as a public good: Which public? Which good? And the third reflects the responsibilities regarding how personal data ferry from research to clinic and back to research.
To understand the moral and legal component in translational medical research by:
- Acquiring competencies that will help identify, assess and resolve ethical and legal questions and provide an analytical framework of translational movements between different settings
- Ascertaining the interrelationship between ethical issues and the production of knowledge through omics, big data and pharma
- Developing dialogical competencies that will support the collaborative effort in generating data, informing clinical therapeutics and improving patient care
On completion of the course, the participants should be able to:
- Understand the relationship between science and society
- Discuss underlying ethical questions in omics, big data and drug development
- Use analytical tools and obtain practical experience with identifying, assessing and resolving ethical and legal questions
- Critically access and discuss complex ethical issues
- Master dialogical methods that will support collaboration across fields in translational research
Mittelstadt & Floridi (eds): The Ethics of Biomedical Big Data (2016).
Sheila Jasanoff (ed): States of Knowledge. The co-production of science and social order (2004).
Ethics and Epistemology in Big Data Research" (2017), in Bioethical Inquiry, 14: 489-500
Williams et al.: "Omics Research Ethics Considerations" (2018), in Nursing Outlook 66: 386-393.
Metcalf et al.: "Where are the human subjects in Big Data research? The emerging ethics divide" (2016), in Big Data and Society January-July: 1-14.
Knoppers et al.: "A human rights approach to an international code of conduct for genomic and clinical data sharing" (2014), in Human Genetics, 133: 895-903.
• Focus is on a mentored hands-on experience with postgrads' specific ethical interests and challenges within their own work of moving between basic science and clinical settings
• The course will consist of presentations, small group discussions, pair exercises, case-based work and master class elements
• Individual reading
- Theory exercises
- Exam Preparation
Automatic registration upon appointment in the Translational Excellence Programme
- 0 ECTS
- Type of assessment
- Continuous assessmentPortfolio• Attendance
• Active participation
• Postgrads will do three exercises (one per day of course) and store in a log book that is handed in for peer supervision
- Exam registration requirements
Participants are automatically registered for the Examination upon course registration.
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
Criteria for exam assesment
- Knowledge of the interrelationship between science, ethics and society
- Ability to identify, assess and resolve ethical and legal issues in translational medicine
- Ability to discuss complex ethical issues and collaborate across fields