Mind the Risk
Modern technology gives us increasing possibilities to diagnose and predict disease using DNA-analysis of tissue, cell-lines and blood samples. This makes individualized treatment and prevention of disease easier, but it also rasies questions and concerns when it comes to evaluating and dealing with genetic risk information, both as professional health care givers and as patients.
Mind the Risk: Managing genetic risk information
Biomedical research is constantly finding new ways to detect genetic variation and link the findings to diseases and to the effects of various drug treatments. The amount of information that it produces keeps increasing, but we are still not sure how to manage it.
There are pressing ethical concerns and a need to improve clinical practice. Mind the Risk is an international, multi-disciplinary research projet that runs over six years. Together, we will provide philosophical and conceptual framework that together with historical and socio-cultural analyses of concerns about risk information, empirical investigations of risk perceptions and preferences and ethical analyses may guide regulation and management of genetic and related risk information in various settings.
We are working to
- Develop a conceptual framework for genetic risk information and management.
- Assess perceptions and evaluations of genetic risks in different stakeholder groups
- Assess the ethical, psychological and social implications of the provision of risk information from genetic and related technologies.
- Explore new forms of communication and information, and develop tools to improve communication skills regarding genetic risk information
About Mind the Risk
Mind the Risk is a six year international network collaboration with scientists and researchers from Uppsala, Birmingham, Göttingen, Manchester, Milano and Stockholm funded by Riksbankens Jubileumsfond (The Swedish Foundation for Humanities and Social Sciences)
How precise should stratified medicine be?
The Manchester-based Mind The Risk research team have designed a model to help researchers understand how prescribing-algorithms to guide treatment with biologics in rheumatoid arthritis (RA) are valued by users (patients or potential patients).