Do patients and research subjects have a right to receive their genomic raw data? An ethical and legal analysis.

BACKGROUND: As Next Generation Sequencing technologies are increasingly implemented in biomedical research and (translational) care, the number of study participants and patients who ask for release of their genomic raw data is set to increase. This raises the question whether research participants and patients have a legal and moral right to receive their genomic raw data and, if so, how this right should be implemented into practice. METHODS: In a first step we clarify some central concepts such as "raw data"; in a second step we sketch the international legal framework. The third step provides an extensive ethical analysis which comprehends two parts: an evaluation of whether there is a prima facie moral right to receive one's raw data, and a contextualization and discussion of the right in light of potentially conflicting interests and rights of the data subject herself and third parties; in a last fourth step we emphasize the main practical consequences of the ethical analyses and propose recommendations for the release of raw data. RESULTS: In several legislations like the new European General Data Protection Regulation, patients do in principle have the right to receive their raw data. However, the procedural implementation of this right and whether it involves genetic counselling is at the discretion of the Member States. Even more questions remain with respect to the research context. The ethical analysis suggests that patients and research subjects have a moral right to receive their genomic raw data and addresses aspects which are also of relevance for the legal discussion such as the costs of release of raw data and its impact on academic freedom. CONCLUSION: Taking into account the specific nature and implications of genomic raw data and the contexts of research and health care, several concerns and potentially conflicting interests of the data subjects themselves and involved researchers, physicians, biomedical institutions and relatives arise. Instead of using them to argue in favor of restrictions of the data subjects' legal and moral right to genomic raw data, the concerns should be addressed through provision of information and other measures. To this end, we propose relevant recommendations.

Applying systems biology to biomedical research and health care: a précising definition of systems medicine.

BACKGROUND: Systems medicine has become a key word in biomedical research. Although it is often referred to as P4-(predictive, preventive, personalized and participatory)-medicine, it still lacks a clear definition and is open to interpretation. This conceptual lack of clarity complicates the scientific and public discourse on chances, risks and limits of Systems Medicine and may lead to unfounded hopes. Against this background, our goal was to develop a sufficiently precise and widely acceptable definition of Systems Medicine. METHODS: In a first step, PubMed was searched using the keyword "systems medicine". A data extraction tabloid was developed putting forward a means/ends-division. Full-texts of articles containing Systems Medicine in title or abstract were screened for definitions. Definitions were extracted; their semantic elements were assigned as either means or ends. To reduce complexity of the resulting list, summary categories were developed inductively. In a second step, we applied six criteria for adequate definitions (necessity, non-circularity, non-redundancy, consistency, non-vagueness, and coherence) to these categories to derive a so-called précising definition of Systems Medicine. RESULTS: We identified 185 articles containing the term Systems Medicine in title or abstract. 67 contained at least one definition of Systems Medicine. In 98 definitions, we found 114 means and 132 ends. From these we derived the précising definition: Systems Medicine is an approach seeking to improve medical research (i.e. the understanding of complex processes occurring in diseases, pathologies and health states as well as innovative approaches to drug discovery) and health care (i.e. prevention, prediction, diagnosis and treatment) through stratification by means of Systems Biology (i.e. data integration, modeling, experimentation and bioinformatics). Our study also revealed the visionary character of Systems Medicine. CONCLUSIONS: Our insights, on the one hand, allow for a realistic identification of actual ethical as well as legal issues arising in the context of Systems Medicine and, in consequence, for a realistic debate of questions concerning its matter and (future) handling. On the other hand, they help avoiding unfounded hopes and unrealistic expectations. This especially holds for goals like improving patient participation which are intensely debated in the context of Systems Medicine, however not implied in the concept.