Image via WikipediaThe goal of “personalized medicine” relies upon defining the genetic variation responsible for disease susceptibility and response to therapy [1]. For most common human diseases, the contribution of a single sequence variant to disease susceptibility is typically small, and can only be detected with data from large numbers of people [2]. Practically, this necessitates collaboration among investigators who either have DNA and phenotypic information previously collected, or have access to populations from which to recruit participants. It also requires that data be shared among the collaborators. Modern bioinformatics platforms have the capacity to combine datasets and store them for re-analysis. This is scientifically advantageous since it makes possible studies with enhanced validity in a cost-effective fashion. However, this data storage can complicate the already vexing practical, scientific, and ethical issues associated with gene and tissue banks. Research participants' data may have been collected without authorization that meets today's standards for informed consent. Research participants may not have consented to participation in genetics research in general, to inclusion in genetics databases specifically, or to use of their samples in genetic analyses that were unanticipated, unknown, or nonexistent at the time samples were collected [3]. Participants who consented to the collection of their data for use in a particular study, or inclusion in a particular database, may not have consented to “secondary uses” of those data for unrelated research, or use by other investigators or third parties [4]. There is concern that institutional review boards (IRBs) or similar bodies will not approve of the formation of aggregated databases or will limit the types of studies that can be done with them, even if those studies are believed by others to be appropriate, since there is a lack of consensus about how to deal with re-use of data in this manner............read more inn PLoS Medicine.14 octubre, 2008
Ethical and Practical Issues Associated with Aggregating Databases
Image via WikipediaThe goal of “personalized medicine” relies upon defining the genetic variation responsible for disease susceptibility and response to therapy [1]. For most common human diseases, the contribution of a single sequence variant to disease susceptibility is typically small, and can only be detected with data from large numbers of people [2]. Practically, this necessitates collaboration among investigators who either have DNA and phenotypic information previously collected, or have access to populations from which to recruit participants. It also requires that data be shared among the collaborators. Modern bioinformatics platforms have the capacity to combine datasets and store them for re-analysis. This is scientifically advantageous since it makes possible studies with enhanced validity in a cost-effective fashion. However, this data storage can complicate the already vexing practical, scientific, and ethical issues associated with gene and tissue banks. Research participants' data may have been collected without authorization that meets today's standards for informed consent. Research participants may not have consented to participation in genetics research in general, to inclusion in genetics databases specifically, or to use of their samples in genetic analyses that were unanticipated, unknown, or nonexistent at the time samples were collected [3]. Participants who consented to the collection of their data for use in a particular study, or inclusion in a particular database, may not have consented to “secondary uses” of those data for unrelated research, or use by other investigators or third parties [4]. There is concern that institutional review boards (IRBs) or similar bodies will not approve of the formation of aggregated databases or will limit the types of studies that can be done with them, even if those studies are believed by others to be appropriate, since there is a lack of consensus about how to deal with re-use of data in this manner............read more inn PLoS Medicine.
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