Regenerative medicine is an emerging area of science that holds great promise for treating and even curing a variety of injuries and diseases. In cooperation with the FDA, the trans-NIH Regenerative Medicine Innovation Project (RMIP) was established by the 21st Century Cures Act to accelerate progress in the field of regenerative medicine by supporting clinical research on adult stem cells.
One goal of RMIP is to promote understanding of whether and how certain cell characteristics contribute to successful clinical outcomes. To accomplish this goal, RMIP-funded researchers are expected to provide representative samples of the source stem cells and clinical-grade stem cell product for characterization through the Regenerative Medicine Innovation Catalyst (RMIC) In-Depth Cell Characterization hub (IDCCH). Maximizing the value of these datasets by applying data standards and harmonizing data across RMIP studies is an essential step towards the goal.
The NHLBI BDC ecosystem has been selected as the data management and analysis platform for RMIP generated data. This platform will facilitate the aggregation of study data generated by multiple sources, processing the data through standardized workflows, and analysis. The DMC aids investigators in implementing recommended procedures, structure, implementation, and standards to create high quality interoperable datasets with documented provenance that are consistent and optimized for data access and FAIRness (Findable, Accessible, Interoperable and Re-usable). Implementing data standards will increase the interoperability of the datasets and facilitate efficient dataset combinations. Exact standards and associated metadata will vary by scientific area, study design, characteristics of the dataset and data type. In collaboration, the DMC, RMIP investigators, the IDCCH and RMIP stakeholders have developed recommended data standards, data structure, file formats and required metadata. Study documentation and metadata provide essential context surrounding the data generation to allow for appropriate interpretation of data and analysis results.
The DMC continues to provide resources and guidance to streamline this process. As you become familiar with BDC we encourage you to use this forum to provide insight and ask questions. If you need any assistance, please submit a help-desk ticket. Tickets are continuously monitored by our support staff, and responses are typically followed up on within one business day.
Jeran Stratford
Regenerative medicine is an emerging area of science that holds great promise for treating and even curing a variety of injuries and diseases. In cooperation with the FDA, the trans-NIH Regenerative Medicine Innovation Project (RMIP) was established by the 21st Century Cures Act to accelerate progress in the field of regenerative medicine by supporting clinical research on adult stem cells.
One goal of RMIP is to promote understanding of whether and how certain cell characteristics contribute to successful clinical outcomes. To accomplish this goal, RMIP-funded researchers are expected to provide representative samples of the source stem cells and clinical-grade stem cell product for characterization through the Regenerative Medicine Innovation Catalyst (RMIC) In-Depth Cell Characterization hub (IDCCH). Maximizing the value of these datasets by applying data standards and harmonizing data across RMIP studies is an essential step towards the goal.
The NHLBI BDC ecosystem has been selected as the data management and analysis platform for RMIP generated data. This platform will facilitate the aggregation of study data generated by multiple sources, processing the data through standardized workflows, and analysis. The DMC aids investigators in implementing recommended procedures, structure, implementation, and standards to create high quality interoperable datasets with documented provenance that are consistent and optimized for data access and FAIRness (Findable, Accessible, Interoperable and Re-usable). Implementing data standards will increase the interoperability of the datasets and facilitate efficient dataset combinations. Exact standards and associated metadata will vary by scientific area, study design, characteristics of the dataset and data type. In collaboration, the DMC, RMIP investigators, the IDCCH and RMIP stakeholders have developed recommended data standards, data structure, file formats and required metadata. Study documentation and metadata provide essential context surrounding the data generation to allow for appropriate interpretation of data and analysis results.
The DMC continues to provide resources and guidance to streamline this process. As you become familiar with BDC we encourage you to use this forum to provide insight and ask questions. If you need any assistance, please submit a help-desk ticket. Tickets are continuously monitored by our support staff, and responses are typically followed up on within one business day.