Dynamic Dossier in the Cloud: A Sociotechnical Architecture for a Real-Time and Metrics-Based Data Tracking System with Gene and Cell Therapies as a Case Study
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43441_2020_Article_227.pdf
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1.26 MB
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Author(s)
Nam, Kevin
Larholt, Kay
Hirsch, Gigi
Beninger, Paul
Fritsche, David
Shoda, Diane
Ferguson, John
Bourgeois, Florence T.
Palmer, Donna
Katz, Karen
Date Issued
October 2020
Journal
Therapeutic Innovation & Regulatory Science
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
Abstract
Background
Data sharing among stakeholders in the development, access, and use of drug therapies is critical but the current system and process are inefficient.
Methods
We take a Systems Engineering approach with a realistic use case to propose a scalable design for multi-stakeholder data sharing.
Results
We make three major contributions to the drug development and healthcare communities: first, a methodology for developing a multi-stakeholder data sharing system, with its focus on high-level requirements that influence the design of the system architecture and technology choice; second, the development of a realistic use case for long-term patient and therapy data tracking and sharing in the use of potentially curative and durable gene and cell therapies. Further, a bridge for the ‘awareness gap’ was found between the payer (Payer is organization which takes care of financial and operational aspects (which include insurance plans, provider network) of providing health care to US citizens. Or refer to health care insurers.) and the regulator communities by illustrating the common data tracking needs, which highlights the need for coordinated data activities; and third, a proposed system architecture for scalable, multi-stakeholder data sharing. Next steps are briefly discussed.
Conclusion
We present a system design for multiple stakeholders such as the payer, the regulator, the developer (drug manufacturer), and the healthcare provider to share data for their decision-making. The stakeholder community would benefit from collaboratively moving the system development proposal forward for efficient and cost-effective data sharing.
MIT Department
Lincoln Laboratory
Massachusetts Institute of Technology. Center for Biomedical Innovation
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s43441-020-00227-y
