Evidence map›Paper›PMID 33118143›Full record

ArticleTherapeutic innovation & regulatory science2021

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.

Kevin Nam, Kay Larholt, Gigi Hirsch, Paul Beninger, David Fritsche, Diane Shoda, John Ferguson, Florence T Bourgeois, Donna Palmer, Karen Katz and 1 more

Abstract read
In one paragraph

Article in Therapeutic innovation & regulatory science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kevin NamMIT Lincoln Laboratory, Massachusetts Institute of Technology, 244 Wood St., Lexington, MA, 02421, USA. kevin.nam@ll.mit.edu.ORCID 0000-0001-7881-0933
Kay LarholtMIT Center for Biomedical Innovation, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building E19-604, Cambridge, MA, 02139, USA.
Gigi HirschMIT Center for Biomedical Innovation, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building E19-604, Cambridge, MA, 02139, USA.
Paul BeningerPublic Health & Community Medicine, Tufts University School of Medicine, Boston, USA.
David FritscheMIT Center for Biomedical Innovation, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building E19-604, Cambridge, MA, 02139, USA.
Diane ShodaGreyscaling LLC, 3722 Las Vegas Blvd S, Unit 2111, Las Vegas, NV, 89158, USA.
John FergusonPharmacovigilance Specialty Care, Sanofi-Genzyme Business Unit, 50 Binney St., Cambridge, MA, 02142, USA.
Florence T BourgeoisMIT Lincoln Laboratory, Massachusetts Institute of Technology, 244 Wood St., Lexington, MA, 02421, USA.
Donna PalmerMIT Center for Biomedical Innovation, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building E19-604, Cambridge, MA, 02139, USA.
Karen KatzFoCUS Project, NEWDIGS, MIT Center for Biomedical Innovation, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building E19, Cambridge, MA, 02139, USA.
Matt W CourtneyFoCUS Project, NEWDIGS, MIT Center for Biomedical Innovation, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building E19, Cambridge, MA, 02139, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData sharing among stakeholders in the development, access, and use of drug therapies is critical but the current system and process are inefficient.

methodsWe take a Systems Engineering approach with a realistic use case to propose a scalable design for multi-stakeholder data sharing.

resultsWe 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.

conclusionWe 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.

Indexed as

BenchmarkingInformation DisseminationHumansGene and cell therapiesMulti-stakeholder sharingPayersRegulatory agenciesScalable data architectureSystems engineering

Identifiers

PMID33118143
PMCPMC7864828

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.