Abstract

Objective

This article describes a scalable, performant, sustainable global network of electronic health record data for biomedical and clinical research.

Materials and Methods

TriNetX has created a technology platform characterized by a conservative security and governance model that facilitates collaboration and cooperation between industry participants, such as pharmaceutical companies and contract research organizations, and academic and community-based healthcare organizations (HCOs). HCOs participate on the network in return for access to a suite of analytics capabilities, large networks of de-identified data, and more sponsored trial opportunities. Industry participants provide the financial resources to support, expand, and improve the technology platform in return for access to network data, which provides increased efficiencies in clinical trial design and deployment.

Results

TriNetX is a growing global network, expanding from 55 HCOs and 7 countries in 2017 to over 220 HCOs and 30 countries in 2022. Over 19 000 sponsored clinical trial opportunities have been initiated through the TriNetX network. There have been over 350 peer-reviewed scientific publications based on the network’s data.

Conclusions

The continued growth of the TriNetX network and its yield of clinical trial collaborations and published studies indicates that this academic-industry structure is a safe, proven, sustainable path for building and maintaining research-centric data networks.

Details

Title
A global federated real-world data and analytics platform for research
Author
Palchuk, Matvey B 1   VIAFID ORCID Logo  ; London, Jack W 2 ; Perez-Rey, David 3 ; Drebert, Zuzanna J 1 ; Winer-Jones, Jessamine P 1   VIAFID ORCID Logo  ; Thompson, Courtney N 1 ; Esposito, John 1 ; Brecht Claerhout 1 

 TriNetX, LLC , Cambridge, Massachusetts, USA 
 Thomas Jefferson University , Philadelphia, Pennsylvania, USA 
 Biomedical Informatics Group, Artificial Intelligence Department, Universidad Politécnica de Madrid , Madrid, Spain 
Publication year
2023
Publication date
Jul 2023
Publisher
Oxford University Press
e-ISSN
25742531
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3168347190
Copyright
© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.