Data Harmonization, Standardization, and Collaboration for Diabetic Retinal Disease (DRD) Research: Report From the 2024 Mary Tyler Moore Vision Initiative Workshop on Data

The 2024 Mary Tyler Moore Vision Initiative (MTM Vision) Workshop on Data convened to discuss best practices and specific considerations for building a comprehensive, shareable MTM Vision data lake. The workshop aimed to accelerate the development of new indications, therapies, and regulatory pathways for diabetic retinal disease (DRD) by standardizing and harmonizing clinical data and ocular 'omics analyses. Standardization of data collection, the use of common data elements, and data interoperability were emphasized, alongside federated learning approaches to promote data sharing and collaboration while maintaining data privacy and security. The integration of molecular data with other multimodal data types was recognized as a promising strategy for leveraging machine learning and AI approaches to advancing therapeutics development and improving treatment outcomes for DRD patients. Partnerships with entities such as the National Eye Institute, part of the National Institutes of Health, foundations, and industry were deemed vital for the successful implementation of these initiatives.

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Publication Details

Journal
Translational Vision Science & Technology
Published
2024-10-03
DOI
https://doi.org/10.1167/tvst.13.10.4
Citations
3
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
1.21

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article

Data Harmonization, Standardization, and Collaboration for Diabetic Retinal Disease (DRD) Research: Report From the 2024 Mary Tyler Moore Vision Initiative Workshop on Data

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3 citations
Translational Vision Science & Technology
Retinal Imaging and Analysis
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article

Data Harmonization, Standardization, and Collaboration for Diabetic Retinal Disease (DRD) Research: Report From the 2024 Mary Tyler Moore Vision Initiative Workshop on Data

Jeffrey M. Sundstrom, Jennifer K. Sun, Aaron Lee, Kerry Goetz, S. Robert Levine, Amitha Domalpally, Brian L. VanderBeek, Dorene S. Markel, Ward Fickweiler
article en
3 citations

Abstract

The 2024 Mary Tyler Moore Vision Initiative (MTM Vision) Workshop on Data convened to discuss best practices and specific considerations for building a comprehensive, shareable MTM Vision data lake. The workshop aimed to accelerate the development of new indications, therapies, and regulatory pathways for diabetic retinal disease (DRD) by standardizing and harmonizing clinical data and ocular 'omics analyses. Standardization of data collection, the use of common data elements, and data interoperability were emphasized, alongside federated learning approaches to promote data sharing and collaboration while maintaining data privacy and security. The integration of molecular data with other multimodal data types was recognized as a promising strategy for leveraging machine learning and AI approaches to advancing therapeutics development and improving treatment outcomes for DRD patients. Partnerships with entities such as the National Eye Institute, part of the National Institutes of Health, foundations, and industry were deemed vital for the successful implementation of these initiatives.

Translational Vision Science & TechnologyVol. 13(10)
National Institutes of Health (US), Michigan Department of Education (US), University of Wisconsin–Madison (US), Harvard University (US), Penn Presbyterian Medical Center (US), Moore College of Art and Design (US), University of Washington (US), University of Michigan (US), National Eye Institute (US), University of Pennsylvania (US), Penn State Milton S. Hershey Medical Center (US)
Research to Prevent Blindness, Regeneron Pharmaceuticals, Carl Zeiss Meditec AG, Santen, U.S. Food and Drug Administration, Genentech
Openalex Percentile: Top 20%
Retinal Imaging and Analysis
1.21
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