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FAIR

Webinar

Delivering Data Driven Value

BMS Enabled FAIR Practices: R&D Information Landscape

Bristol Myers Squibb is proud to share a proposal to standardize our data and information models. The artifacts introduced today serve as foundational knowledge of Research and Development and attempt to capture factual and tacit knowledge in this space.

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Journal Article

Delivering Data Driven Value Harnessing AI To Expedite R&D

Bioassays Have An Integration Problem: Collaboration Will Be Key To Making Them FAIR

Whilst life science companies have come to recognize data as their greatest asset, it is also their greatest challenge. Bioassay protocols are one such example where legacy data management systems are holding R&D back, and where adopting the FAIR (Findable, Accessible, Interoperable, Reusable) principles would improve the usability of the data.

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Webinar

Delivering Data Driven Value

How FAIR Is My Data: The FAIRe(nough) Benchmark at AstraZeneca

The FAIRe(nough) benchmark has been developed in AZ with a focus on integration of data products and systems against a specific context or use case. Providing both high- and low-level assessment metrics, the benchmark is an essential enabler for anyone facing a data integration and FAIRification project.

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Journal Article

Delivering Data Driven Value

Maximizing Data Value for Biopharma through FAIR and Quality Implementation: FAIR Plus Q

Despite considerable progress, the transformative shift from an application-centric to a data-centric perspective, enabled by FAIR implementation, remains very much a work in progress on the ‘FAIR journey’. In this review, we consider use cases for FAIR implementation.

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Webinar

Delivering Data Driven Value

Expert Panel Discussion: Ontologies and FAIR

We have assembled a panel of experts from Scibite, Pfizer, GSK and Astrazeneca to discuss why it’s valuable to leverage the interplay of ontologies and FAIR, and what a difference it can make in R&D decision making.

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Best Practices Guides

Delivering Data Driven Value

FAIR4Clin Implementation Guide

This guide was created and is maintained as part of the FAIR implementation project by the Pistoia Alliance and consists of three parts: Introduction, Metadata and Application.

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Webinar

Delivering Data Driven Value

Enhancing Access to Clinical Trial Data for Secondary Use

At the Pistoia Alliance, we are exploring how the FAIRification of such data, along with advanced analytics including AL/ML/NLP powered systems can be used to access/share/reuse patient data from historical clinical trials.

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Webinar

Delivering Data Driven Value

Collaborative Observational Health Research Using OHDSI Methods

This webinar will present clinical data standardization and harmonization using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), standard vocabularies, and standardized analytics.

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Webinar

Delivering Data Driven Value

The Architecture of FAIR Data Platforms: COLID and EDISON at Bayer and Roche

Bayer and Roche are leading biopharmaceutical companies, which each have a diverse and distributed ecosystem of platforms to manage data and metadata used by different parts of each organization. This webinar will present the technical details for each platform.

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Webinar

Delivering Data Driven Value

Collaborative Observational Health Research Using OHDSI Methods

This webinar will present clinical data standardization and harmonization using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), standard vocabularies, and standardized analytics.

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Journal Article

Delivering Data Driven Value

Implementing the FAIR Data Principles is Now a Critical Endeavour

In this article, Ian Harrow and Thomas Liener, Consultant Project Managers at The Pistoia Alliance explain the importance of the FAIR (Findable, Accessible, Interoperable, Reusable) data principles, factors currently limiting their implementation and the potential benefits should these challenges be overcome.

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Webinar

Delivering Data Driven Value

FAIR Data: From Principles To Best Practices

The FAIR Data Principles are a hot topic in research data management. Everybody wants to play FAIR, but how can principles become best practices? This webinar discusses the production and use of research data that is Findable, Accessible, Interoperable, and Reusable (FAIR) and what it means for the research ecosystem.

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