FAIR4Clin

Version 1.0 2023-01. - Licence: CC 4.0.

Contributors

Outline

Introduction

• Challenges for Clinical data and why this guide will help

  • Who this guide is designed for

  • Context of this guide: Clinical Data Challenges and Opportunities

  • Purpose of this guide: From Awareness to Making Pragmatic Choices 

  • Scope of this guide

  • Clinical study data can be big!

  • A multiplicity of clinical data types

• How the principles FAIR can bring value to Clinical data

  • Realising value for clinical trial data

  • Realising value from Real World Data

Metadata

• Clinical study design and FAIR implementation

• Clinical study data process through the FAIR lens

  • Planning and preparation of the study

  • Approvals, permissions and agreements

  • Study conduct and data collection 

  • Data curation / harmonisation processes

  • Analysis of data

  • Reporting

  • Data follow-up activities 

• Common Data Models for clinical data

  • CDISC

  • OHDSI

  • FHIR®

• Shared model of clinical study design and outcome

  • The BRIDG initiative

  • Semantic integration with Semantic Web standards

Application

• Clinical Trial Registries

  • Background

  • FAIR assessment of clinical trial registries

  • Clinical Real World Data

  • Other registries and efforts

• Quality and Governance of Clinical data

  • Quality of clinical data and metadata

  • Clinical data governance at the study level

• Infrastructure, training and culture for clinical FAIR data

  • Infrastructure

  • Education and training

  • Data-centric culture and the FAIR mindset