AI-DRIVEN DATA INTEGRATIONS AND AUTOMATIONS FOR CLINICAL RESEARCH OPERATIONS (CRO)

The complexity of modern clinical research operations (CRO) necessitates advanced solutions for managing vast datasets, streamlining workflows, and ensuring compliance with stringent regulatory requirements. AI-driven data integration and automation technologies have emerged as key enablers of efficiency and accuracy in CRO, facilitating real-time data synchronization, workflow automation, and predictive analytics. This comprehensive article examines the current challenges in clinical research operations, explores AI-driven solutions for data integration, evaluates automation technologies, and assesses the benefits of AI integration in CRO. The article also discusses critical implementation considerations, including technical infrastructure requirements and change management strategies, while highlighting how AI technologies transform traditional clinical research processes through improved operational efficiency, enhanced data quality, and streamlined regulatory compliance

Publication Details

Journal
SPIRE - Sciences Po Institutional REpository
Published
2024-12-10
DOI
https://doi.org/10.5281/zenodo.14348930
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-DRIVEN DATA INTEGRATIONS AND AUTOMATIONS FOR CLINICAL RESEARCH OPERATIONS (CRO)

SPIRE - Sciences Po Institutional REpository
Artificial Intelligence in Healthcare and Education
article

AI-DRIVEN DATA INTEGRATIONS AND AUTOMATIONS FOR CLINICAL RESEARCH OPERATIONS (CRO)

article en

Abstract

The complexity of modern clinical research operations (CRO) necessitates advanced solutions for managing vast datasets, streamlining workflows, and ensuring compliance with stringent regulatory requirements. AI-driven data integration and automation technologies have emerged as key enablers of efficiency and accuracy in CRO, facilitating real-time data synchronization, workflow automation, and predictive analytics. This comprehensive article examines the current challenges in clinical research operations, explores AI-driven solutions for data integration, evaluates automation technologies, and assesses the benefits of AI integration in CRO. The article also discusses critical implementation considerations, including technical infrastructure requirements and change management strategies, while highlighting how AI technologies transform traditional clinical research processes through improved operational efficiency, enhanced data quality, and streamlined regulatory compliance

SPIRE - Sciences Po Institutional REpository
Industry, innovation and infrastructure
Openalex Percentile: Top 66%
Artificial Intelligence in Healthcare and Education
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