Data-fitness-assessment-to-improve-R-and-D-outcomes

    Data fitness assessment to improve clinical outcomes

    A strategic exercise that examines data governance, data quality, validation, and verification, and data visibility and accessibility.

    Data-driven clinical research to power scientific discovery and innovation

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    Life sciences clinical research is becoming increasingly data driven. Data governance, data quality, validation, verification, and, most importantly, how data takes shape in terms of data visibility and accessibility is becoming increasingly relevant to life sciences clinical research. Life sciences companies are implementing effective clinical data management strategies that harness the FAIR (findable, accessible, interoperable, reusable) guiding principles for scientific data management and stewardship. These include:

    • identifying data consistency, quality, and visibility gaps
    • harnessing the framework of process and governance to improve clinical data management
    • ensuring regulatory compliance of the data sets through its journey

    Catalyze the discovery and development of innovative treatments by effectively exploiting big data using modern technologies such as artificial intelligence and machine learning.

    Data fitness assessment for next-gen clinical data management

    Service offering

    Key results

    Business outcomes

    • Sources and complexity
    • Aggregation and building a semantic layer
    • Data governance and quality
    • Future state architecture
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    Comprehensive report on data governance and quality

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    SWOT analysis to prioritize better data visibility

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    Steps to adopt data standards (e.g., CDISC)

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    Roadmap for next-gen clinical data management

    Clinical program access

    • Diversity in clinical trials without geographic barriers, with focus on developing countries.

    Analyzing R&D strategy

    • Global regulatory and compliance insight for fast regulatory approval.

    Agile clinical development

    • Flexible, configurable, and dynamic approach to clinical trials.
    • Real-time access to all study data through controls to ensure the utmost protection of participant safety and data integrity.

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