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Redefining and Validating Digital Biomarkers as Fluid, Dynamic Multi-Dimensional Digital Signal Patterns.

Rhoda Au1,2,3, Vijaya B Kolachalama3,4,5, Ioannis C Paschalidis5,6

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|February 11, 2022
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Summary

The definition of digital biomarkers needs expansion beyond current regulatory standards to unlock their full potential. Embracing data science and AI can create new prognostic and diagnostic tools, improving health outcomes and reducing costs.

Keywords:
biomarkersdigitaldigital biomarkersfluidic dynamic digital patternsnew regulatory standardstechnology

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Area of Science:

  • Biomedical engineering
  • Digital health
  • Data science

Background:

  • The term "digital biomarker" is often narrowly defined, limited by existing regulatory frameworks like the United States Food and Drug Administration (FDA).
  • Current conceptualizations restrict the innovative potential of digital technologies in healthcare.
  • This limited view hinders the development of advanced diagnostic and prognostic tools.

Purpose of the Study:

  • To propose an expanded definition of digital biomarkers, moving beyond traditional regulatory constraints.
  • To highlight the opportunity for data science and artificial intelligence (AI) in creating novel digital biomarkers.
  • To advocate for new regulatory pathways and validation standards for next-generation digital biomarkers.

Main Methods:

  • Conceptual analysis of existing digital biomarker definitions and regulatory landscapes.
  • Exploration of the potential of data science and AI in biomarker discovery.
  • Review of current chronic disease management approaches and their limitations.

Main Results:

  • Current definitions of digital biomarkers are insufficient to capture the full scope of digital health innovation.
  • A new class of dynamic, AI-driven digital biomarkers can offer prognostic and early diagnostic capabilities.
  • Existing healthcare models for chronic disease are costly and yield suboptimal health quality.

Conclusions:

  • Revisiting and broadening the definition of digital biomarkers is crucial for leveraging digital technologies.
  • Data science and AI are key to developing advanced digital biomarkers for proactive healthcare.
  • New regulatory frameworks and validation standards are necessary to realize the promise of next-generation digital biomarkers.