Use Case:

ARIA: Population Scale (1M+) Healthcare Analytics Platform Product

ARIA offers researchers a centralized solution for high throughput genomic, clinical, and health data analysis at the million+ participant scale. The unprecedented scalability of the solution enables users to manage and create cohorts and apply complex statistical analyses of their choosing, all within a connected and secure ecosystem.

Velsera, Precision Medicine
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Problem Space & Opportunity

Problem:

Access to explore and analyze large genomic, clinical, and health datasets to create clinical trials and develop precision medicine is limited to bioinformaticians with scripting expertise in R or Python. These specialists are rarer to find which increases cost and slows down time to market for novel drug therapies in the Precision Health market.

Opportunity:

Accelerate time to insights and reduce significant clinical trial and precision medicine costs for biopharma and research institutions by designing and building a product with a streamlined, intelligent visual interface. This interactive user experience will enable a wider array of researchers and analysts to explore, analyze, annotate, and share data insights at scale.

Hypothesis:

An interactive user experience tailored to the research needs of clinicians and analysts will enable the formation of novel scientific hypotheses while accelerating time to insights by expanding access to real-time, population scale genomics and health data exploration. We can improve health outcomes for patients in shorter timelines at lower costs by providing clinical researchers with a product that enables the exploration and analysis of genomic and health datasets via

  • interactive browsing of common data models
  • configurable filters with advanced longitudinal queries
  • clear, robust data visualizations

The Goal:

Understand, design, and implement an interactive user interface that leverages the power of the existing custom client solutions including the cloud architecture, real-time processing performance, and computational experience (R studio/Jupyter). Deliver an off-the-shelf, configurable, platform product that significantly grows our user base from bioinformaticians to include clinical researchers thereby expanding our biopharma market share and providing cross-sell opportunities.

Teams

  • Solution-layer:
    1-3 months
    • 2 scrum teams dedicated to the product delivery.
    • 1 scrum team exploring new product ideas.
  • Program-Layer:
    3-18 months
    • Product core team including Principal Product Manager, Scientific Liaison, Architect, and Principal Product Designer
  • Portfolio-Layer:
    1-5 years
    • SVP Scientific Strategy, VP Product & Design, Chief Architect, Chief Technology Officer

Techniques

  • Storytelling

  • Service Design Workshops

  • Scientific & Clinical Stakeholder Collaboration

  • User Research

  • Wireframe & Prototype
  • Data Visualization

Elements

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