Predictive Analytics Platform

Our proprietary machine learning models transform routine clinical information (such as blood chemistry) into holistic health assessments. By analyzing your study dataset, we can:

  • Detect systemic health effects beyond primary endpoints.
  • Reveal secondary benefits that strengthen scientific relevance.
  • Project outcomes into long-term risk trajectories.
  • Support differentiated claims in publications and regulatory filings.

Award Details

Selected applicants receive predictive risk model analyses, consultation with our data science team, and opportunities to co-publish in peer-reviewed journals.

Example Studies

  • Digital therapeutics for metabolic syndrome.
  • Dietary interventions for diabetes or heart health.
  • Exercise regimens on lipid management.
  • Environmental exposures and health outcomes.

Eligibility

  • Human clinical, interventional, or observational study.
  • De-identified patient-level data available within 3 months.
  • Baseline + endpoint data: age, sex, metabolic and lipid panels.
  • Willingness to share data and co-publish with Voloridge Health.

Who Can Apply

  • Academic researchers & principal investigators.
  • Clinicians and healthcare providers.
  • Public health institutions & nonprofits.
  • Digital health startups & consumer health companies.
  • Pharma & biotech organizations.

What to Submit

  • Study abstract / overview with supporting materials.
  • Primary outcomes (actual or expected).
  • Rationale for broader health impact.
  • Available data types, study design, and sample size.
  • Timeline for data availability.

Selection Criteria

  • Scientific merit & methodological soundness.
  • Fit with Voloridge Health’s mission & scoring models.
  • Data quality, size, and completeness.
  • Potential for novel, scalable insights.
  • Likelihood of impactful publication.

You will hear back within four weeks. If selected, analysis is typically completed within three months of dataset receipt.

Contact us at bizdev@voloridgehealth.com.

We’re looking for real-world data that can move the needle on predictive and preventive health. Let’s work together!

Study Submission