๐Ÿงช CONCEPT BUILD โ€” unofficial redesign specimen for Mike. Real copy remixed; synthetic bits marked.
For clinical trials

Underrepresentation has an address.

FDA Diversity Action Plans make inclusion a requirement. The shift to community-based and decentralized sites makes it a geography problem. The layer that finds underrepresented populations โ€” and proves they were reached โ€” barely exists. That's the layer we built.

~80%
of trials delayed or closed by recruitment
$8M/day
potential revenue lost to delays
Tract-level
disease prevalence (CDC PLACES)

Three questions trial teams can't answer today.

01

Where do underrepresented, trial-eligible populations actually live?

  • Ranked geographies for sites and community partnerships, based on where unreached eligible populations actually live.
02

What stands between them and a site?

  • Tract-level maps of who current trial infrastructure can't reach โ€” transportation gaps, distance, infrastructure.
03

Did outreach, enrollment, and retention reach them?

  • Inclusion benchmarks measured comparably across geographies โ€” so inclusion is proven, not promised.

The DAP report is the product.

FDA Diversity Action Plans don't ask what you intended โ€” they ask what you did, where, and how you know. Every Variate answer ships with a receipt: the question, the variables (with vintages), the weights, the counts. Outreach becomes a documented, auditable artifact your regulatory team can file.

Sample DAP-report artifact:SYNTHETIC โ€œQ2 outreach targeted 14 census tracts flagged for eligibility + transport gaps; 3,150 estimated eligible adults; contact attempts logged per tract; enrollment vs. eligible-by-tract rendered as the inclusion ratio table attached โ€” generated with dataset vintages and weight-set hash intact.โ€

Built on real data, answered in plain English.

200+ federal health and social variables โ€” including tract-level disease prevalence for asthma, COPD, and arthritis (CDC PLACES) โ€” fused with social vulnerability, transportation, and health-infrastructure data. Population math done properly: never county averages smeared across empty space. And when the model is unsure, it says so, and a human decides.