DeepSensi™
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For Pharma

Attack the denominator:
90% of trials fail.

$2.6 billion per approved drug — most of it spent on leads that were never real and patients who were never found. Verified evidence and borderless, autonomous matching change both.

Target ID without hallucinated leads

Every candidate correlation survives multi-layer evidence verification before it reaches your scientists — signal, not noise, enters the pipeline.

Autonomous trial matching & advocacy

The Golden Horizon engine scans global registries and an autonomous agent pursues eligible patients and providers on a defined follow-up schedule — recruitment reach across four continents, referred through patients' own physicians.²

Population-scale simulation

Protocol assumptions stress-tested on large synthetic cohorts before the first patient is enrolled — zero real patient data required.

DSS-scored evidence for submissions

Every AI-assisted result carries an Evidence Integrity Score and a sealed audit chain — data your regulatory team can actually file.

Continuous post-market signal detection

Automated surveillance across the network flags safety signals per patient profile — years before manual pharmacovigilance would.

Four-continent recruitment reach

Edge deployment brings eligible populations online that no site network reaches today — including offline and underserved regions.

90%of trials fail — the target
4continents of reach
SIL-4grade evidence bound¹
14.3 smedian per verified analysis

¹ Fault Tree Analysis per IEC 61025, worst-case operational bound 3.23 × 10⁻⁶ per assertion — WP-001.  ² Golden Horizon compassionate-access and PharmaLink dual-track architecture — WP-006. Population simulation and autonomous hypothesis generation — WP-005.

Put one failing recruitment cohort through the network.

The papers →
Zero PII· HIPAA· GDPR· EU AI Act — architected· FDA — Q-Sub engaged Verified Clinical Intelligence