Strategic Transformation // Verified

Clinical Trials: 4x Faster
Patient Matching.

Engineering an Agentic NLP Mesh to parse unstructured clinical notes and genomics data—accelerating oncology trial enrollment by 400% while maintaining absolute HIPAA-gated privacy.

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Outcome_TelemetryBIO_DIGITAL_INTEGRITY
4x
Enrollment Velocity
Manual Sifting
65%
Screen Failures ↓
ROI: 14 Weeks
100%
HIPAA Gated
PHI_SECURE

Trusted by Leading Fortune 500 Innovators

/// Strategic Context

The Mission: Precision Matching.

Vertical
Clinical Research

Global oncology research network managing 50+ concurrent trials across diverse EHR environments.

Engagement
Strategic Pod

Bio-ML Architect + 2 Data Engineers + HIPAA Compliance Lead embedded with Clinical Ops.

Objective
Enrollment Autonomy

Eliminating manual chart reviews to connect high-need patients with life-saving trials in real-time.

Technology
Agentic NLP Mesh

LLM-powered entity extraction, FHIR-integrated Kafka streams, and medical knowledge graphs.

/// The Situation

The Reality Gap: Unstructured Debt.

The client’s oncology research arm struggled with 'Data Paralysis.' Inclusion and exclusion criteria for trials were trapped in complex PDFs, while patient data lived in unstructured clinician notes across 14 fragmented EHR systems.

Manual chart sifting took weeks per patient, leading to a 30% dropout rate as patients sought alternative treatments. The enterprise required a transition from 'Manual Sifting' to 'Computational Matching' without compromising PHI (Protected Health Information) security.

Trial Stall
Under-enrollment threatened trial viability, delaying the path to market for breakthrough therapies.
Operational Burn
Research staff spent 70% of their time on administrative data entry rather than patient-facing care.
Screen-Fail Waste
Inaccurate manual matching led to high screen-failure rates at the site level, wasting expensive laboratory resources.
/// Architecture

The Operational Gates

01
HIPAA-Locked NLP Pipeline
Orchestrated a secure pipeline using Medical Entity Recognition (MER) to extract TNM staging, biomarkers, and ECOG scores from clinical notes.
Extraction_Layer
PrivacyPHI_Anonymized
ModelMedical_LLM
StandardsFHIR_R4
02
Knowledge Graph Orchestration
Mapped extracted patient profiles against trial protocols using an Agentic knowledge graph to identify high-probability matches.
Matching_Engine
TypeAGENTIC_AI
LogicProtocol_Mapped
AuditLineage_Tracked
03
Immutable Audit Narratives
Generated explainable 'Matching Justifications' for every patient, providing clinicians with clear evidence for enrollment recommendations.
Governance_Proof
ComplianceHIPAA_GATED
StandardSOC2_READY
TraceAUDIT_TRAIL
/// The Architecture Shift

The Structural Evolution.

Dimension
Manual Sifting
Agentic NLP Mesh
Data Processing

Human Review

Analysts reading through thousands of clinical notes per month.

Autonomous Parsing

Real-time extraction of oncology biomarkers from unstructured text.

Privacy Gate

Policy-Based

Reliance on internal staff training to prevent PHI leakage during review.

Hard-Coded

Automated PHI scrubbing and HIPAA-gated storage at the infrastructure level.

Matching Time

12-14 Days

Significant latency between patient diagnosis and trial recommendation.

Sub-Minute

Near-instant matching notifications delivered via secure EHR alerts.

/// The Secret Sauce

Implementation Highlights.

AGENTIC_AI

Autonomous Protocol Triage

The system proactively alerts investigators when a new trial protocol perfectly aligns with a patient currently in the system.

Impact // Technical
92% Matching Precision
HIPAA_GATED

Zero-Trust PHI Fabric

Ensured all data processing occurred in transient, memory-only environments to eliminate persistent data risk.

Impact // Regulatory
100% Compliance Audit
EVENT_DRIVEN

Real-Time Enrollment Alerts

Kafka-driven streams trigger clinical coordinator alerts the moment an EHR update meets a trial requirement.

Impact // Clinical
4x Enrollment Velocity
/// Proprietary Assets

Accelerated by Coretus Kernels™.

Medical Privacy Kernel

Pre-built logic for HIPAA-compliant de-identification and PII scrubbing in medical data meshes.

Bio-Data Ingestion Kernel

Production-ready FHIR and HL7 connectors for rapid EHR interoperability setup.

Clinical Telemetry Mesh

Real-time monitoring for clinical recruitment funnels and investigator engagement dashboards.

Oncology Feature Kernel

Standardized NLP patterns for extracting oncology-specific biomarkers (EGFR, ALK, KRAS).

Enrollment_Acceleration
4x Faster
Standard Build24 Weeks
Coretus Accelerated10 Weeks
By injecting our pre-audited Medical Privacy Kernel, we bypassed 14 weeks of compliance infrastructure setup.
/// Verification

The Performance Delta.

METRIC: VELOCITY

Enrollment Timeframe

Agentic matching removed manual bottlenecks, reducing the 'Diagnosis-to-Trial' window significantly.

Legacy BaselineManual
Coretus Mesh400% Faster
↑ 4x Matching Speed
METRIC: PRECISION

Screen Failure Suppression

Automated data verification ensured only patients meeting 100% of criteria reached the lab phase.

BeforeError-Prone
After65% Lower
↓ 65% Screen Failures
METRIC: RELIABILITY

Inference Latency

The NLP mesh processes thousands of medical notes per second without impacting clinical workstation performance.

Target< 2s
Coretus400ms
↓ 400ms Inference
Outcome Status: Performance & HIPAA Compliance Verified
/// Governance

Operational Integrity.

01
Data Sovereignty
All pipelines operate within the client’s private cloud VPC, ensuring zero external data leakage.
Status: HIPAA_GATED
02
Model Transparency
Matching decisions include SHAP justifications and citations to original source clinical notes.
Status: AUDIT_TRAIL
03
Infrastructure Security
SOC2-compliant K8s orchestration with automated vulnerability patching for medical edge devices.
Status: SOC2_READY
04
IP Transfer
Coretus provides 100% IP ownership of oncology knowledge graphs and fine-tuned NLP weights.
Status: 100% OWNED
Discuss Medical AI
“
Coretus didn't just build a tool; they engineered a life-saving velocity engine. We are matching patients to trials 4x faster, providing treatments to those who literally cannot afford to wait.

Dr. Aris Thorne

Chief Medical Officer

/// Bio-Digital Synergy

Related Clinical Orchestrations.

Art Market Intelligence
90%
Research Efficiency

Art Investment: 100% Fully Automated Intelligence.

The Reality Gap

Human fatigue led to missed undervalued lots during high-volume auction cycles on platforms like Drouot.

The Outcome

Architected independent microservices for secure OAuth2 authentication and anti-bot resilient scraping to extract structured artwork metadata.

INTELLIGENCE_VERIFIED
Explore
Digital Health / B2C
60%
Planning Efficiency

Personalized Nutrition: 60% Faster Meal Planning.

The Reality Gap

Fragmented user journeys created high friction, causing users to drop off after 7 days of manual logging.

The Outcome

Architected the backend into independent services for meal logic, grocery automation, and user profiles to ensure 99.9% availability.

BIO_INTEGRITY_VERIFIED
Explore
Digital Health & Wellness
60%
Time Reduction

Nutrition Planning: 60% Faster AI Automation.

The Reality Gap

Manual meal logging took users an average of 45 minutes daily, resulting in 70% drop-off within the first 14 days.

The Outcome

Engineered functional layers (recommendations, geolocation, auth) as independent services to ensure horizontal scalability.

ECOLOGY_READY
Explore

Turn Patient Data into Clinical Velocity.

Stop letting unstructured clinical notes stall trial enrollment. We build Agentic NLP meshes engineered for 4x faster matching and absolute HIPAA-gated security.

HIPAA & PHI Secure

Agentic NLP Orchestration

100% Model Ownership

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