BiQadx
Edge-to-Cloud Interoperability

Unified Intelligence.

Hardware defines the physical capability, but software establishes the clinical reality. Explore the Unified LIMS and the embedded synthetic neural net orchestrating our diagnostic ecosystem.

Data Architecture

Encrypted Data Pipeline

Every assay result traverses a verified, encrypted, and audited pathway. No data leaves the instrument without cryptographic signing and Neural Net inference passing.

Instrument
Dr. POCT™ / EtherX-1
Edge Controller
Local result validation
Unified LIMS
Order / result broker
BiQadx AI
Neural net inference
HIS / EMR
FHIR R4 export
Core Platform

Unified API Framework

A rigid, siloed laboratory information system is a bottleneck. BiQadx utilizes a unified, API-first architectural approach to connect decentralised POCT units alongside core-lab systems like the EtherX-1.

Every instrument connects via an embedded Edge Controller, translating raw telemetry and fluorometric curves into standardized resources.

HL7 v2.5.1FHIR R4REST APIGraphQLSNOMED CTLOINC

Order Management

Bi-directional HL7 v2.5.1 ORM/ORU order and result routing between instruments and the HIS/LIS.

Sys.Module.1

Auto-Verification Engine

Rule-based result auto-verification with configurable delta-check and critical-value alerting logic.

Sys.Module.2

Audit Trail

21 CFR Part 11 compliant tamper-evident audit log. Every action timestamped and user-attributed.

Sys.Module.3

Zero-Trust Security

AES-256-GCM encryption at rest and in transit. Role-based access control with SSO integration.

Sys.Module.4

QC Management

Levey-Jennings charting, Westgard rule engine, and peer-group benchmarking for reagent lot tracking.

Sys.Module.5

Inventory Intelligence

Predictive reagent stock forecasting with automated reorder trigger generation and cold-chain monitoring.

Sys.Module.6
Synthetic Intelligence

Diagnostic Neural Net

The Diagnostic AI layer runs classification models during post-analytical processing. Fed by validated fluorometric timeseries data, it outputs calibrated call probabilities with explainability summaries for each result event.

BiQadx.AI.InferenceEngine // v3.2.0
// Initialize Neural Net Session
const session = await ModelDB.load("dx-nn-v3.2");
// Stream real-time fluorometric curve
const inference = await BiQadxAI.{
panel: "RESP-6-PLEX",
fluorData: assay.channels.buffer,
calibrationVector: sys.factory.matrix
});
// Inference Output Node
> Target classification: DETECTED / 0.978 CONFIDENCE
  • Fluorometric curve classification (R² > 0.998)Deep learning models trained on 50,000+ proprietary clinical response curves.
  • Sub-100ms inference latency on Edge SoCHardware-accelerated execution entirely within the Instrument Controller.
  • Federated learning protocolsModel weights improve centrally, but zero raw patient PHI leaves the device.
  • Continuous Model VersioningOver-the-air updates deploy new neural net versions with automatic rollback capabilities.

Build Integration Spec

Our AI can generate a custom LIMS integration specification for your hospital's existing HIS infrastructure, including payload schemas and API endpoint maps.

BiQadx content is R&D / prototype / pilot-stage. No clinical claims. For planning and technical understanding only. Not medical advice.