nucleus - graphsafety.ai

/nucleus: The Safety Neural Network

/nucleus introduces an architectural inversion in pharmacovigilance. For decades pharmacovigilance relied on a passive repository model served by human experts. As case volumes increased the only way to scale was by adding headcount. /nucleus reverses this model by shifting pharmacovigilance from experts serving data to an intelligent safety operating system where computable logic actively serves the expert.

The Challenge

Traditional safety databases are designed to store information rather than think. Data remains idle until it is queried; intelligence runs in batches, and collaboration relies on email and manual handoffs. As case volumes grow, this operating model creates a linear scaling trap where more cases simply translate into more people, higher costs and greater operational risk.

graph safety suite

/nucleus

graph safety /nucleus is an AI-native safety database designed as an active nervous system for pharmacovigilance. It continuously interprets safety data as it arrives, enabling real‑time intelligence, collaboration, and decision readiness across the safety organisation.

The 9 Pillars of Algorithmic Pharmacovigilance

Intelligent Nervous System

Real-time active intelligence where safety data triggers logic instantly instead of waiting for batch processing, delivering immediate risk insight.

Collaborative Intelligence

A single unified workspace where human experts and intelligent agents collaborate seamlessly, enabling faster coordination and shared decision-making.

Verify by Source

Every AI-generated insight remains linked to its original source, ensuring traceability, transparency and trust without black box uncertainty.

Transparent Intelligence

Every inference includes a clear, human-readable rationale grounded in contextual logic, making the system audit-ready by design.

Auto Coding

Context-aware intelligence predicts accurate MedDRA codes grounded in clinical context, enabling consistent and confident classification.

Networked Safety

A safety neural network that connects real-world signals to molecules, patients and adverse events, enabling a complete and connected safety view.

Clinical Context Aware

Context-driven intelligence prioritises what truly matters, suppresses noise and enables smarter triage with reduced alert fatigue.

Universal Gateway

Built to support global submissions and integrations while maintaining a single consistent source of scientific truth across regions.

Persona Based Productivity

Adaptive user experiences designed around individual roles enable faster reviews, deeper focus and higher productivity.

VALUE DELIVERED

What graph safety /nucleus changes

/nucleus is not a passive database. It is an AI-native safety operating system designed for clarity, confidence and continuous readiness.

From Passive to Active Safety Operations

Instead of data sitting idle until reviewed, the graph safety /nucleus operates as an active nervous system where safety data triggers logic immediately, enabling continuous awareness rather than delayed insight.

From Black Box AI to Transparent Intelligence

Legacy systems rely on opaque algorithms. graph safety /nucleus provides explainable intelligence where every inference is grounded in clinical logic and traceable to its source, enabling audit readiness by design.

From Siloed Work to Collaborative Execution

Email-driven handoffs and disconnected workflows are replaced by a unified collaborative fabric where human experts and intelligent systems work together in real time.

From Linear Scaling to Algorithmic Scale

Traditional models require more people as case volumes increase. graph safety /nucleus enables algorithmic pharmacovigilance, allowing organisations to scale case volume without proportionally increasing cost or headcount.