Aizon Unify

Aizon Unify is a GxP data fabric and production historian platform designed for pharmaceutical and biotech manufacturing operations. It captures, contextualizes, and monitors diverse real-time manufacturing data across processes, systems, and sites, breaking down data silos and converting raw data into actionable insights. The platform is built with Good Manufacturing Practice (GMP) standards embedded from the ground up, making it suited for regulated life sciences environments.

Unify addresses three core operational challenges in pharma manufacturing: understanding batch-to-batch variation, maintaining real-time process visibility, and accelerating batch release and regulatory reporting. It targets TechOps, Production, and Quality functions within pharmaceutical companies, CDMOs, and CMOs.

Batch Comparison Analytics

• Enables root-cause analysis and investigations by providing a holistic view of variations across multiple data sources and unit operations.
• Supports quantification of correlations between critical process parameters (CPP) and critical quality attributes (CQA) across various unit operations.
• Simplifies complex multi-source data analysis to make it more accessible for TechOps teams.
• Applied in practice by Curia, a leading CDMO, to reduce yield variability through automated batch comparisons.

Real-Time Process Monitoring

• Monitors the current batch status in real time, providing visibility into process details to keep batches on the expected trajectory.
• Supports quick identification of corrective or preventive actions to avoid interruptions and resolve issues faster.
• Includes historical phase comparisons to identify improvements or slowdowns at any stage of the process.
• Provides traceability features to indicate when operator presence is required in a given area.
• Allows performance comparison across shifts to support achievement of best demonstrated performance at each process step.

Digital Batch Review

• Centralizes complete campaign information including batch details, test data, deviations, and variance tracking to accelerate batch releases.
• Simplifies annual Product Quality Review (PQR) analysis and reporting by making all required data readily accessible.
• Prepares organizations to be audit-ready, enabling immediate access to trustworthy information for regulators and auditors.

Key Platform Capabilities

• Supports flexible contextual data models across structured, unstructured, and time-series data, with batch context treated as a primary design consideration.
• Interoperable architecture with no defined limits on data volume and an unlimited number of users.
• Cloud-based, open, and flexible architecture with low setup barriers, reducing the need to maintain dedicated IT/OT infrastructure.
• Embeds GMP standards by design, described as a "GMP by design" approach rather than retroactive compliance.
• Supports AI algorithm qualification as part of its compliance framework.

Documented Use Cases

• Recordati improved yield by 1.5% within three months using Unify for real-time process monitoring and yield optimization in small molecule pharma manufacturing in Europe.
• Grifols scaled yield optimization across downstream processes using unified data and GxP AI, spanning both Europe and the United States.
• Curia applied Unify's batch comparison analytics to reduce variability in the precipitation phase of small molecule CDMO manufacturing.

Aizon Unify integrates with other Aizon products, including Aizon Predict for advanced manufacturing analytics and Aizon Execute for native capture of batch record information. The platform is deployed as a cloud-based solution and is positioned as an interoperable lakehouse that connects to existing manufacturing systems and data sources without requiring significant infrastructure investment.