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PatroLab™

Transform Reactive Biologics Manufacturing into Predictive, Prescriptive Commercial Control

PatroLab synthesizes real-time monitoring, predictive modeling, and automated process control into a unified digital platform. By converting continuous bioprocess data into early alerts, the platform delivers predictive insights and automated process adjustments—before variability compromises biologic product quality.

PatroLab empowers manufacturers to:

  • Detect process drift earlier through process analytical technology (PAT).
  • Reduce and accelerate deviation investigations.
  • Improve process capability and manufacturing consistency.
  • Strengthen process performance qualification (PPQ) and controlled process verification (CPV).
  • Support real-time release testing (RTRT) for fast drug substance release.

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A Smarter Model for Process Monitoring

Traditional manufacturing relies on periodic sampling and retrospective analysis, risking delays, rework, and late detection of process variability. By the time problems are identified, critical quality attributes (CQAs) might already be affected.

PatroLab replaces this reactive model with continuous monitoring of product quality attributes (PQAs) and production performance. Paired with predictive insight, the platform enables earlier intervention and more informed decision-making.

Traditional Reactive Model

PatroLab Predictive Model

Offline sampling

Continuous monitoring

Delayed Out of Trend (OOT) detection

Early risk and fast root cause identification

Manual parameter adjustments

Automated model predictive control (MPC)

Fragmented data systems

Centralized process data architecture

How PatroLab Works

Real-Time PAT Monitoring

Raman-based PAT measures in-process targets in real time, generating dense time-series data that reveal cell culture behavior and metabolic activity.

  • Monitoring of more than 40 PQAs
  • Continuous 24/7 measurement at 5-minute intervals
  • Reduced manual sampling requirements
  • High-frequency data replacing offline sampling

Digital Twin Modeling

Machine learning and mechanistic metabolic modeling create a digital twin that predicts process performance and product quality attributes across scales.

  • Predictive modeling from 3 L development scale to 16,000 L (eg, 4 × 4,000 L) manufacturing
  • Continuous in-silico simulation of process performance
  • CQA prediction supporting RTRT strategies

Model Predictive Control

MPC translates digital twin predictions into automated adjustments within predefined control limits, stabilizing process performance.

  • Automatic adjustment of CPPs
  • Less reliance on manual intervention
  • Consistent execution of model-informed control strategies
  • Operation within validated control spaces

Integrated Manufacturing Data Layer

A centralized digital manufacturing layer aggregates and contextualizes process information from multiple sources, providing comprehensive process visibility.

  • Integration of inline and offline data streams
  • Live dashboards across development, manufacturing, and quality teams
  • Single source of truth for manufacturing data
  • Support for Quality by Design (QbD) process management
  • CQA prediction supporting RTRT strategies

Product Quality Evaluation in Real Time

Continuous in-situ monitoring across upstream and downstream operations provides live insight into product quality. By combining PAT measurements with predictive models, PatroLab supports RTRT strategies that evaluate CQAs during manufacturing rather than relying solely on end-product testing.

With PatroLab, RTRT can monitor and control process performance indicators like product concentration, while evaluating key CQAs including process-related impurities, product-related variants, and post-translational modifications.

Reliable Commercial Performance

High-frequency process insight dramatically expands the manufacturing data landscape. PatroLab increases batch data density by up to 1,000×, enabling earlier drift detection, stronger CPV trending, and faster deviation investigations.

Operational Robustness

  • Earlier OOT detection
  • Reduced process drift
  • Improved process capability (CpK) and reduced variability

Investigation Efficiency

  • Shared, real-time data access across teams
  • Faster root cause analysis
  • Reduced deviation investigation cycle time

Predictable Commercial Scale

  • Cross-scale modeling from development through manufacturing
  • Stronger PPQ readiness
  • Enhanced CPV performance during commercial operations

Deployment across Development and Manufacturing

PatroLab connects PAT instrumentation at the GMP manufacturing site with centralized modeling and analytics to maintain digital continuity from development through commercial production. Insights generated during development inform manufacturing strategy and control approaches at scale.

Process Development

  • Digital twin model development
  • Scale-up readiness assessment
  • Model training using development-scale data (3 L)

Clinical Manufacturing

  • Control strategy refinement
  • Better preparation for PPQ

Commercial Manufacturing

  • CPV enablement
  • Faster deviation response and investigation
  • Enterprise-level visibility into manufacturing performance

Built for Regulated Environments

As regulatory expectations for CPV intensify, manufacturers require greater transparency, faster investigation capabilities, and robust data governance. PatroLab’s architecture supports secure data integration while advancing digital manufacturing within GMP environments.

Key compliance features include:

  • 21 CFR Part 11–aligned electronic record and access control framework
  • Cryptographically secured audit trails aligned with NIST SP 800-131A standards
  • Centralized governance of process and manufacturing data
  • Role-based user management

Cross-Functional Transparency and Collaboration

  • An interactive interface visualizes manufacturing data for both WuXi Biologics and clients.
  • Through real-time dashboards, teams across process development, manufacturing, and quality functions can monitor performance, investigate trends, and collaborate on process improvements.
  • OOT alerts deliver immediate, actionable notifications for rapid responses to time-sensitive deviations.
Advancing Biopharma 4.0 at Commercial Scale PatroLab transforms biologics manufacturing from reactive monitoring to predictive, prescriptive process control. By integrating real-time PAT data, predictive modeling, and automation, the platform establishes a digital foundation for Biopharma 4.0 manufacturing at commercial scale.
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Further Reading

PatroLab Service Sheet

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PatroLab: Variability, Controlled Infographic

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Manufacturing Systems eBook Learn More

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