Batch MVDA

Quartic's Batch MVDA is a multivariate data analysis software application purpose-built for batch process manufacturing. It enables manufacturers in life sciences, food and beverage, and other process industries to move beyond offline analysis and static reporting, delivering real-time batch monitoring, deviation investigation, and process optimization within a single unified platform. By combining Multivariate Statistical Process Control (MSPC) with modern machine learning, Batch MVDA helps manufacturing teams accelerate root cause analysis, improve yield consistency, and reduce batch-to-batch variability at scale.

The application addresses common pain points in batch manufacturing, including limited visibility into eventual batch outcomes from existing monitoring systems, slow manual deviation investigations, legacy MSPC tools that cannot handle complex non-linear data relationships in bioprocessing, excessive time spent preparing data for analysis, and the disconnect between offline and online modelling environments. Batch MVDA resolves these challenges by providing a connected, analytics-ready workflow from data ingestion through to real-time model deployment.

Core Capabilities

• Golden Batch Modeling: Compare current batches against ideal historical runs and use contribution plots to drill down and uncover the root causes of variability.
• Batch Performance Forecasting: Track real-time batch progress against historical golden trajectories, enabling early deviation alerts and mid-batch corrections before quality is compromised.
• Variable Impact Analysis: Identify the specific variables driving yield variation and trace batch deviations for faster, more accurate root cause analysis.
• Phase-aware batch modeling: Build models that account for the distinct phases of a batch process, improving the accuracy of monitoring and predictions.
• Unified offline and online modelling: Build, validate, and deploy models within a single workflow and software license, eliminating the gap between analytical development and operational execution.
• Native PAT and LIMS integration: Incorporate Process Analytical Technology data and laboratory information management system data directly into multivariate analysis of process data.

Key Benefits

• Unify MVDA, MSPC, and ML workflows across teams in one platform with contextualized, analytics-ready data.
• Achieve yield and quality consistency to address variability caused by raw materials and operator differences.
• Improve batch disposition and release times with evidence-based Continued Process Verification (CPV).
• Perform deviation investigations in hours rather than weeks.
• Scale from a single manufacturing unit to global multi-site operations.
• Detect quality drifts during production rather than at batch disposition, reducing reliance on manual assays for final product release.
• Monitor the effectiveness of Corrective and Preventive Action (CAPA) implementations over time.

Who Batch MVDA Is Designed For

• Process Engineers: Model and visualize batch trajectory in real time, use contribution plots for fast deviation investigation, and compare against historical performance for continuous improvement insights.
• Data Analysts: Build models with any ML system and integrate them with Quartic MVDA models, deploy models for streaming analysis in the cloud or at the secure edge, and enable cross-site collaboration while maintaining model governance and ownership.
• Quality and Compliance Teams: Detect quality drifts during production, reduce reliance on manual assays, and monitor CAPA effectiveness to enhance batch consistency and achieve quality certainty.
• Reliability and Maintenance Teams: Securely bridge OT and IT environments, integrate edge, cloud, and enterprise systems, maintain compliance and data lineage, and avoid vendor lock-in through open standards.
• Digital Transformation Leaders: Connect digital strategy to real operational KPIs, accelerate time-to-impact from months to weeks, and build a culture of informed, data-driven decision-making across plants.

Proven Business Impact

• A global pharma company achieved a 10% increase in upstream yield and faster deviation detection using Quartic's MVDA solution.
• A life sciences customer achieved a 10% capacity uplift and 20% reduction in batch yield variability in chromatography purification.
• A food and beverage customer achieved a 20% reduction in moisture variability and a 17% reduction in energy consumption in pet food drying operations.

Batch MVDA is available as a fully hosted SaaS solution or deployed within a customer's own VPC cloud environment. Model building takes place in the cloud, while deployed models can run at the edge for low-latency execution. The platform offers native connectors to Aveva PI, Ignition, and cloud data lakes such as Azure and AWS without requiring data replication. Enterprise access control lists (ACLs) allow data and model access to be restricted by site, equipment, or data layer, making it suitable for contract manufacturing organisation (CMO) deployments. Typical time to deployment and initial value realisation is four to six weeks.