Process Production Operations

Empowering production operations in process industries to shorten time to market and maximize profitability by leveraging process and quality data

BIOVIA Discoverant

The process development, manufacturing and quality functions generate an abundance of data, which needs to be utilized in a more user-friendly, organized (contextualized) form for improved process knowledge and production operations. Traditional manual methods, such as spreadsheets, are error-prone and waste valuable time. As organizations generate more data through implementation of QbD (Quality by Design), PAT (Process Analytical Technology), PR (Process Robustness), and CPV (Continued Process Verification) initiatives along with new manufacturing and measurement technologies, they need better ways to access and use their data.

BIOVIA Discoverant provides process development, quality, and manufacturing users with self-service, on-demand access to process and quality data from disparate databases and paper records. It automatically aggregates and contextualizes the data and enables ad hoc statistical investigations and analysis with automated validation-ready workflows to provide browser-accessible outputs for teams of observational users. This includes different organizations and geographies improving the working relationship with contract manufacturing organizations (CMOs).

The solution supports three major areas that empower production operations, shorten time to market and maximize profitability:
  • Improve Process Design to understand the critical process drivers
  • Increase Process Performance by monitoring variability enabling preemptive action
  • Enhance Process Improvement by understanding and control process and product variability

Watch the 4-part video series showing how BIOVIA Discoverant improves process design, increases process performance and enhances process improvement.


  • 21 CFR Part 11 compliant capture of paper record data
  • Aggregation and contextualization of data from different sources
  • Self-service point-and-click access to all process and quality data
  • Ad hoc cause-and-effect analysis using all types of process and quality data
  • Automated data analysis and visualization outputs
  • Monitoring of variability with automated alerts for review-by-exception
  • Automated trending and alerts for review-by-exception (CPV)
  • Role-based Signal Monitoring Dashboards for process performance monitoring across in-house and contractor operations
  • Genealogy Map for interactive graphical genealogy reporting allowing upstream/downstream traceability from a selected batch
  • Proportional genealogy analysis using weighted averages based on contribution amounts of raw materials and pooled steps during the manufacturing process
  • Stability analysis with automated Out-of-Trend (OOT) alerts
  • Analysis of on-line and off-line multi-phase cell culture and chromatography data


  • Access to all process and quality data with automated data contextualization
  • Get better process understanding by ad-hoc analysis of data
  • Get visibility into process performance at all levels in the organization
  • Perform upstream / downstream correlations across pooling and splitting points in the process stream
  • Make GMP decisions for deviation investigations and batch dispositioning
  • Make golden batch comparisons
  • Collaborate to create and share process knowledge regardless of organizational or geographic barriers
  • Leverage the value of investments in existing data infrastructure

BIOVA Discoverant minimizes non-value-added manual tasks, reduces the risk of errors, and promotes process understanding and knowledge sharing to reduce process variability. Ultimately BIOVIA Discoverant helps speed time to market and improve process economics and sustainability.

What's New in BIOVIA Discoverant 2017?

Analyzing the effect of raw material characteristics on process outcomes

  • Determine which characteristics contribute to positive operations trends
  • Proactively route raw materials to the processes where they will contribute most
  • Target resources to operations areas most in need

Determining expiration dates for products that degrade in a non-linear fashion

  • Understand stability study data that follows quadratic and cubic models
  • Identify sources for process improvements that lead to longer shelf life

Next-generation Monitoring-by-Exception of quality assay results to minimize non-value added tasks

  • Assess results using both summary statistics and individual test results
  • Make pro-active process adjustments to avoid costly failures
  • Focus efforts where they add the most value

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