CAMO Software and Lonza Group have entered into an agreement where CAMO will deliver a PAT software solution for collecting, handling, storing, monitoring and modelling data.
PAT software solution will complement Lonza’s existing operations and assure compliance with regulatory PAT and QbD initiatives. It consists of a combination of CAMO’s flagship software packages including Unscrambler® X and the Unscrambler X Process Pulse, with adaptations to meet specific operational requirements.
The solution connects directly to data sources in Lonza production lines, and records and stores data in secure databases. During data recording, multivariate models can be run to track process performance and quality parameters. Tracking enables real-time quality control, and the recorded data is available for future data analysis, troubleshooting and product traceability.
Existing production systems at Lonza will be integrated with the solution, offering greater flexibility with minimal system duplication. Delivery of the solution will be completed in phases, with the first delivery scheduled for the fourth quarter of 2014.
Lonza Group PAT lead Tobias Merz said: "The implementation of a PAT data management solution allows us to build up process knowledge from the beginning of a new process development and close the gap between R&D and production."
CAMO Software business development director, Europe, Geir Rune Flaaten said: "This is a great initiative by Lonza and will move the company to the front line of their industry, in respect to PAT."
Unscrambler® X software offers advanced multivariate methods, data visualization tools and the ability to cut through large data sets. It is used in the pharmaceutical, food and beverage, chemical, energy, mining and metals, paper and agriculture sectors.
The Unscrambler® X Process Pulse offers early fault detection and immediate identification of out-of-limit variables for real-time process control. Users can try to remedy potential failures before they occur, and the software includes advanced quality predictions and drilldown plots to investigate the variables contributing to deviations.