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Patrick Sagmeister

Blog

Intravacc and PAS-X Savvy: Digitalization and Data Analytics to Accelerate Bioprocess Development

HIGHLIGHTS

  • INTRAVACC is implementing the Werum PAS-X Savvy platform for data management, (real-time) data analytics, multivariate statistics, and mechanistic modeling.
  • All data from upstream and downstream processes, bioreactors, spreadsheets, and analytical equipment is stored in a central database.
  • Intravacc scientists run visual bioprocess data analytics on real-time data within the web browser.

Bioprocess development generates extensive data (from in silico or in vitro experiments) that must be analyzed using a properly structured methodology. This data can be generated from diverse sources, and it can include large datasets (e.g., time series, pictures, quality measurements, etc.). A data logging and data analysis strategy must be clearly defined and adequately executed to take full advantage of the experimental work. Bioprocess development can be accelerated only after having such a strategy, which would allow maximizing the findings from each experiment.

Intravacc (the Institute of translational vaccinology) is currently developing its strategy for data logging and analysis with the assistance of PAS-X Savvy. This permits Intravacc to continue as one of the leading research centers in vaccine technology.

Next Level Vaccine Production Processes

Researching and developing the next generation of vaccines nowadays is a huge challenge. On one side, there is the need to optimize product quality, increase productivity and ensure quality of vaccines by robust and compliant bioprocesses. On the other side, the timeline for life-saving vaccines needs to be shortened. This is the reason why Intravacc is defining a digital strategy. Data management and real-time analytics are mission-critical and, therefore, in focus. The data management includes all relevant process data, and the real-time analytics is based on univariate and multivariate statistics and mechanistic modeling.

Digitalization and Data Analytics

During the past years, lab digitalization and sensor technology have improved tremendously. The accumulated data from R&D and Quality Control (QC) has an immense potential to speed up time-to-market and develop more robust processes. Only well-prepared and analyzed data leads to process knowledge and, finally, to process control and continuous improvement. Thus, a robust and efficient data management and data analytics strategy are one of the most valuable concepts in bioprocess R&D.

The data analytics strategy defines how to:

  • Efficiently analyze the relation between process parameters and product quality/process performance.
  • Develop platform knowledge by data analytics and mathematical modeling to continuously improve Intravacc’s manufacturing platform.
  • Manage and document data and data insights that are compliant for further use during stage 1 process validation.

 PAS-X Savvy and Intravacc are implementing a comprehensive platform for data management, (real-time) data analytics, multivariate statistics, and mechanistic modeling. The project aims to help Intravacc optimize product quality, increase productivity, and ensure quality with robust and compliant bioprocesses. The PAS-X Savvy software is designed to automate workflows at the core and connect to almost anything at the network's edge. The project manager says:

“We found an excellent realization partner in Körber. The project team is very focused on our business needs, and all interfaces are running smoothly and reliably. The collaboration is excellent.”

[Translate to English:] PAS-X Savvy’s Architecture

Data Governance

All data from upstream and downstream processes, bioreactors, spreadsheets, and analytical equipment is stored in a central database. In PAS-X Savvy, there is the possibility to manage all relevant bioprocess data like time series, quality measurements, spectra, and microscopic pictures in a single database. A consistent nomenclature of the variables is crucial for process management and data analytics and is defined within the project. An intelligent database search functionality for projects and products makes the work for scientists and operators more comfortable. Comprehensive user management leads to complete traceability data.

Data Analytics

To streamline the data analytics process, PAS-X Savvy implemented real-time data analytics within the web browser. All predictive algorithms are implemented using Python and R integrations. As a result, there is no need to import or export any data - all data is available to perform any mathematical operation, visualization, or other analytical methods.

[Translate to English:] Figure 1: Data analytics using the browser-based PAS-X Savvy platform. An example of equivalence testing is used to evaluate biopharma tech-transfers and scale-ups of upstream and downstream processes.

Joining forces

Intravacc has developed innovative soft sensors for monitoring cell cultures. This allows for the reduction of expensive and maintenance-intensive hardware sensors. The mechanistic models on which these soft sensors are based have been deployed at the PAS-X Savvy platform. Moreover, PAS-X Savvy facilitates standardized reporting for experiments and other collaboration features. And consequently, it enhances the cooperation between scientists.

[Translate to English:] Figure 2: Intravacc and Körber develop novel soft sensors to estimate important production variables in collaborative research projects.

About Intravacc

Intravacc is a not-for-profit R&D organization. We develop and optimize vaccines, vaccine processes, and vaccine technologies. We aim to substantially reduce the development risks and costs of new vaccines to contribute to global health and equity in access to vaccines worldwide. We achieve our aim by developing and improving vaccine design, production processes, analytics, and technologies. In our state-of-the-art facilities, our experienced R&D institute takes your discovery up to Phase I/II clinical trials. Furthermore, we share and transfer our knowledge and technologies to public and private partners worldwide and work on collaborative R&D.

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