DoE is an essential tool to assess the criticality of process parameters during process development. DoE provides significant advantages over one-factor-at-a-time (OFAT) experimentation and is often used in process characterization studies to determine acceptable ranges of process parameters to deliver quality product. However, DoE is difficult to implement because it requires third-party tools, statistical expertise and manually exporting/importing and aligning data sets.

With Polar Insight DoE, you can create your experimental design with just a few clicks, record experimental results in the same digital system of record and understand which parameters are critical to quality based on statistical analysis. Reduce the number of experiments you need to run to gain process understanding, optimize performance and support regulatory compliance.

Siloed data and lack of standardized data formats across different bioreactor scales and projects make it difficult to monitor and compare bioreactor runs. Polar Insight Bioreactor Comparison provides interactive visualizations for exploration and comparison of all bioreactor runs within a campaign, including control parameters, process variables and quality attributes. Using these visualizations enables process development scientists to easily explore and understand their process parameters across bioreactor cultures; both for monitoring currently running processes and comparing data between historical processes. 

Collating all the data required to accurately portray cell line genealogy across numerous different experiments is often time consuming and error prone. With Polar Insight Cell Line Genealogy, you can quickly uncover the history of a cell culture and understand relationships between cultures at any point, including extended lineages and availability.

When the primary focus is analyzing experimental results during a study/project rather than operations, it can be challenging to identify and address bottlenecks. Polar Insight Project Tracking Dashboard enables project managers to track progress and share deadlines, increasing efficiency and collaboration. Seeing the status of all work currently ongoing including elapsed and touch time, number of repeats and other key quality metrics enables project managers to take corrective action when needed.

On-Demand Webinar

Watch the webinar “How to build the data foundations to enable meaningful insights from AI” to learn how to build the required data foundations to enable good insights. AI/ML are often set as the goals for implementing a digital strategy but if these tools are implemented without a clear problem or business impact in mind, the results are unlikely to deliver value.

A data-centric approach, and the ability to ask the right questions, are needed to support business strategy and ensure data accessibility, quality, interoperability and reusability across the BioPharma development lifecycle.