New IDBS Polar Data Science Capabilities Democratize Access to AI/ML-powered Insights to Accelerate BioPharma Process Optimization

IDBS announces the launch of new data science capabilities for its Polar platform to accelerate BioPharma process optimization. The enhanced Polar Insight suite of easy-to-use, advanced data analytics and visualization tools includes Design of Experiments (DoE), Multivariate Analysis (MVA) and cell line genealogy, among others.

Accessing meaningful insights from process and quality data across the BioPharmaceutical lifecycle is critical to accelerating time to market of life-changing therapies. However, scientists are hampered by poorly contextualized and siloed data that typically require multiple tools and a high level of expertise in statistics and complex analytics to interpret. This slows the path to decision-enabling insight and locks up valuable resources.

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IDBS Polar unlocks the value of data by providing integrated digital workflows, eliminating data silos and delivering a high-quality, contextualized data backbone. Polar Insight empowers scientists with direct access to insight from the complex data sets they generate, historic data or data generated across teams curated through Polar digital workflows and seamless equipment integrations, creating a more efficient path to process understanding.

“Extracting actionable insight from process and quality data across the BioPharmaceutical lifecycle is frequently a time-consuming and error-prone process,” said Pietro Forgione, VP of Strategy at IDBS. “IDBS Polar replaces paper records, spreadsheets and ad-hoc software tools with integrated digital workflows which, together with the new Polar Insight data science capabilities, remove data cleansing bottlenecks and put decision-enabling advanced analytics in the scientists’ hands. Democratizing access to process insight enables BioPharma organizations to efficiently focus resources on the critical areas for quality and performance to accelerate process development, regulatory filings and technology transfer.”

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