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The CDMO industry is at a turning point. As demand for complex modalities like ADCs and cell therapies surges, traditional "manual relay" project evaluations are no longer sustainable. With 60% of pharmaceutical organizations now prioritizing AI readiness in their partners, fragmented legacy systems have become a significant operational liability.
This reliance on unstructured data creates a "spreadsheet tax" - a systemic drain on technical resources that complicates the bid process. When experts must manually extract molecular data from unsearchable PDFs, the resulting delays hinder an organization's ability to model capacity and mitigate risk in real-time. In a market defined by rapid lead times, the competitive advantage belongs to those who can convert raw inquiry data into actionable intelligence in minutes, not weeks.
Join us for the webinar to explore how our AI technologies are reshaping the future of pharmaceutical manufacturing.
The CDMO industry is at a turning point. As demand for complex modalities like ADCs and cell therapies surges, traditional "manual relay" project evaluations are no longer sustainable. With 60% of pharmaceutical organizations now prioritizing AI readiness in their partners, fragmented legacy systems have become a significant operational liability.
This reliance on unstructured data creates a "spreadsheet tax" - a systemic drain on technical resources that complicates the bid process. When experts must manually extract molecular data from unsearchable PDFs, the resulting delays hinder an organization's ability to model capacity and mitigate risk in real-time. In a market defined by rapid lead times, the competitive advantage belongs to those who can convert raw inquiry data into actionable intelligence in minutes, not weeks.
Join us for the webinar to explore how our AI technologies are reshaping the future of pharmaceutical manufacturing.
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Scaling clinico-genomic data integration: Large pharmaceutical organizations working with external data providers used Polly to build interoperable clinico-genomic data products 6x faster.
Although purchased datasets are often labeled as "clean," they still lack interoperability—Polly's pipelines bridge this gap with robust integration and harmonization.
Information Retrieval: Drug safety monitoring teams used Polly's Knowledge Graph powered co-scientist to conversationally retrieve the right cohorts & assess drug response—cutting discovery time by 70%.
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If you’re working with complex biological data, you may be asking:
Can generative AI truly assist in scientific reasoning, not just data analysis?
What does it mean for hypothesis generation, literature review, or even designing experiments?
Could this accelerate—not replace—my discovery pipeline?
Whether you're skeptical, curious, or already experimenting with AI in your lab—this is a session designed to ground your understanding in evidence, not speculation.
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