Unlocking Valuable Clinical Trial Study Data with AI Data Extraction.

Practical Case Study with Bayer Consumer Health and Capgemini Engineering

Life Science organizations face the challenge of extracting valuable data from vast amounts of documents for current and future projects, and business insights. It can hinder decision-making and delay critical research advancements and product developments.

This webinar offers actionable insights from a real case study. It will highlight how to set up a data pipeline that extracts and transforms data from clinical trial studies without the need for coding expertise.

Key Takeaways: 

  • How to overcome challenges associated with extracting insights from a high volume of complex documents?
  • What are the potential cost-saving opportunities associated with leveraging AI data extraction technology in Life Sciences research and development?
  • How "Human-in-the-Loop" designs ensure data accuracy, reliability, and consistency when extracting insights from large volumes of documents?
  • What practical steps to take in order to integrate AI data extraction solutions into existing workflows and processes effectively?

Agenda:

  • 5 min  -  Welcome and Introduction (Martin Keller, CEO of ACODIS)
  • 15 min - Business Impact and Key Challenges and Learnings of extracting data from unstructured sources (Dr. Shannon Montgomery, Data Scientist, CAPGEMINI ENGINEERING)
  • 15 min - How to scale and extract high-quality data with AI-powered solution? (Martin Keller, CEO of ACODIS) 
  • 10 min -  Q&A