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The AI in Business Podcast

AI for Supply Chain Challenges in Life Sciences - with Shreyas Becker of Sanofi

Apr 9, 2024
20:34
Snipd AI
Shreyas Becker from Sanofi discusses using AI to tackle supply chain challenges in life sciences. Topics include real-world evidence delivery, sharing sensorial data with big tech, and how data drives problem-solving. The podcast sheds light on the complexities of bio manufacturing, standardization challenges, key quality metrics, and AI's impact on efficiency in life sciences.
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Podcast summary created with Snipd AI

Quick takeaways

  • Bio manufacturing poses challenges in predictability due to live organism variability, emphasizing the need for data-driven solutions.
  • Quality and yield are crucial in life sciences manufacturing, focusing on product quality, toxicity, and resource efficiency.

Deep dives

Challenges in Bio Manufacturing: Managing Variations in Production Output

Bio manufacturing presents challenges in predicting and controlling production output, unlike traditional manufacturing processes. For example, making drugs through bio manufacturing involves live organisms that introduce variability in output quantities, requiring a focus on predictability and reliability. Analogies like baking bread highlight the complexities of variables such as ingredient quality, environmental conditions, and process consistency affecting final output, underscoring the need for extensive monitoring and data-driven solutions.

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