The Use of Generative AI in Pharma (Emmanuel Walckenaer in Pharmaphorum)

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Generative AI in pharma is particularly gaining momentum, with many leading companies in life sciences already utilizing AI solutions and innovative technologies to increase productivity and efficiency across the board. With the use of Large Language Models (LLMs) and advanced machine learning techniques to create new, human-like text and imagery from existing data and experiences, generative AI can enhance how humans perform everyday tasks and work across industries. 

To utilize generative AI in pharma, it’s important to ensure the technology is applied correctly with data that is proprietary and only available confidentially. It’s essential to consider fundamental customer needs, such as transparency, bias and fairness, data isolation, and the auditability of results.  

While it’s disrupting all industries, generative AI has the potential to impact the way pharma companies have approached traditional processes. Benefits include:

  • Production of large amounts of data quickly and at scale, while ensuring accuracy 
  • Drug development acceleration, allowing companies to gain a competitive edge and bring life saving drugs to market
  • Success of identifying disease patterns in larger datasets
  • Empower data scientists, analysts and medical writers to focus on more strategic initiatives.

Automation in a highly regulated landscape is complex and should be approached with caution. As pharma companies continue to express interest in leveraging components of LLMs into their workflows, it’s important they collaborate with a vendor that takes a data and human-centric approach to implementation. 

Yseop’s CEO, Emmanuel Walckenaer elaborates more on the future of generative AI in Pharmaphorum – read more here: 

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