Artificial intelligence (AI) continues to be a game-changer across a wide range of industries, especially with the advent of ChatGPT and Large Language Models. Biopharma is no different, and pharmaceutical companies and contract research organizations (CROs) are feeling increased urgency to integrate AI into their labs and workflows.

Despite the potential value however, laboratories have been tentative and even sluggish for a variety of reasons. With the right AI strategy, research organizations can maximize the output of in-house scientific staff, with minimal IT involvement, and seamlessly scale as their research needs grow. After reading, you’ll understand:

• Using AI as a Valued Partner in Research - When properly tailored to a lab’s needs, AI technology can fundamentally change the scientists’ work and becomes an indispensable research partner.
• The Role of AI in Streamlining Scientific Workflows - A key advantage of leveraging AI in drug development is freeing scientists from mundane and repetitive tasks, allowing them to focus on high-value scientific work.
• The Limitations of Data Management-Only Solutions - To harness the true power of AI in drug development, R&D organizations need technology infrastructure specifically built for scientific data.
• Seamlessly Transitioning to AI for Biopharma - Enthought is uniquely positioned to help biopharma companies transition from outmoded approaches in R&D to AI-driven solutions while preparing for what’s coming next.

​