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Today’s guest is Ben Coverdale, Global Account Director of Life Sciences at Patsnap. Patsnap is a healthcare technology company that provides IP and R&D teams with enhanced insights to make informed and timely decisions. Using a specialized AI model and the Hiro assistant, the platform boosts productivity and reduces inefficiencies across the innovation lifecycle. Ben joins us on today’s program to explore the transformative role of generative AI and large language models (LLMs) in life sciences. His discussion with Emerj Senior Editor Matthew DeMello covers how data silos are dissolving as companies adopt integrated LLM strategies, offering new possibilities for collaboration and efficiency. Ben provides insight into the practical applications of LLMs, the promise they hold for optimizing R&D, and the potential impact on the regulatory landscape. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
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33 ratings
Today’s guest is Ben Coverdale, Global Account Director of Life Sciences at Patsnap. Patsnap is a healthcare technology company that provides IP and R&D teams with enhanced insights to make informed and timely decisions. Using a specialized AI model and the Hiro assistant, the platform boosts productivity and reduces inefficiencies across the innovation lifecycle. Ben joins us on today’s program to explore the transformative role of generative AI and large language models (LLMs) in life sciences. His discussion with Emerj Senior Editor Matthew DeMello covers how data silos are dissolving as companies adopt integrated LLM strategies, offering new possibilities for collaboration and efficiency. Ben provides insight into the practical applications of LLMs, the promise they hold for optimizing R&D, and the potential impact on the regulatory landscape. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
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