Today’s guest is Rhett Alden, Chief Technology Officer at Elsevier. Elsevier is a global leader in information analytics and academic publishing, providing trusted scientific, technical, and medical content for researchers, clinicians, and professionals. Rhett returns to the podcast to explore how AI is reshaping healthcare education by bridging the gap between emerging technologies and traditional training methods. In this episode, Rhett shares how Elsevier is applying generative AI to enhance procedural training for healthcare students and professionals while emphasizing the continued importance of human-led instruction for conceptual understanding, ethical decision-making, and patient empathy. He also discusses the increasing adoption of AI across healthcare education institutions and the need for thoughtful implementation models that preserve quality and support human connection in learning environments. Want to share your AI adoption story with executive peers? Click emerj.com/ex2 for more information and to be a potential future guest on Emerj’s flagship’ AI in Business’ podcast!

Today’s guest is Rhett Alden, Chief Technology Officer at Elsevier. Elsevier is a global leader in information analytics and academic publishing, providing trusted scientific, technical, and medical content for researchers, clinicians, and professionals. Rhett joins us on today’s show to discuss how Elsevier is tackling hallucinations in AI frameworks to deliver reliable, peer-reviewed medical and scientific information. Alden explains how retrieval-augmented generation (RAG) models differ from large language models (LLMs), ensuring that AI-generated responses are grounded in verifiable, high-quality sources. He shares how Elsevier integrates precision, completeness, bias mitigation, and harm reduction into its evaluation framework, providing transparency for clinicians who depend on AI-assisted insights. 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!

Today’s guest is Fred Manby, CTO and Co-founder of Iambic Therapeutics. Iambic uses algorithms to drive a high-throughput experimental platform that specializes in developing new drug discovery techniques. Fred returns to the program to explore the next frontier of AI-driven drug discovery. Building on the previous discussion, this episode delves into the transformative role of automation, data generation, and predictive modeling in pharmaceutical development. This episode is sponsored by Iambic Therapeutics. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Today’s guest is Fred Manby, CTO and Co-founder of Iambic Therapeutics. Iambic uses algorithms to drive a high-throughput experimental platform that specializes in developing new drug discovery techniques. Fred joins us on today’s program to discuss the evolving landscape of drug discovery in life sciences. With AI playing an increasingly critical role, the conversation explores the biggest challenges facing drug discovery workflows and how life sciences leaders can better leverage data-driven tools to address them. 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!

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 returns to the show to dive deeper into the real-world applications of generative AI and large language models (LLMs) that are reshaping the drug discovery landscape. He provides a closer look at use cases where AI is not just enhancing traditional processes but enabling entirely new possibilities in drug targeting and sequencing that were previously unimaginable. 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!

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!

Today’s guest is Rajvir Madan, Chief Digital and Information Technology Officer at Arcutis Biotherapeutics. Arcutis Biotherapeutics is a biopharmaceutical company that develops therapies for skin-related conditions. Rajvir joins us on today’s show to explore the pressing challenges and exciting opportunities within the life sciences industry. From long development timelines to the complexities of regulatory submissions, Rajvir highlights why the traditional approach to bringing new treatments to market—often spanning over a decade—needs urgent rethinking. 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!

Today’s guest is RJ Kedziora, Co-founder, Partner, Chief Operating Officer, and Chief Technology Officer at Estenda Solutions. Estenda is a healthcare and medical custom software development, data analytics, and consulting company with 20 years of experience in digital health. RJ joins us on today’s episode to explore where the industry is seeing use cases for leveraging new AI capabilities to help drive data efficiencies. Once these technologies are commonplace, RJ shares what he thinks the future of data in healthcare spaces is going to look like. To discover more AI use cases, best practice guides, white papers, frameworks, and more, join Emerj Plus at emerj.com/p1.

Today’s guest is RJ Kedziora, Co-founder, Partner, and Chief Operating and Technology Officer at Estenda Solutions. Estenda is a healthcare and medical custom software development, data analytics, and consulting company with 20 years of experience in digital health. RJ joins us on today’s program to talk about challenges for healthcare leaders in driving the data necessary to take advantage of these new use cases in generative AI and beyond. Throughout the episode, RJ provides measured and tested frameworks for tackling new opportunities in the standardization and interoperability of healthcare systems, especially where they intersect with the need for data sharing across the sector and what that means for HIPAA protections. To access Emerj’s frameworks for AI readiness, ROI, and strategy, visit Emerj Plus at emerj.com/p1.

Today’s guest is Xiong Liu, Director of Data Science and AI at Novartis. Xiong joins us on the program today to offer life sciences leaders a framework for driving meaningful data infrastructure advancements at their organizations. Xiong emphasizes the need for robust data quality, ethics considerations, and scalability to ensure practical applications in real-life use cases. Later, he highlights the importance of understanding customer perspectives, aligning business goals with AI efforts, and leveraging graph databases to manage large-scale healthcare data. 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!