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AI in Healthcare and Life Sciences Podcast

The AI in Healthcare and Life Sciences Podcast

The AI in Healthcare and Life Sciences Podcast helps healthcare, pharmaceutical, and life sciences leaders understand how artificial intelligence is transforming patient care, drug discovery, clinical research, insurance, and healthcare operations.

Each episode from Emerj AI Research features practical, non-technical conversations with AI leaders, healthcare executives, investors, and industry experts on where AI is creating real business value across healthcare and life sciences.

The show includes insights from organizations such as IQVIA, Takeda, Pfizer, and AstraZeneca, alongside perspectives from venture capitalists investing in AI for healthcare innovation.

Browse the latest episodes below, or follow the show wherever you listen to podcasts.

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How AI Is Closing the Knowledge Gap in MedTech Field Service – with Mohit Sheera of Terumo Blood and Cell Technologies

How AI Is Closing the Knowledge Gap in MedTech Field Service – with Mohit Sheera of Terumo Blood and Cell Technologies

August 6, 2026

Field service leaders in MedTech are facing a widening gap between rising equipment complexity and the technician expertise, data, and parts logistics needed to keep devices running. In this episode, Mohit Sheera, Strategic Planning Leader at Terumo Blood and Cell Technologies, examines how AI-enabled remote diagnostics and multimodal data synthesis are changing who can resolve a service issue and how quickly. The conversation covers technician...

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Closing the Decision‑Making Gap in Healthcare AI – with Raman Kaur of Elsevier

Closing the Decision‑Making Gap in Healthcare AI – with Raman Kaur of Elsevier

June 4, 2026

Fragmented data environments continue to slow clinical and operational decision‑making, even as AI adoption accelerates across healthcare. In this episode, Raman Kaur, Vice President of Technology at Elsevier, examines how leaders can close the gap between information and action with host Yolandi De Weerdt, focusing on context, shared definitions, and workflow‑aligned AI. She highlights the practical shifts required to simplify data foundations, reduce cognitive burden,...

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Rethink Healthcare Workforce Strain with Data Enablement – with Tony Pastorino of Resultant

Rethink Healthcare Workforce Strain with Data Enablement – with Tony Pastorino of Resultant

May 7, 2026

Clinician burnout takes hold long before most healthcare leaders see it, and the signals that could forecast it are often already being collected, but locked inside systems and teams that don't communicate. In this episode, Tony Pastorino, Director of Healthcare Strategy at Resultant, examines how a shift from data governance to what he calls "data enablement", paired with predictive analytics and direct conversations with frontline...

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Driving the Transformation of Drug Discovery Through AI‑Ready Data Foundations – with Barry Bunin of CDD

Driving the Transformation of Drug Discovery Through AI‑Ready Data Foundations – with Barry Bunin of CDD

April 13, 2026

Persistent friction between experimental, computational, chemistry, and biology teams continues to slow discovery work, largely due to siloed data and tools that are too difficult for scientists to adopt. In this episode, Barry Bunin, CEO & President at Collaborative Drug Discovery, examines how simplifying data capture and creating a shared source of truth enables faster iteration, clearer model‑experiment alignment, and more effective collaboration across disciplines....

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AI That Clinicians Can Trust: Building Reliable Clinical Decision Support with Rhett Alden of Elsevier

AI That Clinicians Can Trust: Building Reliable Clinical Decision Support with Rhett Alden of Elsevier

April 2, 2026

Clinicians face a significant trust gap and administrative burden that hinders the effective deployment of AI at the point of care. In this episode, Rhett Alden, CTO at Elsevier, outlines how integrating transparent, peer-reviewed AI assistants directly into clinical workflows can mitigate physician burnout and reduce medical errors. The discussion examines the governance frameworks, data transparency requirements, and specialized training necessary to shift from skeptical...

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