Digital twins—AI-powered models based on individual health data—are poised to transform how healthcare predicts, treats, and personalizes care. But Jason Alan Snyder, a technologist and futurist, raises powerful ethical and technical concerns about how these systems are being deployed today. Built from EHRs, lab results, wearables, and even genomics, these digital representations can simulate decisions and even replace human judgment. Yet they are often created without consent or clarity. In this clip, Snyder urges healthcare leaders to reclaim agency over the design and governance of these digital surrogates, emphasizing that the future of AI in healthcare must be rooted in truth, transparency, and trust.
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Highlights
What’s next for AI in drug discovery and development? Tom Neyarapally, CEO of Archetype Therapeutics, shares his outlook on how converging technologies—from LLMs to spatial omics—are reshaping how we discover and deliver drugs. He emphasizes that while AI tools are evolving rapidly, the integration of diverse data modalities and collaborative innovation between nimble startups and large pharma is essential. Neyarapally also touches on reducing late-stage trial failures and costs—key challenges that AI is finally beginning to address. For stakeholders focused on AI in drug development, this conversation offers both strategic insight and practical optimism.
David Norris, a lifelong technologist and healthcare innovator, unpacks why AI—especially large language models (LLMs)—is gaining rapid traction in healthcare. With decades of progress converging in recent breakthroughs, Norris outlines how AI can now handle tasks from reading faxes to calling patients about lab results. He emphasizes the practical LLM use cases in healthcare that free clinicians from administrative burdens, allowing more time for patient care. This transformation isn't about replacing jobs—it's about restoring the human connection in medicine by shifting repetitive tasks to AI. The conversation brings clarity to the real benefits of AI in healthcare and where it's headed next.
In this insightful discussion, Pelu Tran explores the practical role of artificial intelligence in enhancing clinician productivity and navigating the widespread inefficiencies in healthcare. Drawing from Ferrum Health’s platform, Tran explains how AI enables faster diagnosis, supports care coordination, and amplifies provider capacity—particularly in overburdened fields like radiology. He also highlights the real cost of AI adoption, pointing to the significant resources required to integrate AI into existing healthcare systems. This conversation sheds light on the evolving impact of AI for healthcare productivity and reframes the debate: it’s not just about quality vs. efficiency—it’s about enabling clinicians to sustain care at scale.
In this compelling interview, Dr. Azra Raza challenges the traditional focus of oncology, arguing that early cancer detection should be the central pillar of cancer research and treatment. Sharing her personal journey as an immigrant and oncologist, Dr. Raza critiques the widespread reliance on animal models and late-stage therapies, advocating instead for the study of human tissue and the identification of disease at its earliest stages. Her lifelong work in hematologic malignancies, particularly myelodysplastic syndromes, underscores the urgency of this shift. By focusing on “the first cell” rather than the last, she highlights how early intervention could dramatically reduce suffering and improve survival—raising critical questions about current priorities in cancer care and the persistent challenges in cancer treatment.
In this compelling conversation, Dr. David Fajgenbaum describes how his team uses a platform called Matrix, powered by a biomedical knowledge graph, to scan all known relationships between drugs, diseases, and genes. The goal? To apply AI for healthcare data analysis in identifying potential treatments, some of which had been previously overlooked or discarded due to lack of profitability. One powerful example includes the identification of a TNF inhibitor for Castleman disease that led to a lifesaving intervention. Dr. Fajgenbaum emphasizes how this technology doesn't just discover new solutions but also revalidates forgotten ones, shedding light on opportunities to repurpose existing drugs. This showcases the transformative potential of AI predictive analytics in healthcare.
In this clip, Dr. Alister Martin outlines how both AI and healthcare policy can reduce the cost of care. While his organization, A Healthier Democracy, remains people-first in its approach, Dr. Martin strongly advocates for AI upskilling as essential in the modern workforce. He warns that it's not AI that will replace workers, but workers who use AI that will replace those who don't. On the policy side, Dr. Martin makes a compelling case for maintaining reimbursement pathways through Medicare and Medicaid to sustain initiatives that demonstrably lower emergency room visits and hospitalizations—highlighting the cost-effectiveness of AI in healthcare. His remarks provide actionable direction for organizations aiming to use AI for healthcare cost saving strategies.
In this insightful interview, Dr. Debra Patt shares how AI applications in healthcare are transforming the daily realities of clinical care. As a breast medical oncologist and health policy leader, she describes the power of ambient AI scribe technology, which reduces administrative burdens and improves patient communication by instantly generating visit notes. She outlines specific benefits—from more accurate ICD-10 coding to enhanced decision-making in cancer care—that not only help providers get patients the right treatment faster, but also streamline billing and prior authorization. Her perspective offers a grounded, real-world view of "what are the applications of AI in healthcare" today, especially for oncology practices navigating high patient loads and value-based care demands.
Can AI replace doctors—or is it here to restore what’s been lost in medicine? David Norris, CEO of Affineon Health, tackles this provocative question with depth and clarity. Far from eliminating physicians, Norris argues that AI solutions are essential for addressing physician burnout, streamlining administrative tasks, and reviving the human relationship between doctors and patients. He illustrates how AI, like Affineon’s $2.50/day AI assistant, can triage clinical inboxes, flag clinically significant lab trends, and bring 10 years of patient history into a three-second review—freeing doctors to focus on what matters most. This conversation is a must-watch for anyone curious about how AI is reshaping the future of care.
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