AI is transforming healthcare by streamlining medical workflows, enhancing drug development, and driving more efficient, data-driven solutions. Krish Ramadurai shares insights on AI-native health tech, digital pathology, and the challenges of scaling automation in biotech, highlighting the impact of technology on the future of medicine.

Picking the right drugs is a high-stakes game. Get it right more often than the competition, and the rewards are massive. Miss a few, and you’re out. So how do top investors and biotech leaders make smart bets? Understanding what pharma actually wants, securing multiple key advocates, and strategically managing risk are all part of the playbook. From clinical-stage assets to investor-backed decision-making, this deep dive unpacks how biotech companies position themselves for success—and what separates the winners from the rest.

AI in healthcare is evolving fast, but how much of it is real progress—and how much is just hype? While AI-driven tools are reshaping clinical workflows and decision-making, many solutions struggle with integration, regulatory hurdles, and real-world adoption. The real winners? Companies that master proprietary data, streamline physician workflows, and build AI solutions that actually work within the constraints of healthcare. From clinical automation to imaging and diagnostics, the impact is undeniable—but replacing doctors? Not happening anytime soon. Where is AI making a real difference, and where is it just noise? Let’s break it down.

Pelu Tran, CEO and founder of Ferrum Health, dives into the revolution of AI in healthcare. He discusses the transformative impact of AI on patient care and clinical workflows, and addresses the fears surrounding job displacement. The conversation highlights the challenges of integrating technology, including costs and data security. Tran emphasizes the importance of balancing automation with human expertise and presents strategies for effective AI onboarding. He envisions a future where innovations can enhance both patient outcomes and medical practices.

AI is transforming biotech, making drug development more predictable. From improving drug discovery to tackling the translatability crisis, new advancements are optimizing clinical success rates. Learn why many AI-designed drugs fail, how human data is reshaping the field, and why repurposing shelved assets might be the next big opportunity in pharma.

Waiting until cancer is already formed before acting? That approach needs to change. Science now has the tools to detect the earliest warning signs—long before a tumor even develops. Breakthrough technologies like AI-driven monitoring and implantable sensors could transform how we detect disease, tracking subtle biological changes in real time. Instead of periodic tests that might miss critical moments, continuous screening could catch cancer in its earliest whispers—when prevention is still possible. If we already know the steps leading to cancer, why aren't we stopping them? The answers might surprise you.

Understanding lab results can be overwhelming, but what if AI could help make sense of the data and improve patient care? Dr. Sanjay Juneja and David Norris explore how artificial intelligence is reshaping healthcare—reducing administrative burdens, detecting conditions like iron deficiency, and streamlining workflows. They also discuss how AI is giving doctors more time with patients by handling routine tasks, easing burnout, and enhancing provider-patient relationships. AI is transforming healthcare by improving efficiency, enhancing patient care, and raising important ethical questions about its role in medical practice.

Cancer detection is long overdue for a revolution. Current screening methods miss too much, cost billions, and often lead to false positives. But what if we could catch cancer at the very first cell—before it ever becomes a threat? A breakthrough technology could make that possible. AI, continuous monitoring, and implantable devices are reshaping how we detect disease, moving beyond outdated methods toward real-time, 24/7 tracking. Imagine a future where cancer is stopped before it even starts. Is this the next big leap in medicine?

Early cancer detection can save lives, yet traditional treatments often focus on late-stage disease. This episode explores the critical need for a shift in approach—studying human cells directly, improving model systems, and building a comprehensive tissue repository to better understand cancer at its earliest stages. Dr. Azra Raza shares insights on key differences in cancer progression between children and adults, along with the ethical and practical challenges of early intervention.

Mika Newton and Dr. Nigam Shah explore whether healthcare technology and AI are addressing the right problems. They discuss the tendency to focus on easy solutions like using language models to respond to patient messages, which may not save time as expected. The conversation highlights the need to redefine goals and use AI for innovative approaches rather than just replicating existing tasks done by humans. They emphasize increasing access and efficiency in healthcare, like using AI for triaging patients and educational interactions, which can free up resources and potentially double service capacity.