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.

The future of healthcare is evolving rapidly, and technology is playing a bigger role than ever. Pelu Tran shares insights on how AI, data-driven decision-making, and digital tools are reshaping patient care and the way doctors work. From improving clinical workflows to making healthcare more accessible, these innovations are changing the industry in real time. We also explore the challenges of integrating new technology, the balance between automation and human expertise, and what the next decade of healthcare could look like. How will these advancements impact both patients and medical professionals?

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.

Mika Newton speaks with Dr. Nigam Shah, a Stanford professor and Chief Data Scientist at Stanford Healthcare, about AI’s role in healthcare. They discuss evaluating AI’s impact on patient care, the challenges of benchmarking AI models, and the importance of using real-world data. The conversation explores how AI can enhance clinical decision-making, the need for well-defined research questions, and strategies for selecting the right data to improve healthcare outcomes.

AI is reshaping healthcare, from clinical workflows to drug discovery and the rise of full-stack biotech companies. But what are the real challenges, and where is AI falling short? Mika Newton sits down with Krish Ramadurai from AIX Ventures to break down the complexities of AI in healthcare, the importance of domain expertise, and the push to automate clinical development. They also discuss how startups can navigate the industry’s regulatory landscape and what investors are looking for in AI-driven healthcare solutions. Whether you're in biotech, investing, or just curious about the future of AI, this discussion offers valuable insights.