AI and Healthcare

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.

Join Dr. Sanjay Juneja and Columbia University professor Dr. Azra Raza in an in-depth discussion about the transformative potential of AI and technology in early cancer detection. Dr. Raza shares her insights on how continuous monitoring and innovative technologies could find cancer at the 'first cell stage,' long before traditional methods. Learn about her journey from pediatric oncology to establishing one of the richest tissue repositories, and discover how AI-powered implantable devices could revolutionize the future of healthcare. This episode sheds light on the untapped possibilities in proactive cancer care and the critical shift needed to focus on early detection.

This episode features Nigam Shah discussing the sustainability of AI in healthcare, focusing on challenges in development, validation, and regulation. The conversation explores the limitations of current AI models, the evolving role of governance, and the need for localized validation to ensure accuracy and relevance.

In this episode, Mika Newton speaks with Dr. Nigam Shah, a professor at Stanford and Chief Data Scientist at Stanford Healthcare, about the challenges and opportunities of AI in healthcare. They discuss the sustainability of AI development, the complexities of regulation, and the importance of localized validation. The conversation explores how AI can enhance clinical decision-making, optimize healthcare resources, and expand patient access while addressing barriers in implementation, governance, and data sharing.

This podcast episode explores the intersection of AI and healthcare, focusing on drug development, repurposing, and access to medical treatments. Mika Newton speaks with Bob Battista about the challenges of sharing pharmaceutical data, regulatory barriers, and how AI could enhance clinical decision-making. They discuss real-world data, patient knowledge, and the role of technology in optimizing treatment pathways. The conversation also touches on privacy laws, governance, and the potential for AI to empower patients with better access to medical insights. Viewers will gain a deeper understanding of how innovation and policy changes could improve healthcare outcomes.

Bob Battista, an expert in AI and healthcare, dives into the revolutionary potential of AI in reshaping patient autonomy. He highlights how AI can enhance decision-making by processing vast clinical data, allowing patients to take charge of their health. The conversation addresses critical issues around data sharing and governance, comparing AI in healthcare to self-driving cars. Ultimately, they explore the vital role of improving health literacy to empower patients in navigating AI-driven support for better treatment outcomes.

Mika Newton and Bob Battista dive into how AI is revolutionizing healthcare decision-making. They discuss AI's ability to analyze clinical evidence and personalize treatment recommendations. The conversation highlights the challenges of regulatory restrictions and data silos that hinder progress. They emphasize the importance of accessible data for maximizing AI's potential and explore how adaptable healthcare guidelines can enhance patient outcomes, particularly in oncology.

Drug repurposing offers a way to find new treatments using existing medications, but regulatory hurdles and financial disincentives often prevent progress. Mika Newton and Bob Battista examine the challenges of data sharing in the pharmaceutical industry, the high costs of clinical trials, and why companies hesitate to pursue niche indications. They also explore potential policy solutions that could encourage collaboration and make more life-saving treatments accessible to patients.

Mika Newton and Tom Neyarapally discuss how AI is changing the landscape of drug discovery. They examine the role of machine learning, patient data, and computational tools in accelerating the process, reducing costs, and improving the chances of developing effective treatments. The conversation covers how AI-driven screening, drug repurposing, and real-world data integration are helping to overcome traditional challenges in bringing new therapies to patients faster. They also examine the potential for collaboration between AI technology and clinical expertise to drive future breakthroughs in medicine.