AI and Healthcare

Breaking Healthcare’s Bottleneck: AI, Data & Policy Fixes with Bob Battista and Mika Newton - Full Podcast

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.

Who is responsible for AI decisions?—with Mika Newton

Mika Newton and Bob Battista explore how AI could reshape healthcare by giving patients greater control over their medical decisions. They discuss the potential for AI to process vast amounts of clinical data, improve access to relevant treatments, and bridge gaps in health literacy. The conversation also raises important questions about data sharing, patient autonomy, and the future of AI-driven support in medicine.

How is AI Changing Healthcare Decision Making?—with Mika Newton

Mika Newton and Bob Battista discuss how AI is shaping healthcare decision-making. They explore its role in analyzing clinical evidence, updating guidelines dynamically, and personalizing treatment recommendations. The conversation also highlights challenges like regulatory restrictions and data silos that limit AI’s full potential in the industry.

What is the biggest hurdle in drug repurposing today?—with Mika Newton

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.

How AI Screening Is Shaping the Future of Drug Discovery with Tom Neyarapally and Mika Newton

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.

What’s the future of AI in transforming drug discovery?—with Mika Newton

Mika Newton and Tom Neyarapally explore how advancements in AI are accelerating the development of new algorithms, improving target discovery, and enhancing high-throughput screening. The conversation highlights the challenges and opportunities in aggregating innovative technologies, the convergence of AI tools in healthcare, and the potential for personalized and economically viable drug development.

How does AI driven screening speed up cancer treatment R&D?—with Mika Newton

Explore how AI is transforming drug discovery by enabling the rapid screening of billions of molecules and identifying new uses for existing drugs. This approach integrates patient data with advanced tools to predict effective treatments for diseases with unmet medical needs, significantly reducing the time and cost of development.

AI's Role in Modern Healthcare with Dr. Debra Patt and Dr. Sanjay Juneja

In this episode, Dr. Sanjay Janeja and Dr. Debra Patt discuss AI in healthcare. They cover its applications in cancer care, from improving diagnostics and treatment decisions to enhancing patient education and real-time symptom management. The conversation also highlights AI's potential in drug discovery, reducing healthcare costs, optimizing administrative workflows, and addressing the challenges of data integration and biases in AI systems. Together, they emphasize the importance of collaboration between clinicians and digital tools to deliver better, more efficient patient care.