In this episode of The Harry Glorikian Show, Dr. David Albert, founder of AliveCor, shares his journey in digital medicine. We discuss the evolution of mobile ECG technology and the integration of AI in cardiology. Dr. Albert emphasizes the importance of patient empowerment and the shift from traditional hospital care to home-based monitoring. We discuss the challenges and innovations in cardiac care and highlight the future of AI in predicting and preventing heart conditions. For more information on AliveCor and their work, visit: https://alivecor.com/

In this episode of The Harry Glorikian Show, Kyle Kiser discusses the origins and evolution of Arrive Health, a company focused on improving healthcare affordability and access through technology. We discuss the company's founding story, the significance of its rebranding, and how it leverages real-time data to assist providers in making informed prescription decisions. We also delve into the challenges of prior authorization and the role of AI in enhancing healthcare efficiency. Harry and Kyle discuss healthcare technology's evolution and impact on medication access and cost transparency. They explore their platform's growth, collaboration with payers and PBMs, and AI's role in streamlining prior authorization. The conversation emphasizes improved medication access, potential service expansion beyond pharmaceuticals, and a patient-centric approach to healthcare access. Kyle closes the talk with insights on future innovations for healthcare innovators, which are always great from the inside out! For more information on Arrive Health and their work, visit: https://arrivehealth.com/

This conversation with Carlos Ciller, founder of Retina AI (now under Ikerian), explores how AI is changing clinical decision-making in real time. Carlos discusses their platform that serves as a diagnostic copilot for physicians, identifying patterns in medical images and alerting doctors to important findings. He explains how their system integrates with clinical workflows, helping physicians make faster decisions while freeing up time for patient care. We also talk about how Ikerian is expanding beyond eye care into detecting neurodegenerative diseases through retinal biomarkers and the growing field where eye scans can reveal systemic health conditions. Carlos shares insights on the challenges of implementing AI in healthcare and his vision for the future where scanning devices might allow patients to monitor multiple health conditions through simple, accessible tests.

In this conversation, Joe DeVivo discusses the significant advancements and transformations at Butterfly Network, focusing on the digital evolution of ultrasound imaging, the integration of AI technologies, and the company's mission to improve global health access. He shares insights on the challenges faced in mainstream adoption and highlights the impact of their devices in humanitarian efforts around the world. In this conversation, Joe DeVivo discusses innovative strategies in the medical device industry, particularly focusing on sales approaches, product-market fit, and the importance of simplicity in technology. He shares insights on how unexpected use cases for handheld ultrasound devices are emerging as doctors adopt them in various settings. DeVivo also explores future innovations in ultrasound technology and emphasizes the critical role of patient data ownership in transforming healthcare.

In this episode, Keith Channon discusses the advancements in cardiac diagnostics through Caristo Diagnostics and their innovative product, Carry Heart. The conversation delves into the persistent issue of heart attacks, the limitations of current diagnostic methods, and how Carry Heart utilizes advanced imaging technology to assess inflammation in coronary arteries, providing a more accurate risk assessment for patients. The discussion also covers the clinical implications of this technology and actionable steps for patients to reduce their risk of cardiovascular events. In this conversation, Keith Channon discusses the evolving landscape of cardiovascular medicine, focusing on the optimization of drug dosing, the integration of AI in risk prediction, and the importance of targeted therapies. He highlights the potential of new technologies to enhance patient outcomes and the need for regulatory approval to facilitate wider clinical use. The discussion also touches on the significance of understanding inflammation in cardiovascular disease and the future applications of these advancements beyond cardiology.

In this episode of The Harry Glorikian Show, host Harry Glorikian welcomes back Jeff Elton, CEO of Concert AI, to discuss the latest advancements in AI-driven healthcare solutions. They reflect on the recent JP Morgan Healthcare Conference, highlighting the optimism surrounding AI's role in transforming drug development and oncology. Jeff shares insights into Concert AI's innovative data ecosystems, partnerships, and the introduction of Kera, an AI platform designed to enhance clinical decision-making. The conversation also explores the challenges and opportunities in the evolving landscape of healthcare technology, emphasizing the importance of collaboration and adaptability in the face of rapid change.

Harry's guest this week is Raffi Krikorian, chief technology officer and managing director at Emerson Collective, the social change organization founded by Laurene Powell Jobs. Krikorian is the former vice president of engineering at Twitter (now X), where he was responsible for getting rid of the Fail Whale and making the company’s backend infrastructure more reliable; the former director of Uber's Advanced Technology Center in Pittsburgh, where he oversaw the launch of the world's first fleet of self-driving cars; and then the chief technology officer at the Democratic National Committee, where he helped rebuild the party's technology infrastructure after the Russian hacking debacle of 2016. At Emerson Collective, Krikorian built the technology organization, leads the development of data products, and works to upgrade the back offices of the non-profits Emerson works with. On top of all that, he recently launched a podcast called Technically Optimistic, where he’s taking a deep dive into the way AI is challenging us all to think differently about the future of work, education, policy, regulation, creativity, copyright, and many other areas. The show is a must-listen for anyone who cares about how we can build on AI to transform society for the better while minimizing the collateral damage. Harry talked with Krikorian about why he moved to Emerson Collective, why and how he started the podcast, and what he really thinks about what government should be doing to prepare for the waves of social change AI will bring.

Generative AI isn’t magic. You can’t just  sprinkle it like pixie dust over an existing project or dataset and expect wonderful things to happen automatically. In fact, just to use the data you already have, you have to you may have to invest a lot in the new infrastructure and tools needed to train a generative model. And that’s the part of the puzzle Harry focuses on in today's interview with David Buniatyan. He’s the founder of a company called ActiveLoop, which is trying to address the need for infrastructure capable of handling large-scale data for AI applications. He has a background in neuroscience from Princeton University, where he was part of a team working on reconstructing neural connectivity in mouse brains using petabyte-scale imaging data. At ActiveLoop, David has led the development of Deep Lake, a database optimized for AI and deep learning models trained on equally large datasets. He says the company’s goal is to take over the boring stuff. That means removing the burden of data management from scientists and engineers, so they can focus on the bigger questions—like making sure their models are training on the right data—and ultimately innovate faster.

Harry's guests this week are Frank Cheng, CEO of UK-based Caristo Diagnostics, and Keith Channon, Caristo's co-founder and chief medical officer. Under their leadership, Caristo has introduced an AI-based test called CariHeart that applies machine learning to the data in a three-dimensional CT scan of the heart. It looks for signs of inflammation in the fat tissue around the major coronary arteries—a risk factor that's often overlooked because it isn't always accompanied by plaque or narrowing of the arteries. Doctors can use that information to decide whether a patient needs to take a cholesterol-lowering drug like a statin or an anti-inflammatory drug like colchicine. Caristo’s test is being used on an experimental basis in the UK, and it hasn’t yet been approved for use in the US. But it’s a leading example of the way AI, put together with fundamental advances in our understanding of human biology, is really beginning to change the practice of medicine.

If you believe that computation will help companies get better at developing new drugs, then what specific kind of computation and software should you invest in? Quantum chemistry simulations? Molecular dynamics simulations? Generative AI models? Harry's guests this week, Garegin Papaoian and Michael Antonov, lead a company called Deep Origin that's taking an all-of-the-above approach. The company’s philosophy is that physics-based modeling by itself won’t be enough to build a powerful drug discovery engine. But neither will generative AI, which requires more training data than lab scientists will ever be able to provide. They think the only reasonable approach today is to combine the two, and use both physics and AI to try to get better at predicting which molecules could become effective drugs. It’s important stuff, because if Deep Origin is right, then a lot of other more specialized biotech and techbio startups could be going down the wrong path.