At The Harry Glorikian Show, I, Harry Glorikian, am your host. In short, I have talks with leaders in the healthcare & life sciences industry about the ongoing data-driven transformation of their industry.
From new ways to diagnose & treat patients, bring down costs & creating new value, all the way to AI algorithms that increase efficiency & accuracy, better data is revolutionizing healthcare.
I turn to doctors, hospital administrators, IT directors, entrepreneurs, & others for help mapping out the changes & their impact on everyone from patients to researchers.
Welcome to the show!
Site
RSS
Apple
Data updated on 14/07/2026
Recent rankings
Latest chart positions across Apple Podcasts and Spotify rankings.
Shared links between episodes and podcasts
Links found in episode descriptions and other podcasts that share them.
Discover shows related to The Harry Glorikian Show, based on actual content similarities. Explore podcasts with similar topics, themes, and formats, backed by real data.
Dr. David Albert and The AI Revolution in Cardiology
Episode 141
Tuesday, July 15, 2025 • Duration 45:39
🎙️ In this episode, we discuss:
00:00 The Journey of an Innovator
06:27 The Birth of a Smartphone ECG
11:29 Overcoming Resistance in Digital Health
16:20 The Evolution of ECG Technology
23:43 The Importance of Early Detection in Cardiac Care
26:20 Innovations in 12-Lead ECG Technology
29:00 AI and Machine Learning in Cardiac Diagnostics
34:23 Remote Monitoring and Patient Empowerment
38:34 Navigating AI Diagnostics: Sensitivity vs Specificity
41:26 Consumer Wearables vs. Medical Devices
43:14 Future of AI in Cardiology and Personal Health Awareness
Kyle Kiser is Using AI to Make Your Patient Experience Better
Episode 140
Tuesday, July 1, 2025 • Duration 40:13
🎙️ In this episode, we discuss:
00:00 The Origin Story of Arrive Health
06:04 Rebranding and Evolving Mission
11:50 Real-Time Patient-Specific Drug Costs
18:08 Tackling Prior Authorization Challenges
22:56 Leveraging AI for Healthcare Efficiency
25:36 Understanding Scale and Impact
28:04 Collaboration with Payers and PBMs
30:27 Leveraging AI for Prior Authorization
32:43 Enhancing Access to Medications
36:27 Expanding Beyond Medications
38:19 Reframing Access to Care
40:51 Future Directions and Innovations
44:55 Wisdom for Innovators in Healthcare
Making better real-time clinical decisions with AI
Episode 139
Thursday, May 1, 2025 • Duration 38:57
🎙️ In this episode we discuss:
01:06 The founding story of Retina AI
03:56 Why ophthalmology is uniquely suited for AI solutions
06:27 Recent Series B funding and what it means for the company
08:31 How AI integrates into real-world clinical workflows
12:04 AI alerts and notifications for clinical decision support
16:36 Working with pharmaceutical companies on clinical trials
19:15 Predicting disease progression for untreated patients
25:42 The transition from traditional AI to newer approaches
29:28 Expanding beyond eye care with the Ikerian rebrand
32:06 Using the eye as a window to detect other diseases
37:44 How physicians have responded to AI diagnostic tools
41:09 Predictions for AI in healthcare and eye care by 2028
Future of Ultrasound: Innovations Ahead
Episode 138
Tuesday, April 15, 2025 • Duration 51:26
Chapters
00:00 Introduction and Company Updates
02:49 The Digital Transformation of Ultrasound Imaging
06:00 Advancements in Technology and Market Growth
09:03 AI Integration in Medical Imaging
14:50 Impact on Global Health and Humanitarian Efforts
20:55 Challenges in Mainstream Adoption of Handheld Ultrasound
29:43 Strategic Sales Approaches in Medical Devices
34:11 Finding Product-Market Fit
36:12 Simplicity in Medical Technology
39:26 Unexpected Use Cases and Market Adoption
45:24 Future Innovations in Handheld Ultrasound
51:58 The Importance of Patient Data Ownership
Revolutionizing Cardiovascular Care with AI
Episode 137
Tuesday, April 1, 2025 • Duration 56:28
00:00 Introduction and Overview of Caristo Diagnostics
09:08 The Technology Behind Carry Heart
18:00 Clinical Implications and Risk Assessment
27:27 Actionable Steps for Patients
30:34 Optimizing Cardiovascular Drug Dosing
32:31 AI in Cardiovascular Medicine
33:50 Leveraging Historical Data for Risk Prediction
36:25 AI's Role in Molecular Pathway Analysis
39:03 GLP-1 and Cardiovascular Outcomes
41:56 Targeted Therapies in Cardiovascular Treatment
42:45 Building Trust in New Technologies
49:16 Regulatory Approvals and Future Prospects
54:15 Expanding Applications Beyond Cardiology
57:16 Looking Ahead: The Future of Caristo Diagnostics
Al's Transformative Role in Pharma ConcertAl CEO Jeff Elton
Episode 136
Tuesday, February 11, 2025 • Duration 56:53
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.
Takeaways:
The JP Morgan Healthcare Conference indicated a positive outlook for the industry.
AI is becoming a central theme in healthcare discussions.
Concert AI is developing a comprehensive data ecosystem for oncology.
The introduction of agentic AI models is set to revolutionize data processing.
Collaboration with NVIDIA is enhancing Concert AI's capabilities.
Kera is a significant advancement in AI-driven healthcare solutions.
The future of drug development will rely heavily on AI and data analytics.
Healthcare organizations must adapt to the rapid pace of technological change.
Building partnerships is crucial for addressing healthcare fragmentation.
The integration of AI in clinical trials can significantly reduce timelines.
Chapters
00:00 The Annual Healthcare Pilgrimage
03:19 Optimism in the Pharma Industry
06:07 The Rise of AI in Healthcare
10:03 Concert AI's Evolution and Innovations
Raffi Krikorian Says "We Don't Have Much Time Left" to Rein in AI
Episode 135
Tuesday, April 9, 2024 • Duration 59:05
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.
Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify!
Here's how to do that on Apple Podcasts:
1. Open the Podcasts app on your iPhone, iPad, or Mac.
2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.
Scroll down to find the subhead titled "Ratings & Reviews."
How ActiveLoop Is Building the Back End for Generative AI
Episode 134
Tuesday, March 26, 2024 • Duration 01:02:42
Generative AI is going to change how we do things across the entire economy, including the fields Harry covers on the show, namely healthcare delivery, drug discovery, and drug development. But we’re still just starting to figure out exactly how it’s going to change things. For example, AI is already speeding up the process of discovering new biological targets for drugs and designing molecules to hit those targets—but whether that will actually lead to better medicines, or create a new generation of AI-driven pharmaceutical companies, are still unanswered questions.
One thing that’s for sure is that 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.
Deep Lake manages data in a tensor-native format, allowing for faster iterations when training generative models. David 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.
Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify!
Here's how to do that on Apple Podcasts:
Open the Podcasts app on your iPhone, iPad, or Mac.
How Caristo is Using AI to Reduce Heart Attack Risk
Episode 133
Tuesday, March 12, 2024 • Duration 01:04:20
If you learned that radiologists looking at CT scans for the traditional signs of coronary artery disease catch only 20 percent of the people who actually have a high risk of a heart attack, and if you learned that there’s a new AI-based test that can catch subtle signs of inflammation in the other 80 percent of patients—well, you’d probably want to get that test yourself, right? Harry's guests this week, Frank Cheng and Keith Channon, are from a UK-based company that has developed just such a test. Cheng is the company's CEO, and Channon is co-founder and chief medical officer. And under their leadership, Caristo has introduced a test called CariHeart that applies machine learning to the data in a three-dimensional CT scan of the heart. It looks for otherwise invisible signs of inflammation in the fat tissue around the major coronary arteries, and then it predicts the chances that the patient will suffer a heart attack in the next eight years. 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. Cheng and Channon say Caristo’s test isn’t intended to put cardiologists or radiologists out of work—it’s designed to help them be more effective. And given that cardiovascular disease is the number one cause of death around the world, any technology that can help catch signs of coronary artery disease earlier could save a lot of lives.
Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify!
Here's how to do that on Apple Podcasts:
1. Open the Podcasts app on your iPhone, iPad, or Mac.
2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.
Why Deep Origin Is Betting on Both Physics and AI for Drug Discovery
Episode 132
Tuesday, February 27, 2024 • Duration 51:17
Investors and companies in the life science industry have been betting a lot of money over the last few years on a single idea: that computation will help us get a lot better at developing new drugs. But the word “computation” covers a pretty broad range of techniques. And the reason that there are dozens if not hundreds of computational drug discovery startups popping up is that everyone has their own hypothesis about what specific kind of computation is going to be the most powerful.
For example, you might be convinced that the most important thing is to understand the physics of protein-protein interactions, at an atomic level. And so you would put your money into atomic-scale simulations that show how proteins fold or unfold to form different shapes under different conditions. Or you might think that it’s more important to model proteins at the molecular scale, to make predictions about whether and how a particular drug molecule might dock with a target protein. Or you might think that it’s smarter to try to model whole cells and see how different molecular pathways interact to affect different functions of the cell. Or you might not care about the details of physics- or chemistry-based models at all. In that case could just take a big generative AI model, similar to a large language model, and train it on huge amounts of unlabeled data about genes and proteins in diseases cells and healthy cells to see what kinds of predictions it comes up with.
It’s too early to say which of these computational approaches—and which level or scale of focus—is going to be the most fruitful. But maybe you don’t have to choose. Maybe you can bet on all of these different ideas, all at once. Harry's guests this week are the CEO and CSO of a startup that’s taking an all-of-the-above approach. It’s called Deep Origin, and it was formed last year from the merger of two companies founded by theoretical chemist Garegin Papoian and software builder Michael Antonov.
Antonov helped to found the virtual reality hardware company Oculus. After Facebook acquired Oculus, he got curious about longevity and how software could help untangle the trillions of gene-protein interactions that mediate health and disease. He founded a company called Formic Labs to dig into that problem, and last year the company changed its name to Deep Origin. Papoian, meanwhile, is a former academic scientist who’s who also took the helm as CEO of his startup AI and who’s interested in how to use software to model molecular dynamics and quantum chemistry.
15:10 2024: A Standout Year for Concert AI
18:55 Balancing Growth and Innovation
22:33 Scaling Across Therapeutic Areas
26:26 The Future of Collaborations in Healthcare
28:37 Integrating Immune Status and Data Collaboration
31:04 Introducing Kera AI: The Future of Data Management
35:24 Innovations in Clinical Trials and Data Solutions
40:16 Rethinking Drug Development: Digital Twins and AI
42:36 Navigating Market Shifts and Talent Challenges
54:02 The Future of Concert AI and Healthcare Solutions
3.
4. Under one of the highlighted reviews, select "Write a Review."
5. Next, select a star rating at the top — you have the option of choosing between one and five stars.
6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.
7. Once you've finished, select "Send" or "Save" in the top-right corner.
8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out.
9. After selecting a nickname, tap OK. Your review may not be immediately visible.
On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!
1.
2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.
3. Scroll down to find the subhead titled "Ratings & Reviews."
4. Under one of the highlighted reviews, select "Write a Review."
5. Next, select a star rating at the top — you have the option of choosing between one and five stars.
6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.
7. Once you've finished, select "Send" or "Save" in the top-right corner.
8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out.
9. After selecting a nickname, tap OK. Your review may not be immediately visible.
On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!
3. Scroll down to find the subhead titled "Ratings & Reviews."
4. Under one of the highlighted reviews, select "Write a Review."
5. Next, select a star rating at the top — you have the option of choosing between one and five stars.
6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.
7. Once you've finished, select "Send" or "Save" in the top-right corner.
8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out.
9. After selecting a nickname, tap OK. Your review may not be immediately visible.
On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!
Recently Antonov and Papoian decided to join forces, and Biosim AI merged into Deep Origin. They say 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.
Exactly how Antonov and Papoian came to their conclusion, and how that integration is playing out, was the main theme of this week's conversation. 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.
Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify!
Here's how to do that on Apple Podcasts:
1. Open the Podcasts app on your iPhone, iPad, or Mac.
2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.
3. Scroll down to find the subhead titled "Ratings & Reviews."
4. Under one of the highlighted reviews, select "Write a Review."
5. Next, select a star rating at the top — you have the option of choosing between one and five stars.
6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.
7. Once you've finished, select "Send" or "Save" in the top-right corner.
8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out.
9. After selecting a nickname, tap OK. Your review may not be immediately visible.
On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!
