Moneyball Medicine

This week Harry's guest is....Harry! We're flipping the script and giving Harry a chance to wax eloquent about AI in healthcare and drug research, the growing role of personal health monitoring devices, the unique features of the Boston life science ecosystem, the meaning of the recent downturn in biotech investment, the most common mistakes made by new entrepreneurs, and much more. This week's guest interviewer is Wade Roush, who hosts the tech-and-culture podcast Soonish and has been the behind-the-scenes producer of The Harry Glorikian Show ever since Harry started the show in 2018.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch: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

Harry's guest this week is Dr. Isaac Kohane, chair of the Department of Biomedical Informatics at Harvard Medical School and co-author of the new book The AI Revolution in Medicine: GPT-4 and Beyond. Large language models such as GPT-4 are obviously starting to change industries like search, advertising, and customer service—but Dr. Kohane says they're also quickly becoming indispensable reference tools and office helpmates for doctors. It's easy to see why, since GPT-4 and its ilk can offer high-quality medical insights, and can also quickly auto-generate text such as prior authorization, lowering doctors' daily paperwork burden. But it's all a little scary, since there are no real guidelines yet for how large language models should be deployed in medical settings, how to guard against the new kinds of errors that AI can introduce, or how to use the technology without compromising patient privacy. How to manage those challenges, and how to use the latest generation of AI tools to make healthcare delivery mor

In the same way that written English is built around an alphabet of just 26 letters, all life on Earth is built around a standard set of just 20 amino acids, which are the building blocks of all proteins. And just as we've invented special characters like emoji to go beyond our standard letters, it turns out that biologists can expand their repertoire of powers using non-standard amino acids—those that either occur rarely in nature, or that can only be made in the lab. GRO Biosciences, a spinout from the laboratory of the renowned synthetic biology pioneer George Church at Harvard Medical School, is one of the companies working to explore the exciting applications of non-standard amino acids (NSAAs), and Harry's guest this weeks is GRO's co-founder and CEO, Dan Mandell. He says NSAAs could help overcome some of the limitations that keep today’s gene and protein therapies from being used more widely, while also expanding the kinds of jobs that protein-based therapies can do.For a full transcript of this episod

Owning a dog can be a joy, but one sad downside is that dogs are highly prone to cancer—six million of them are diagnosed with the disease in the U.S. each year. Harry's guest this week, Christina Lopes, is co-founder and CEO of a company called One Health that's working to improve cancer outcomes for our canine friends. The company offers a precision cancer diagnosis and treatment service called FidoCure that takes what we’ve learned about genomic testing of tumors in humans and uses it in veterinary clinics. Vets can submit a dog’s tumor sample for DNA sequencing, and FidoCure's report will show whether the animal has specific mutations that could help determine which cancer drug will be most effective. Harry and Christina talk about how that process works, why dogs are more vulnerable to cancer in the first place, where she got the idea for the company, and how One Health's work could benefit dogs and humans alike.For a full transcript of this episode, please visit our episode page at http://www.glorikian.

Unlike cancer, brain diseases like epilepsy, Alzheimer’s disease, or depression don't tend to have  easily measured biomarkers that could help doctors tailor treatments, or that could help researchers develop more effective drugs. So in neurology and psychiatry, the precision medicine revolution hasn't really arrived yet. But Beacon Biosignals, where Harry's guest  Jacob Donoghue is the co-founder and CEO, is trying to change all that. Beacon is focused on making electroencephalography into a more reliable and useful data source for diagnosing and treating neurological disease. EEG is a non-invasive way to measure electrical activity in the brain, and it’s been a common medical tool for almost 100 years. But takes a lot of training for a human doctor to interpret an EEG correctly. It’s slow, it’s expensive, and it’s a bit of a dark art—all of which makes it the perfect candidate for machine learning analysis. Donoghue says the goal at Beacon Biosignals is to use computation to get more value out of existing E

Large language models are already changing the business of search. But now they’re about to change the practice of medicine. Harry's guests, Vivek Natarajan and Shek Azizi, are both researchers on the Health AI team at Google, where they're pushing the boundaries of what large language models can achieve in specialized domains like  health. This spring their team announced it would start rolling out a new large language model called Med-PaLM 2 that’s designed to answer medical questions with high accuracy. (The model got an 85 percent score on the U.S. Medical License Exam, the test all doctors have to take before they’re allowed to practice.)  It's been clear for a while that consulting with an AI would eventually become an indispensable part of every medical journey—whether you’re a patient searching for information about your symptoms, or a doctor looking for an expert second opinion. And now that such a future is almost here, the work Vivek and Shek are doing at Google feels both exciting and a little bit

Harry's guests this week are Sri Kosaraju, the CEO of Inscripta, and Richard Fox, a former Inscripta scientist who just rejoined the company as its SVP of Synthetic Biology. In reabsorbing Infinome—the Inscripta spinout Fox described to Harry in a spring 2021 episode of the show—Inscripta is placing a big bet on biomanufacturing, the creation and fermentation of genetically customized microbes that can pump out medical, agricultural, and nutraceutical products, and more. Inscripta had previously focused on a benchtop "bio-foundry" machine called Onyx that that makes programmed edits to bacterial or yeast cells at thousands of different points in their genome in parallel. Now it's pivoting away from selling the machine and instead focusing on becoming a power user of its own technology. Its ultimate plan is market multiple biomanufactured products, starting with a synthetic form of bakuchiol, an alternative to the anti-aging compound retinol.For a full transcript of this episode, please visit our episode page

Harry's guest this week, Jen Nwankwo, is the founder and CEO of a drug discovery company in Boston called 1910 Genetics. Her PhD is in pharmacology, which shows through in her practical focus on fixing the drug discovery process to get more and better therapies into the hands of doctors. To hear Jen tell it, 1910 Genetics is focused on finding the most promising new drug candidates for stubborn health problems—and it takes a refreshingly agnostic approach to everything else. The company doesn’t hunt for just small-molecule drugs or just protein therapies. It explores both. It doesn’t utilize just one form of neural networking or machine learning. It uses whatever model produces the best science for a given problem. It doesn’t hunt for drugs using just wet lab data or just computational simulations. It does both. It isn’t just assembling its own pipeline of drugs or just partnering with larger pharma companies. It’s working on both. Jen wasn’t even dead set on being an entrepreneur—she had to be talked into ap

Tears are a signal of more than just our emotions. The liquid in tears comes from blood plasma, and contains a lot of the same proteins and other biomolecules that circulate in the bloodstream. But what this liquid doesn’t have are a lot of the extra components like antibodies that would get in the way if you were looking for specific biomarkers—such as the low-molecular-weight proteins released as a byproduct of the inflammation around tumors. Harry's guests Anna Daily and Omid Moghadam are from a startup called Namida Lab that’s the first company to market a lab test using tears to predict cancer risk. Specifically, Namida’s test assesses the short-term risk that a patient might have breast cancer, as a way of helping them decide how soon to go in for a mammogram. "Namida" is actually the Japanese word for tears, and beyond breast cancer, the company aims to build a whole business around risk assessment and diagnostics, using just the biomarkers in tears. Eventually it could be possible to collect a sample

It may feel like generative AI technology suddenly burst onto the scene over the last year or two, with the appearance of text-to-image models like Dall-E and Stable Diffusion, or chatbots like ChatGPT that can churn out astonishingly convincing text thanks to the power of large language models. But in fact, the real work on generative AI has been happening in the background, in small increments, for many years. One demonstration of that comes from Insilico Medicine, where Harry's guest this week, Alex Zhavoronkov, is the co-CEO. Since at least 2016, Zhavoronkov has been publishing papers about the power of a class of AI algorithms called generative adversarial networks or GANs to help with drug discovery. One of the main selling points for GANs in pharma research is that they can generate lots of possible designs for molecules that could carry out specified functions in the body, such as binding to a defective protein to stop it from working. Drug hunters still have to sort through all the possible molecules

There have been a lot of stories in the news over the last few months about AI chatbots like ChatGPT that can respond to your questions with convincing and well-written answers. These so-called large language models can tell you how to build a treehouse, how to bake a cake, or how to sleep better. But notice that word large. Behind the scenes, these models have learned which word tend to cluster together by sifting through hundreds of billions of pieces of data—basically the entire Internet, in the cast of ChatGPT, including all of Wikipedia and thousands of published books. Now imagine that another chatbot came along that could learn how to generate convincing text response by studying only, say, 18 sentences. Something like that is what this week’s guest Raphael Townshend, the founder and CEO of Atomic AI, has accomplished when it comes to predicting the structure of RNA molecules.RNA has been in the news a lot lately too. That's in part because some of the vaccines that helped us beat back the coronavirus

The medical news publication STAT calls Will Flanary “the Internet’s funniest doctor.” The guests we bring on the show usually talk about how technology is changing healthcare, but Will and his wife Kristin are changing healthcare in a very different way—through comedy. A former standup comic who trained as an ophthalmologist and runs a successful ophthalmology practice in Oregon City, Oregon, Will is better known by his alter ego “Dr. Glaucomflecken.” His short videos have millions of views on YouTube and TikTok, and feature a cast of quirky characters, all played by Will himself, who lightly satirize medical culture and the idiosyncracies of the US healthcare system. And now Will and Kristin have a hybrid comedy and interview podcast called “Knock, Knock, Hi” where they bring on guests who share their own weird and hilarious medical stories.If you wanted to find a comparably successful crossover between medicine and comedy, you’d probably have to go all the way back to TV shows like M*A*S*H and Scrubs. But

There's a quiet revolution happening in the field of genetic screening of newborns. Within the last couple of years it’s become possible to sequence the entire genome of a newborn baby, all six billion base pairs of DNA, and diagnose potential genetic disorders in about 7 hours. That’s already happening in a handful of hospitals, with a focus on babies who are showing symptoms of rare genetic disorders. But within five years, says Harry's guest, Dr. Stephen Kingsmore, it should be possible to extend this rapid whole-genome sequencing to every baby in every hospital, whether they’re showing symptoms or not.Kingsmore earned his medical degrees in Northern Ireland, trained in internal medicine and rheumatology at Duke, and studied genomic medicine at Children’s Mercy Hospital in Kansas City. And he’s now the president and CEO of the Institute for Genomic Medicine at Rady Children’s Hospital in San Diego. There, he’s been leading an aggressive push to prove that rapid whole-genome sequencing and diagnosis can not

Last October, medical imaging company Arterys announced that it had been acquired by healthcare AI giant Tempus. That caught our attention here at The Harry Glorikian Show, because back in the fall of 2018—exactly 100 episodes ago, as it turns out—we welcomed Arterys co-founder and CEO Fabien Beckers as our guest. At the time, Arterys had recently won FDA clearance for a cloud-based software platform that used deep learning to help radiologists automatically locate the contours of the ventricles of the heart. The company would go on to apply similar technology to MRI and CT images of all sorts of tissue, including the breast, chest, brain, and lungs. What made the platform doubly unique was that doctors could access it over the web, so hospitals didn’t have to maintain expensive on-premise software or hardware. Today it would be hard to find a health tech company that isn’t using AI and cloud computing in some way, but it's easy to forget how recent those developments are; Arterys was the very first company t

You can wear an Oura ring or a WHOOP armband to tell you how your body is adapting to exercise. A continuous glucose monitor can send your phone information about your blood sugar levels are changing. And during the pandemic, a lot of people bought home pulse oximeters to monitor their blood oxygenation levels. But there’s one part of the body where home health sensors haven’t reached yet, and that’s our brains. They're protected inside our thick skulls, which means it’s pretty hard to measure what’s going on in there. Until recently, the only real instruments available to doctors and neuroscientists were big hospital-based machines like X-Rays, CT-scans, EEGs, and MRIs.But that might finally be changing. Harry's guest this week is Ryan Field, chief technology officer at Kernel. The vision of the L.A.-based company is to develop a consumer device that would work like a pulse oximeter, but for your brain. The first version, Kernel Flow, is shaped like a bicycle helmet, and it contains more than 50 low-power la

Out of all the dozens of types of cancer that occur in humans, we habitually screen for only five: breast, cervical, colon, prostate, and lung. But what if there were a single test that could detect 50 types of cancer, based on a simple blood draw? That's exactly what's possible today, thanks to the Galleri test, introduced by Illumina spinoff Grail in 2021. The $949 test, which won breakthrough designation from the FDA in 2019, uses machine learning to assess the patterns of methyl groups—molecules that attach to chromosomes and control gene activity—in free-floating DNA shed by tumors. This week Harry interviews Grail's president, Dr. Josh Ofman. He says that the company is working to bring down the price of the test, and that if multi-cancer early detection tests like Galleri are eventually approved for population-level screening, it could help avert 100,000 deaths per year.For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast Please rate and review The Ha

These days, there's an explosion of digital imaging technology for almost every part of the body. There are the familiar types of imaging everyone knows, like CT scans, MRIs, ultrasound, and of course, X-rays. But now doctors and medical researchers are also exploring newer types of digital imaging technology, such as Optical Coherence Tomography, or OCT.OCT uses near-infrared light that penetrates just a couple of millimeters into a tissue such as an artery wall or the retina of the eye. By collecting the light that scatters back, OCT can produce an incredibly high-resolution cross section or even a 3D reconstruction of the tissue. Ophthalmology is one of the fields putting OCT to use most aggressively, partly because it’s perfect for showing cross-sections of the retina, the iris, the cornea, or the lens on the scale of micrometers.But as you can imagine, every time an ophthalmologist or optometrist uses an OCT scanner, the procedure generates a huge amount of digital data. Harry's guest, Carlos Ciller, sta

There are many causes for diabetes—chronicallly high blood sugar—but there’s also a growing list of ways to prevent it, or manage it once it starts. Wearable technologies like continuous glucose monitors or CGMs are high on that list. These devices have tiny needles that penetrate the skin and measure glucose levels in the interstitial fluid between cells. They can send that data to a smartphone, where apps made by a variety of companies can record it and analyze it.January.ai is one such company, and co-founder and CEO Noosheen Hashemi joined Harry on the show back in July of 2021. It turns out that the same foods can have different effects on the blood glucose levels of different individuals, and January’s app starts off using live CGM data to study those patterns using machine learning algorithms. Then it can start making predictions about a user's future blood glucose levels, even after they stop wearing a CGM. That can help them make smarter decisions about what, when, or how much to eat, or how much the

About half a million babies are born every year through IVF. That number would probably be a lot higher if the procedure were cheaper and more accessible—but making that happen would  mean transforming IVF from an artisanal craft into something more like a modern automated factory, with AI helping doctors and technicians make faster and better decisions at every step. And that’s exactly what Harry's guest Mylene Yao, the co-founder of Univfy, is doing. Univfy helps patients with two aspects of the IVF process. The first is using machine learning to provide patients with a more accurate assessment of  the odds of success, before they decide whether to invest in one or more IVF cycles, which can cost up to $30,000 per cycle. The second is financing. Univfy works with a bank called Lightstream to provide up to $100,000 in financing for up to three rounds of IVF, with a large refund as part of the deal if the treatments don’t result in a baby. Harry talks with Dr. Yao about the prospects for far broader access to

For the 100th episode of The Harry Glorikian Show, Harry welcomes Phil Febbo, chief medical officer at Illumina. The San Diego-based company is the leading maker of the high-speed gene sequencing machines that are at the core of the precision medicine revolution. The company has an 80 percent market share, which means that if you or your loved one has had any sequencing done for any reason, chances are your samples were sequenced on an Illumina machine. Gene sequencing is already a key part of both diagnostics and treatment decisions for many disease, but its use is only going to expand as the technology gets faster and cheaper.This fall, Illumina announced that it’s coming out a new gene sequencing machine called the NovaSeq X that can sequence a genome more than twice as fast as Illumina’s previous top-of-the-line machine, and at a lower cost. That’s bound to speed up progress all across the field of genetic medicine, drug discovery, and life science research. And that’s where Harry starts his interview wit