Moneyball Medicine

As we say here on The Harry Glorikian Show, technology is changing everything about healthcare works—and the reason we keep talking about it month after month is that the changes are coming much faster than they ever did in the past. Each leap in innovation enables an even bigger leap just one step down the road. Another way of saying this is that technological change today feels exponential. And there’s nobody who can explain exponential change better than today’s guest, Azeem Azhar.Azeem produces a widely followed newsletter about technology called Exponential View. And last year he published a book called The Exponential Age: How Accelerating Technology is Transforming Business, Politics, and Society. He has spent his whole career as an entrepreneur, investor, and writer trying to help people understand what’s driving the acceleration of technology — and how we can get better at adapting to it. Azeem argues that most of our social, business, and political institutions evolved for a period of much slower ch

Genialis, led by CEO Rafael Rosengarten, is one of the companies working toward a future where there are no more one-size-fits-all drugs—where, instead, every patient gets matched with the best drug for them based on their disease subtype, as measured by gene-sequence and gene-expression data. Analyzing that data—what Rosengarten calls "computational precision medicine"—is already helping drug developers identify the patients who are most likely to respond to experimental medicines. Not long  from now, the same technology could help doctors diagnose patients in the clinic, and/or feed back into drug discovery by providing more biological targets for biopharma companies to hit."Our commitment to biomarker-driven drug development is very principled," Rosengarten tells Harry. "There are some amazing drugs out there that, when they work, work miracles. But they don't work that often. Some work in maybe 15 percent of the patients or 20 percent. If you could tell which of those patients are going to respond, then a

When the coronavirus pandemic swept across the world in early 2020, Spain was one of the countries hardest hit. At the time, Nuria Oliver was a telecommunications engineer working and living in Valencia, one of Spain's 17 autonomous regions. She’d spent years working for companies like Microsoft, Telefonica, and Vodafone, using AI to analyze data from mobile networks to explore big questions about healthcare, economics, crime, and other issues—so she realized right away that mobile data could be an important tool for government leaders and public health officials trying to get a handle on the spread of COVID-19.With the backing of Valencia's president, Oliver put together a team of scientists to analyze network data to understand among other things, how much people in Spain were moving around. That helped them predict infection rates, and to see whether lockdowns were really helping to contain the virus's spread. The team's predictions were so accurate, in fact, that when they entered an X Prize Foundation co

We've learned from previous guests that machine learning and other forms of AI are helping to identify better disease treatments, get drugs to market faster, and spot health problems before they get out of hand. But what if they could also help patients find the best doctors for them, and help doctors frame their advice in a way that patients can relate to? This week, Harry's guest, Briana Brownell, talks about the computational tools her company Pure Strategy is building to find patterns in people’s personal preferences that can lower cultural barriers, enable better matchmaking between patients and doctors, predict which patients are most likely or least likely to go along with a treatment plan, or help doctors communicate their recommendations better. "Not everybody makes decisions in the same way," Brownell says. "Not everybody values the same things. But by understanding some of those psychological and value-based drivers, we can get better health care outcomes."Please rate and review The Harry Glorikian

Your medical records don't make pleasant bedtime reading. And not only are they inscrutable—they're often mutually (and deliberately) incompatible, meaning different hospitals and doctor's offices can't share them across institutional boundaries. Harry's guest this week, Ardy Arianpour, is trying to fix all that. He’s the co-founder and CEO of Seqster, a San Diego company that’s spent the last five years working on ways to pull patient data from all the places where it lives, smooth out all the formatting differences, and create a unified picture that patients themselves can understand and use.The way Ardy explains it, Seqster “smashes the data siloes.” Meaning, the company can combine EMR data, gene sequence data, wearable device data, pharmacy data, and insurance claims data all in one place. The big goal guiding Seqster, he says, is to put the patient back at the center of healthcare.Please rate and review The Harry Glorikian Show on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch

Chances are you or someone you love has had a biopsy to check for cancer. Doctors got a tissue sample and they sent it into a pathology lab, and at some point you got a result back. If you were lucky, it was negative and there was no cancer. But have you ever wondered exactly what happens in between those steps? Until recently, it’s been a meticulous but imperfect manual process where a pathologist would put a thin slice of tissue under a high-powered microscope and examine the cells by eye, looking for patterns that indicate malignancy. But now the process is going digital—and growing more accurate.Harry's guest this week is Leo Grady, CEO of, Paige AI, which makes an AI-driven test called Paige Prostate. Grady says that in a clinical study, pathologists who had help from the Paige system accurately diagnosed prostate cancer almost 97 percent of the time, up from 90 percent without the tool. That translates into a 70 percent reduction in false negatives—nice odds if your own health is on the line. This week

Many of us wear wireless, battery-powered medical sensors on our wrists in the form of our smartwatches or fitness trackers. But someday soon, similar sensors may be woven into our very clothing. Harry's guest this week, Nanowear CEO Venk Varadan, explains that his company's microscopic nanosensors, when embedded in fabric and worn against the skin, can pick up electrical changes that reveal heart rate, heart rhythms, respiration rate, and physical activity and relay the information to doctors in real time. And that kind of technology could move us one step closer to a world where we're far more intimately connected to the medical system and doctors can catch health problems before they turn into disasters.Nanowear's leading product is a sash called SimpleSense that fits over the shoulder and around the torso. Last month the company won FDA approval for the software package that goes with the SimpleSense sash and turns it into a diagnostic and predictive device. It's currently being tested in a network of cli

Today we bring you the second half of Harry's conversation with Dave deBronkart, better known as E-Patient Dave for all the work he’s done to help empower patients to be more involved in their own healthcare. If you missed Part 1 of our interview with Dave, we recommend that you check that out before listening to this one. In that part, we talked about how Dave’s own brush with cancer in 2007 turned him from a regular patient into a kind of super-patient, doing the kind of research to find the medication that ultimately saved his life. And we heard from Dave how the healthcare system in the late 2000s was completely unprepared to help consumers like him who want to access and understand their own data.Today in Part 2, we’ll talk about how all of that is gradually changing, and why new technologies and standards have the potential to open up a new era of participatory medicine – if, that is, patients are willing to do a little more work to understand their health data, if innovators can get better access to th

The podcast is back with a new name and a new, expanded focus! Harry will soon be publishing his new book The Future You: How Artificial Intelligence Can Help You Get Healthier, Stress Less, and Live Longer. Like his previous book MoneyBall Medicine, it's all about AI and the other big technologies that are transforming healthcare. But this time Harry takes the consumer's point of view, sharing tips, techniques, and insights we can all use to become smarter, more proactive participants in our own health. The show's first guest under this expanded mission is Dave deBronkart, better known as "E-Patient Dave" for his relentless efforts to persuade medical providers to cede control over health data and make patients into more equal partners in their own care. Dave explains how he got his nickname, why it's so important for patients to be more engaged in the healthcare system, and what kinds of technology changes at hospitals and physician practices can facilitate that engagement. Today we're bringing you the firs

Harry's guest this week is Matthew Might, director of the Hugh Kaul Precision Medicine Institute at the University of Alabama at Birmingham. Might trained as a computer scientist, but a personal odyssey inspired him to make the switch into precision medicine. Now he uses computational tools such as knowledge graphs and natural language processing to find existing drug compounds that might help cure people with rare genetic disorders.Might's odyssey began with the birth of his first child, Bertrand, in 2007. Bertrand seemed healthy at first, but soon developed a cluster of symptoms including developmental delay, lack of motor control, inability to produce tears, and epilepsy-like seizures.  For more than four years, doctors were unable to diagnose Bertrand's condition. But eventually a technique called whole exome sequencing revealed that he had no functioning gene for NGLY1, an enzyme that normally removes sugars from misfolded proteins. Bertrand, it turned out, was the first person in the world to be diagnos

This week Harry is joined by Kevin Davies, author of the 2020 book Editing Humanity: The CRISPR Revolution and the New Era of Genome Editing. CRISPR—an acronym for Clustered Regularly Interspaced Short Palindromic Repeats—consists of DNA sequences that evolved to help bacteria recognize and defend against viral invaders, as a kind of primitive immune system. Thanks to its ability to precisely detect and cut other DNA sequences, CRISPR has spread to labs across the world in the nine years since Jennifer Doudna and Emmanuel Charpentier published a groundbreaking 2012 Science paper describing how the process works. The Nobel Prize committee recognized the two scientists for the achievement in 2020, one day after Davies' book came out. The book explains how CRISPR was discovered, how it was turned into an easily programmable tool for cutting and pasting stretches of DNA, how most of the early pioneers in the field have now formed competing biotech companies, and how the technology is being used to help patients t

Harry traveled to the San Francisco Bay Area this summer, and while there he interviewed the co-founders of three local data-driven diagnostics and drug discovery startups, all of whom participated in the same graduate program: the Biomedical Informatics Program at Stanford's School of Medicine.  Joining Harry were Aria Pharmaceuticals co-founder and CEO Andrew Radin, BigHat Biosciences co-founder and chief scientific officer Peyton Greenside, and Inflammatix co-founder and CEO Tim Sweeney. The conversation covered how each company's work to advance healthcare and therapeutics rests on data and  computation, and how the ideas, skills, connections each entrepreneur picked up at Stanford have played into their startups and their careers.Radin's company, formerly known as twoXar, models pathogenesis computationally to identify potential drug molecules, shaving years off the drug development process. Radin developed Aria’s core technology, a collection of proprietary algorithms for discovering novel small molecul

Harry's guest this week is Jeff Elton, CEO of a Boston-based startup called Concert AI that's working to bring more "real-world data" and "real-world evidence" into the process of drug development. What's real-world data? It's everything about patients' health that's not included in the narrow outcomes measured by randomized, controlled clinical trials. By collecting, organizing, and analyzing it, Elton argues, pharmaceutical makers can it design better clinical trials, get drugs approved faster, and—after approval—learn who's really benefiting from a new medicine, and how. Concert AI, which has offices in Boston, Philadelphia, Memphis, New York, and Bangalore, specializes in providing “research-grade real-world data” and AI-based analytical services to companies developing cancer drugs. Before joining Concert AI, Elton was managing director of strategy and global lead of predictive health intelligence at Accenture, and before that he was a senior vice president of strategy and global chief operating officer

In a companion interview to his June 7 talk with Stanford's Michael Snyder, Harry speaks this week with Noosheen Hashemi, who—with Snyder—co-founded the personalized health startup January.ai in 2017. The company focuses on helping users understand how their bodies respond to different foods and activities, so they can make diet and exercise choices that help them avoid unhealthy spikes in blood glucose levels.January's smartphone app collects blood glucose levels from disposable devices called continuous glucose monitors (CGMs), as well as heart rate data from patients’ Fitbits or Apple Watches. The app also makes it easier for users to log the food they eat, and see what impact each food has on their glucose levels. Once the app has enough data, January’s machine learning algorithms can start predicting the effects of different foods and activities on blood glucose. It can then recommend meals and exercise that’ll help users keep their blood glucose in a healthy target range. The goal isn’t to prevent gluco

This week Harry sits down with Vangelis Vergetis, the co-founder and co-executive director of Intelligencia, a startup that uses big data and machine learning to help pharmaceutical companies make better decisions throughout the drug development process. Vergetis argues that if you put a group of pharma executives in a conference room, then add an extra chair for a machine-learning system, the whole group ends up smarter—and able to make more accurate predictions about which drug candidates will succeed and which will fail.Bringing better analytics into the pharma industry has been an uphill battle, Vergetis says. One survey by McKinsey, his former employer, showed that financial services companies were the most likely to adopt AI and machine learning tools; the least likely were the building and construction trades. But just one rung up from the bottom was healthcare and pharmaceuticals. "The impact that AI could have on health care is "enormous," Vergetis says. "It's in the trillions. But in terms of AI ado

From her TED talks and her appearances on PBS, geneticist Wendy Chung is known to millions of people as an expert on autism. But thanks to funding from the Simons Foundation, she’s also known to tens of thousands of people with autism and their families as the leader of history’s largest study of the genetics of autism spectrum disorder (ASD). It’s called SPARK, for Simons Foundation Powering Autism Research for Knowledge, and it's a big-data exercise of unprecedented proportions.SPARK is partnering with more than 30 medical schools and research centers to recruit 50,000 families with members affected the ASD. Participants have their DNA sequenced, enabling SPARK to build a list of genetic differences linked to autism as a starting point for research on the causes and mechanisms behind the condition. At the moment the list includes 157 single genes and 28 copy number variants. But changes in these known ASD genes show up in only about 10 percent of families studied—suggesting that the existing list is just th

Having helped to bring big data to genomics through the lab techniques he invented, such as RNA-Seq, the Stanford molecular biologist Michael Snyder is focused today on how to use data from devices to increase the human healthspan. Some cars have as many as 400 sensors, Snyder notes. "And you can't imagine driving your car around without a dashboard...Yet here we are as people, which are more important than cars, and we're all running around without any sensors on us, except for internal ones." To Snyder, smart watches and other wearable devices should become those sensors, feeding information to our smartphones, which can then be "the health dashboard for humans and just let us know how our health is doing."  (You can sign up to participate in the Snyder lab's study of wearables and COVID-19 at https://innovations.stanford.edu/wearables.)Snyder has been chair of Stanford’s Department of Genetics since 2009 and is director of the Stanford Center for Genomics and Personalized Medicine. He has a BA in chemistry

Angeli Moeller is a molecular biologist, a neuroscientist, a systems biologist, and a data scientist all rolled into one—which makes her a perfect example of the kind of multidisciplinary executive needed for this new digital health ecosystem defined by big data, AI, and machine learning. She's a founding member of the Alliance for Artificial Intelligence in Healthcare, does extensive work for the nonprofit rare disease advocacy group Rare-X, and has spent almost five years managing global data assets and IT partnerships at Bayer. At the beginning of 2021 she became the head of international pharma informatics for Roche, the world’s largest drug company. Harry caught up with her on Zoom in February, and the conversation started with the role of informatics at Roche, but quickly expanded to cover all the areas where deep learning and other forms of AI and data science are transforming drug discovery and healthcare, and what life sciences entrepreneurs need to do to get on board.Please rate and review MoneyBall

The discoveries medical researchers and drug developers can make are constrained by the kinds of questions they can ask of their data. Unfortunately, when it comes to clinical trial data, or gene expression data, or population health data, it feels like you need a PhD in computer science just to know which questions are "askable" and how to frame them. This week, Harry talks with the founders of a startup working to solve that problem.Tag.bio aims to make it possible for any worker in the life sciences sector—even if they don't have a PhD in computer science or data science—to interrogate their data quickly and automatically. The idea is to help them uncover trends or connections in their data that would otherwise require months of work and help from a data scientist or a data engineer.The company was founded in 2014 as a spinoff from the University of California, San Francisco Cancer Center. That’s where co-founder Jesse Paquette first invented a system that let oncology researchers ask guided questions of t

This week Harry speaks with Richard Fox, a computational biologist whose work at two life sciences startups, Inscripta and Infinome, is helping to automate and vastly scale up the process of engineering an organism's genome to evoke new functions or uncover important genetic pathways.With the discovery of the genetic scissors known as CRISPR-Cas9 in 2012, biologists gained the ability to make precise cuts in the genes of almost any organism. For genetic engineers, what used to be a slow, labor-intensive, manual process was suddenly easy. It was like jumping from a medieval monastery where all the monks write their manuscripts longhand into a world where everyone has a word processor on their desktop. But the first generation of CRISPR technology was still pretty limited. To continue with the word processing metaphor: you could use CRISPR to change individual letters in a text, but you couldn’t use it to modify entire words, sentences, or paragraphs.At Inscripta, Fox helped to turn CRISPR into a fully featured