May 24, 2022
Harry's guest this week is Rohit Nambisan, CEO of Lokavant, a company that helps drug developers get a better picture of how their clinical trials are progressing. He explains the need for the company's services with an interesting analogy: these days, Nambisan points out, you can use an app like GrubHub to order a pizza for $20 or $25, and the app will give you a real-time, minute by minute accounting of where the pizza is and when it’s going to arrive at your door. But f you’re a pharmaceutical company running a clinical trial for a new drug, you can spend anywhere from $3 million to $300 million—and still have absolutely no idea when the trial will finish or whether your drug will turn out to be effective. Because there's little infrastructure for analyzing clinical trial data in midstream or spotting trouble before it arrives, some studies continue long after they should have been canceled, and positive data sometimes gets thrown out because of minor procedural flaws; in the end, 20 to 30 percent of the money drug makers spend on clinical trials goes down the drain, Nambisan says. Lokavant's platform allows drug makers and clinical research organizations to harmonize the results coming in from study sites, compare it to data from other trials, and discover important signals in the data before it’s too late. For example, a company might discover that it’s not enrolling patients fast enough to complete a trial on schedule, or that the researchers administering the study aren’t following the exact protocols laid out in advance. Such headaches might sound abstract and remote, but poor data management slows down the whole drug development process, which means fewer beneficial new drugs make it to market ever year; that's the ultimate problem Lokavant is trying to fix.
52 min 83 sec
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.
47 min 37 sec
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.
49 min 21 sec
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.
53 min 02 sec
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.
50 min 59 sec
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.)
55 min 49 sec
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.
57 min 41 sec
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.
47 min 03 sec
Richard Fox: Scaling Genome Editing To Drive The Industrial Bio-Economy
52 min 57 sec
Computers can interpret the text we type, and they’re getting better at understanding the words we speak. But they’re only starting to understanding the emotions we feel—whether that means anger, amusement, boredom, distraction, or anything else. This week Harry talks with Rana El Kaliouby, the co-founder and CEO of a Boston-based company called Affectiva that’s working to close that gap.
33 min 06 sec
Rapid and cheap DNA sequencing technology can tell us a lot about which genes a patient is carrying around, but it can't tell us when and where the instructions in those genes get carried out inside cells. Resolve Biosciences—headed by this week's guest, Jason Gammack—aims to solve that problem by scaling up a form of intracellular imaging it calls molecular cartography.
54 min 59 sec
Pek Lum, co-founder, and CEO of Auransa believes that a lot fewer drugs would fail in Phase 2 clinical trials if they were tested on the patients most predisposed to respond. The problem is finding the sub-populations of likely high-responders in advance and matching them up with promising drug compounds. That’s Auransa's specialty.
48 min 33 sec
This week Harry talks with Matteo Franceschetti, founder and CEO of the Khosla Ventures-backed startup Eight Sleep. The company' smart mattress, called the Pod, is one of the latest (and largest) entries in the burgeoning market for home digital-health devices.
34 min 05 sec
Michael Geer is co-founder and CSO (Chief Strategy Officer) of Humanity Health, a London-based startup that’s building an iPhone app and subscription service designed to help users slow or reverse their rate of aging. Geer’s co-founder Pete Ward has described the app as like “Waze for maximizing healthspan,” that is, their predicted years of healthy functioning. This week Harry grills Geer on the app’s features, the startup’s business model, and the argument for better integration of clinical and digital data into consumers’ everyday health decisions.
49 min 39 sec
This week on MoneyBall Medicine, Harry takes a field trip (literally!) into farming and agriculture. His guests are Al Eisaian co-founder and CEO of crop intelligence IntelinAir, and the company’s director of machine learning, Jennifer Hobbs. Intelinair’s AGMRI platform uses customized computer vision and deep learning algorithms to sift through terabytes of aerial image data, to help farmers identify problems like weeds or pests that can go undetected from the ground. The parallels to the digital transformation in healthcare aren't hard to spot.
55 min 50 sec
What if there were a single company that could connect hospital electronic health record systems to a massive genomic testing and analytics platform? It would be a little like Amazon Web Services (AWS) for healthcare—an enabling platform for anyone who wants to deploy precision medicine at scale. That’s exactly what Joel Dudley says he’s now helping to build at Tempus.
52 min 32 sec
This week Harry catches up with Christine Lemke from Evidation Health, a startup in San Mateo, CA, that helps drug developers and other organizations analyze the effectiveness of smart devices and wearables in new types of therapies.
39 min 17 sec
This week Thomas Chittenden of Genuity Science tells Harry about the company's work to use the power of causal statistical learning, Bayesian belief networks, and other advanced math techniques to understand that cascading gene interactions that account for health and disease—and translate them into insights that can provide drug makers with new targets.
54 min 38 sec
Harry welcomes back Andrew A. Radin, CEO of the drug discovery startup twoXAR, where scientists model pathogenesis computationally to identify potential drug molecules and, ideally shaving years off the drug development process.
57 min 29 sec
In this week's show Harry interviews Rayid Ghani, a computer scientist at Carnegie Mellon University who studies how to use AI and data science to model and influence people's behavior in realms like politics, healthcare, education, and criminal justice.
44 min 48 sec
This week Harry speaks with Oura CEO Harpreet Rai, who’s leading an effort to explore how a wearable sleep-monitoring device—the Oura Ring—can pick up patterns that may help diagnose COVID-19 infections and other problems.
46 min 42 sec