Accelerating drug discovery for aging and its diseases (Ben Kamens - Spring Discovery)
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Ben Kamens is the founder and CEO of Spring Discovery, a company devoted to accelerating therapies for aging and its diseases. Prior to that, Ben was the first engineer for Khan Academy, which provides free online education to millions of users around the world. Today Ben joins host Chris Patil to discuss Spring Discovery’s mission to increase healthy lifespan and dramatically reduce disease, his experience with Khan Academy and how it connected to his work in biotechnology, and overcoming challenges in the field of aging. Ben tells Chris about his pragmatic approach to building a company, how Spring Discovery plans to accelerate drug discovery and clinical development, and their collegial relationship with BioAge and other companies in the longevity biotech sector. Ben chats about Spring Discovery’s recent Series B funding, then offers a sneak peek into their therapeutic pipeline, and details his experience running a nonprofit clinical trial for a generic drug to fight against COVID, including what this taught him about testing drugs for age-related indications. Finally, Ben shares his favorite aspect of longevity science that his company is not currently working on, and where he sees the field of aging moving toward over the next five to ten years. To learn more about Ben and Spring Discovery’s work to accelerate drug discovery with machine learning, visit https://www.springdiscovery.com/ (springdiscovery.com). Episode Highlights: Ben Kamens is the founder and CEO of https://www.springdiscovery.com/ (Spring Discovery); he was also the first engineer for Khan Academy Introduction to Spring Discovery and how recent Series B funding will help the company advance its work to increase healthy lifespan and dramatically reduce disease His initial skepticism and passion for fighting disease Overcoming obstacles in the field of aging Building value and resources as a company over time Accelerating drug discovery and clinical development Machine learning approach Spring Discovery’s therapeutic pipeline Ben’s involvement running a nonprofit clinical trial for a generic drug against COVID, and what this taught him about testing drugs for age-related indications You can read Ben’s article “COVID-19 is the latest disease to point at our need to treat immune aging” https://medium.com/spring-discovery/covid-19-is-the-latest-disease-to-point-at-our-need-to-treat-immune-aging-a35e94e01ba8 (here) Favorite aspect of longevity science that his company is not currently working on Quotes: “I couldn't think of a more important mission to try to enable than battling diseases of aging. And our mission is to give the best technology possible to these people who are doing what we think is the most important work possible.” “I came to this field as an outsider and somebody who's really a team builder, and interested in deploying the intersection of scientists and technology to try to fight disease.” “I am an extremely pragmatic person, especially when it comes to company building and entrepreneurialism.” “When you mention aging, you're immediately talking about this extremely broad array of biological phenomena, some of which are going to be relevant clinically, some of which are not.” “This presented a real opportunity to build the best company in the world at measuring the many changes that occur in us as we age.” “We've essentially taken an engineering throughput mindset to disentangling the many dimensions of age-related changes that accrue in our cells and tissues over time, and built a company around getting really, really good at that, and then using that to much more quickly search for therapies.” “You can think of it as a big engine that takes in a whole bunch of primary human samples, spits out this very multidimensional, complete view of cellular function, but does it in a big single screen that's combining tons of phenotypic imaging data with proteomics data, and then
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