Transcribed

Benchling

5.0(5개의 평가)
비즈니스
매월 업데이트

Transcribed explores the human stories behind biotech breakthroughs. Benchling CEO Sajith Wickramasekara sits down with scientists, founders, and R&D leaders to talk candidly about the decisions shaping modern biotech. From career pivots to breakthroughs, setbacks, and lessons in leadership, these are real conversations with the people moving science forward.

5월 8일

Lindsay Edwards on building AI that actually works in biology

Lindsay Edwards went from producing UK top ten singles with Sting and Whitney Houston to pioneering the first data science group at GSK — and he's carried the same creative instinct into machine learning ever since. Now CTO of Relation Therapeutics, he's one of the clearest-eyed voices in the industry on where AI in biology is genuinely working and where it's still mostly noise. Lindsay joined Benchling CEO Sajith Wickramasekara to talk about why "virtual cells" are dangerously overpromised, why legacy data is usually worth less than pharma companies think, and what it will actually take for ML to earn its place in drug discovery. Key Takeaways: ➜ "Virtual cell" has become a wildly overpromised term — what most researchers actually mean is predicting gene expression, which remains largely unsolved and is nowhere close to modeling the full complexity of a cell. ➜ Biology's data bottleneck isn't just a volume problem: because measurements are made in arbitrary relative units rather than absolute values, models routinely learn batch effects instead of meaningful biology. ➜ Rather than spending millions curating legacy data that may be fundamentally unmeasurable, companies should invest that same money in ensuring every new clinical study is collected consistently — and within three years, they'd have an industry-defining dataset. Chapters: [00:51] From chart-topping musician to machine learning pioneer [12:31] Why AI needs a reality check [19:54] The biggest gaps in AI today [22:46] Why biologists need to be more like physicists [26:05] Why too much compute is a problem [32:19] Why legacy data is worth less than you think [34:52] The future of machine learning in biology About Lindsay: Lindsay Edwards is Relation’s CTO and Head of Platform. Previously, Lindsay was VP and Head of AI for Respiratory and Immunology at AstraZeneca. Originally a specialist in systems biology, he joined GlaxoSmithKline in 2014 from the Physiology faculty at King’s College London. He started GSK’s first Data Science group, was Head of Respiratory Data Sciences, Global Head of Respiratory Digital, Data, and Analytics, and then VP and Head of AI/ML for the UK and Europe before becoming VP of AI/ML Engineering. He holds a DPhil in Physiology from Oxford, is a scientific advisor to the Eric and Wendy Schmidt Centre at MIT, and has published more than 40 articles in peer-reviewed journals. 💡 Learn more about Relation Therapeutics: www.relationrx.com Guest Highlights: "My main objection is when someone says, 'we're using AI for drugdiscovery.' That's like saying, 'I'm using chemistry for drug discovery.'" "When somebody says 'virtual cell,' I imagine laypeople think of a computational model that synthetically captures all of the complexity of a cell. We are light years away from that." "Rather than spending $2 million trying to figure out how to drag marginal value out of old data, just spend that money making sure that every single clinical study you run from now is consistent. Within three years, you'd have an industry-defining dataset." 🔗 Links: ➜ Connect with Sajith: linkedin.com/in/sajithw ➜ Connect with Lindsay: linkedin.com/in/lindsay-edwards-7a7268a7

42분
4월 13일

Jacob Berlin on why chemistry is the last frontier for AI drug discovery

Jacob Berlin spent years perfecting a microarray chip the size of a fingernail before he thought about starting a company. Now, as cofounder and CEO of Terray Therapeutics, he's using that hardware to generate chemistry data at a scale the industry has never seen, and arguing that models without proprietary data aren't a moat at all. Jacob joined Benchling CEO Sajith Wickramasekara to talk about why small molecules are AI's hardest and most important frontier, where human chemists still matter, and what the agentic future of drug discovery actually looks like. Key Takeaways: ➜ The AI opportunity in small molecules is trickierthan in biologics because chemical space is infinite, and models without disruptive hardware to generate data at scale will keep hitting the same ceiling. ➜ The durable moat isn't the model—it's the intersection of experimentation and AI, with Terray's dataset now 40x larger than the entire public chemistry dataset and growing by a billion measurements every quarter. ➜ Experienced chemists still play a critical role in seeding novel datasets and catching model suggestions that look wrong but turn out to be breakthroughs. Chapters: [00:50] The elevator pitch (and science) that launched a family business [05:09] Why small molecules still demand reinvention [09:25] Building the stack in sequence: Hardware, then data, and AI [20:43] The true moat in AI drug discovery [29:33] Why the platform isn’t the finish line [33:42] Why we’ll always need humans in the loop [39:18] The future of AI drug discovery is agentic — and actually practical [42:15] Lightning round About Jacob: Jacob is the CEO and cofounder of Terray. Terray was formed in 2018 around a new experimental technology that increases the scale while reducing the cost and cycle time for small molecule evaluation, creating massive amounts of highly precise data to fuel advanced computation and AI in the drug discovery process. Jacob and his team developed this breakthrough technology in his lab at the City of Hope, where he was an associate professor. Under Jacob’s visionary and mission driven leadership, Terray has built a world-class team of computation and drug development leaders, built an internal pipeline focused on new treatments for immunology disorders, established partnerships with global pharma partners, and scaled from that initial invention to a highly automated lab that supports the company’s AI and computational drug discovery and development platform. Jacob’s academic work centered on the intersection of nanotechnology and chemistry, and he has been recognized by the industry as an expert in the field, with numerous awards, and more than fifteen thousand citations of his work. Jacob holds 20 patents, a BA in Chemistry from Harvard and was awarded his PhD in organometallic chemistry from Caltech, where he studied with Nobel Laureate Bob Grubbs. Jacob completed his postdoctoral training at MIT and Rice University, focusing on synthetic chemistry and nanotechnology, before founding his lab at City of Hope. Jacob lives with his family in the Los Angeles area. 💡 Learn more about Terray Therapeutics: https://www.terraytx.com/ Guest Highlights: "What fits on our ultra-dense microarray, which is the size of a fingernail, would have previously fit on about half a tennis court." "I call it 'AI abundance.' You get to the end with 10,000 really interesting molecules, and a chemistry team that can make 50. How do you pick? Solving that optimally is really important." "Whatever you pick to start on is actually your business. If you say, 'We're going to start on this target just to show the platform works, and then we'll pick the real things to work on' — it never happens." 🔗 Links: ➜ Connect with Sajith: linkedin.com/in/sajithw ➜ Connect with Jacob: linkedin.com/in/jacob-berlin-phd-57a82

45분
4월 7일

Kate Haviland on strategic pivots and turning a phase 3 failure into a blockbuster

Kate Haviland knows how to push through clinical setbacks and turn breakthrough science into life-changing therapies. As former CEO of Blueprint Medicines, she led the team that took Ayvakit from a failed Phase 3 to a $500M blockbuster — by cutting the dose by 87% and betting on a patient population nobody had treated before. Kate joined Sajith to talk about holding conviction despite ambiguity, earning trust from teams through uncertainty, and the capital allocation discipline that kept Blueprint focused when everything felt like a priority. Key Takeaways: ▸ Blueprint's Phase 3 failure in GI stromal tumors didn't kill Ayvakit. It redirected it. Cutting the dose by 87% opened a patient population nobody had treated before and built a $500M franchise. ▸ Holding conviction through ambiguity requires knowing the difference between reading data honestly and squinting to see what you want. Kate is direct about how hard that line is to walk. ▸ The Sanofi acquisition came down to more than economics. What distinguished the deal was that Sanofi wanted the team, not just the assets. Chapters: [00:55] Turning a phase 3 failure into a blockbuster drug [12:10] Landing a multi-billion dollar acquisition [18:07] Why collaboration is not a zero-sum game [20:36] Why it’s not always about the deal size [23:01] A CEO’s biggest responsibilities [25:44] Building culture of empowerment and empathy [31:11] Risky bets that ultimately paid off [34:18] Advice for the next generation of scientists About Kate: Kate Haviland is a life sciences executive with more than 20 years of leadership in the biopharmaceutical industry, specializing in scaling high-growth organizations, business development, portfolio strategy, investor relations, and commercial execution. She served as President and CEO of Blueprint Medicines from 2022 until its acquisition in July 2025, previously holding roles as Chief Operating Officer and Chief Business Officer, where she helped drive the company’s growth and build key corporate functions. Earlier in her career, she held leadership positions at Idera Pharmaceuticals, Sarepta Therapeutics, PTC Therapeutics, and Genzyme. Kate holds a B.A. from Wesleyan University and an M.B.A. from Harvard Business School and currently serves on several boards, including Fulcrum Therapeutics, Bicara Therapeutics, the Biotechnology Innovation Organization (BIO), and the Boston Museum of Science. Learn more about Blueprint Medicines: blueprintmedicines.com Guest Highlights: “It's a balance between what the data’s telling you and also understanding the limitations of any given dataset.” “If one party walks away feeling that they've gotten everything on their list, that's not going to be a successful beginning for a collaboration.” “You have to believe that being a leader is about setting this context for great people to do their best work.” Links & Resources: ▸ Connect with Sajith: linkedin.com/in/sajithw ▸ Connect with Kate: linkedin.com/in/kate-haviland-720aab3/

40분
3월 31일

Janice Chen on the CRISPR endgame and why the biggest barrier isn’t scientific

Janice Chen cofounded Mammoth Biosciences straight out of Jennifer Doudna's lab — and she's been rewriting the CRISPR playbook ever since. In this episode, she tells host and Benchling CEO Sajith Wickramasekara about what it really takes to build a platform company, why the biggest barriers to gene editing aren't scientific, and how a cruise ship outbreak in Oakland sparked a race to build a COVID test in days.

40분
2월 19일

Nicole Paulk on radical ideas and the quest for a universal gene therapy

Nicole Paulk talks about turning moonshots into companies, why unpopular ideas are the right ones to pursue, and how biotech has to move faster and cheaper to survive.

1시간 8분
2월 9일

Gleb Kuznetsov on breaking the in vivo bottleneck and building a true platform company

Gleb Kuznetsov talks about about ditching Google for grad school, what it takes to build a true platform company, and where AI-driven drug discovery is headed.

1시간 17분
2025. 10. 22.

Andrew Bellinger on contrarian bets — and pioneering gene editing at Verve

Andrew Bellinger discusses what it takes to build new drug modalities from scratch, the bold bets and tough calls that shaped Verve’s journey, and lessons in building new companies from first-in-class science. * Editor's note: The interview was recorded following the announcement of Verve's acquisition by Lilly, which has since been completed.

49분
2025. 09. 10.

Jake Becraft on going all in on mRNA and proving skeptics wrong

Jake Becraft reflects on making bold bets in mRNA, the journey from lab bench to biotech founder, and the state of science today. (00:00) Introduction to Jake Becraft (00:39) Betting big on mRNA — before it was a proven modality (11:34) Getting your drugs to patients (25:47) The state of modern biomanufacturing (34:30) Medicine is the best investment — and we need policy that reflects that (45:22) Rising to the challenge, as CEO (49:09) Secrets to a healthy cofounder relationship (56:55) Parenting and advice for the next generation (43:13) New funding models in science (48:26) On starting college at 15 — and a lab at 22 (01:04:10) Lightning round

1시간 12분
2025. 08. 01.

Karen Akinsanya on the future of computational drug discovery

Karen Akinsanya unpacks the rise of computational drug discovery, what it takes to prove impact of new technologies, and the importance of setting realistic expectations for AI. (00:00) Introduction to Karen Akinsanya (01:54) Pursuing big technological shifts (06:24) How computation is setting the new standard of speed (10:27) Why you can't develop technology in a vacuum (14:08) Breakthroughs take a lot of patience (and cat videos?) (18:28) The big responsibility with AI (20:41) Breaking down silos and bringing teams together (24:52) The biggest hurdles for AI-driven R&D

28분
2025. 08. 01.

Sara Kenkare-Mitra on saving drug programs and following your curiosity

Sara Kenkare-Mitra talks about resilience, risk, and the kind of leadership it takes to save failing drug programs — and make medicines that matter. (00:00) Introduction to Sara Kenkare-Mitra (00:36) Turning a (nearly) failed program into a bestselling drug (08:33) Learning from industry legends (22:59) Winning for patients, even if others take it across the finish line (27:30) Following your curiosity — and unmet need (37:40) A new era for neurotherapeutics (40:46) Transitioning from large to small companies (46:33) Experience matters in the long game (51:56) Navigating work/life responsibilities (55:36) The biggest pitfall for early career scientists? Impatience. (58:48) Being the only woman in the room (1:00:42) It all comes back to curiosity (1:02:24) Lightning round

1시간 4분
2025. 08. 01.

Patrick Hsu on betting big: CRISPR, AI, and building science in the open

Patrick Hsu reflects on the early days of CRISPR, the power of mentorship, and how AI and open science will reshape the future of research. (00:00) Introduction to Patrick Hsu (01:06) Realizing how big CRISPR would become (06:20) Why Feng Zhang's lab is so high-impact (14:23) How to spot a breakthrough before it happens (18:18) Where the U.S. can't compete with China — and where it can (22:13) How will AI transform the industry — and what's still missing (29:41) Why everyone wins with open science (36:42) Building products that people actually want (43:13) New funding models in science (48:26) On starting college at 15 — and a lab at 22 (55:04) Lightning round

58분

11개의 에피소드

5

최고 5점

5개의 평가

Transcribed explores the human stories behind biotech breakthroughs. Benchling CEO Sajith Wickramasekara sits down with scientists, founders, and R&D leaders to talk candidly about the decisions shaping modern biotech. From career pivots to breakthroughs, setbacks, and lessons in leadership, these are real conversations with the people moving science forward.

제작진

Benchling
방송 연도

2025년 - 2026년
에피소드

11
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© 2025
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