Free Daily Podcast Summary
Tech and Drugs - Podcast: Daily Summaries Delivered
by Thibault Geoui
Welcome to Tech and Drugs, the podcast exploring how data and AI are revolutionizing Pharma and Biotech. Each episode features candid conversations with industry experts tackling real-world challenges, sharing success stories, and lessons learned. Explore how digital transformation accelerates breakthroughs and bridges the gap between tech and science. What You’ll Discover: • How AI is driving drug discovery and development. • Insights from the forefront of TechBio innovation. • Practical lessons for navigating digital transformation.
Latest Episodes
The most recent episodes — sign up to get AI-powered summaries of each one.
- 2 weeks ago1h 0m
Servier's Walid Kamoun on AI and the Future of Oncology R&D
In this Tech & Drugs episode, I sit down with Walid Kamoun, VP and Global Head of Oncology R&D at Servier, to explore how AI is changing oncology drug discovery and development.We discuss where AI is already useful today, what remains difficult, and how pharma leaders can think about AI beyond hype, pilots, and generic “transformation” language.Walid shares a grounded view from the front lines of oncology R&D: how AI can support asset leaders, clinical scientists, target discovery, molecule design, trial planning, regulatory work, and patient matching. We also discuss why AI adoption is not only a technology question, but an operating model, culture, data, and leadership question.A central theme of the conversation is AI as a booster for expert work. Rather than replacing scientific and clinical judgment, AI may help teams create stronger “draft zero” development plans, accelerate decision-making, and focus human expertise where it matters most.Key themes discussed:- How AI is changing oncology drug discovery and development- Why AI should support, not replace, expert judgment- The role of AI in asset leadership and integrated development plans- “Draft zero” thinking for oncology programs- AI in synthetic chemistry and synthetic biology- AI use cases in clinical development, protocol writing, and regulatory work- Matching the right patient to the right drug in precision oncology- Why AI-ready data and infrastructure matter- How biotechs may benefit from AI as an accelerator- How pharma can evaluate AI partners beyond marketing claims- The role of big tech in pharma and biotech R&D- Why oncology R&D still needs strong human, scientific, and clinical leadershipWhy this matters:AI is already influencing how pharma and biotech teams discover, develop, and evaluate new medicines. But the real opportunity is not simply using more tools. It is understanding where AI can improve R&D decisions, accelerate timelines, strengthen development strategies, and ultimately help bring better therapies to patients.Guest information:Guest: Walid KamounRole: VP and Global Head of Oncology R&DCompany: ServierLinkedIn: https://www.linkedin.com/in/walid-kamoun-10223288/Company website: https://servier.com/en/servier/Tech & Drugs explores how data, AI, and technology are changing pharma, biotech, and drug R&D. Hosted by Thibault Geoui, the podcast brings together leaders, scientists, technologists, and builders working at the interface of science and technology.If you enjoyed this conversation, subscribe to Tech & Drugs for more discussions on AI, data, and the future of pharma and biotech.#AIinPharma #Oncology #DrugDiscovery #Biotech #PharmaRND
- Apr 21, 202638 min
From Code to Cells: Dov Gertz of Converge Bio on Generative AI and the Future of Drug Discovery
🎙 Tech and Drugs – Season 02, Episode 03From Code to Cells: Dov Gertz of Converge Bio on Generative AI and the Future of Drug DiscoveryIn this episode, I sat down with Dov Gertz, CEO and co-founder of Converge Bio, a company pushing generative AI directly into the language of biology.Dov represents a new breed of scientist.Trained in computer science and bioinformatics, with research roots in CRISPR discovery alongside leading pioneers like Jennifer Doudna, he is now building AI systems that don’t just analyze biology but actively design it.This conversation sits at the heart of what’s changing in our industry right now - From data to models to real-world impact.What we cover:✔️ Dov’s journey from computer science to CRISPR research and AI-driven biology✔️ Why the biggest bottleneck in AI for drug discovery is not compute, but data quality✔️ The shift from traditional AI to generative AI and why it changes everything✔️ How Converge Bio trains models directly on DNA, RNA, and protein sequences✔️ Why biology is fundamentally harder than NLP despite having more raw data✔️ The rise of autonomous labs and why they are critical to unlock AI’s full potential✔️ Why most clinical failures are not about targets, but about molecules✔️ How generative models can design better antibodies in a single iteration✔️ The reality of AI agents in science and why we are still far from “AI researchers”✔️ Why small, highly skilled teams are outperforming large R&D organizations✔️ The transition from AI experimentation to industrialization in pharma✔️ When we will actually see AI impact FDA approvals (and why it will take time)One idea that stood out for me: We are finally moving from AI as a tool… to AI as a generator of biology.That’s a very different paradigm.Dov brings a clear and grounded perspective on where AI truly works today, where it still struggles, and why the next breakthroughs will come from combining better data, better models, and tighter integration with experimental systems.If you care about the future of drug discovery, the role of generative AI in biology, and what it takes to move from promise to real impact, this episode is for you.I hope you enjoy this conversation as much as I did.
- Mar 3, 202648 min
From Tennis Courts to Molecular Design: Tim Hoctor on Data, Discovery, and the Future of Pharma
🎙 Tech and Drugs – Season 02, Episode 02From Tennis Courts to Molecular Design: Tim Hoctor on Data, Discovery, and the Future of PharmaLast December in Berlin, I had the privilege of sitting down with my friend and longtime mentor Tim Hoctor, one of the true legends at the intersection of technology and life sciences.Tim’s career defies categories.He started as a professional tennis player in California. From there, he stepped into early Silicon Valley startups, then into Molecular Design Limited, the birthplace of computerized chemical registration and what many still call the “MDL Mafia.” Later, he became a senior leader at Elsevier, helping shape how scientific data, literature, and databases connect in the digital era.This conversation is part industry history lesson, part strategic deep dive, and part personal reflection.What we cover:✔️ Tim’s unconventional journey from tennis pro to engineer to life sciences data executive✔️ How MDL pioneered digital molecular representation and why it became foundational to modern pharma✔️ Why linking structured databases to scientific literature was visionary in the 1990s and still unfinished business today✔️ The persistent data silos in pharma and why culture, more than technology, is often the bottleneck✔️ Why 6 billion dollar drug development costs are a systems problem, not just a science problem✔️ The real role of regulators in AI adoption and how agencies are asking industry to help define the future✔️ What COVID changed forever in automation, digital adoption, and supply chain resilience✔️ How tools like ChatGPT are reshaping behavior across pharma teams✔️ Why pharma still hasn’t had its “SpaceX moment” and what it would take to truly disrupt the model✔️ The vision of garage biotech powered by autonomous labs, shared data, and AI driven discoveryTim speaks with rare clarity about what holds our industry back, what gives him hope, and why better data sharing may ultimately matter more than the next algorithm.If you care about the evolution of pharma R&D, the cultural barriers to AI adoption, and what it will take to move from incremental efficiency to true system level change, this episode is for you.I hope you enjoy this conversation as much as I did.
- Feb 4, 202632 min
Inside Scientific Publishing, AI, and the Future of Medical Knowledge with Mitja-Alexander Linss
🎙 Tech and Drugs – Season 02, Episode 01Inside Scientific Publishing, AI, and the Future of Medical KnowledgeIn the opening episode of Season 2, I sat down with Mitja-Alexander Linss, Head of Marketing at Karger Publishers, one of the world’s oldest and most respected medical publishers, to explore how scientific communication is evolving in the age of AI.With over 130 years of publishing history behind it, Karger sits at a fascinating crossroads: peer review, trust, and scientific rigor on one side; AI, new formats, and radically changing consumption habits on the other. This conversation dives deep into what must change, what shouldn’t, and where AI can genuinely add value without breaking the foundations of science.What we cover in this episode:✔️ How scientists and clinicians really consume content today—and why short-form, video, and audio formats are rising fast✔️ Why peer review still matters, and how new formats may (slowly) enter the “version of record”✔️ Where AI is already used in publishing: fraud detection, reviewer matching, workflow optimization✔️ Why fully automated AI peer review remains ethically off-limits—for now✔️ The data licensing debate: LLMs, copyright, fair use, and why scientific data is different✔️ How publishers can responsibly collaborate with AI companies without undermining trust✔️ Augmented and virtual reality in scientific publishing—visualizing molecules and complex data in 3D✔️ The Vesalius Innovation Award and how Karger supports startups in AI and scientific communication✔️ A forward-looking vision: from searching papers to asking questions and getting evidence-based answersIf you’re interested in AI in science, medical publishing, research integrity, or how centuries-old institutions adapt to exponential technologies, this episode offers a thoughtful, grounded perspective—without buzzwords.
- Dec 17, 202530 min
Inside Helical: Bio Foundation Models, Virtual Cells, and the Future of AI-Native Drug Discovery
🎙 Tech and Drugs – Episode #11Inside Helical: Bio Foundation Models, Virtual Cells, and the Future of AI-Native Drug DiscoveryThis week I sat down with Rick Schneider, co-founder and CEO of Helical, a Luxembourg-based startup on a mission to democratize bio foundation models.Rick and his team are building something ambitious: an open, AI-native platform that lets pharma and biotech teams actually use large DNA, RNA, and single-cell foundation models, without needing their own supercomputer or an internal army of ML researchers. From training cutting-edge mRNA models on the Luxembourg HPC MeluXina to releasing beginner-friendly open-source tools, Helical is shaping the next generation of AI for science.What we cover:✔️ Rick’s journey from “almost doctor” to engineer, AI specialist, and now biotech founder✔️ What bio foundation models really are… and why unlabeled sequencing data changes the game✔️ Why one model will never solve all of biology, and why Helical is proudly model-agnostic✔️ How the field is inching toward a “virtual cell” built by combining multimodal model embeddings✔️ Pharma’s real bottlenecks: data scarcity, batch effects, validation culture, and… organizational speed✔️ How Helical enables lab-in-the-loop workflows without operating a lab themselves✔️ The explosion of new bio models, and how Helical helps teams evaluate what’s hype vs. useful✔️ Why shifting more hypothesis testing in silico could finally compress drug discovery timelinesIf you’re curious about where bio foundation models are heading, how pharma should rethink its AI stack, or what it means to build a truly AI-native biotech platform, this conversation with Rick is packed with insights.
- Dec 3, 20251h 7m
Inside Ginkgo Bioworks: High-Throughput Biology Meets AI
🎙 Tech and Drugs – Episode #10A special inside look at Ginkgo Bioworks, where automation, biology, and AI collide.I sat down with John Androsavich (GM, Ginkgo Data Points) and Jason Hocking (VP Engineering) to explore how Ginkgo generates huge multimodal datasets, automates complex biology at scale, and builds the infrastructure that today’s AI models desperately need.What we cover:✅ How Ginkgo evolved from synthetic biology to high-throughput data generation✅ Why clean, diverse datasets — not models — are the real AI bottleneck✅ A look at Ginkgo’s automation: modular “Rack” systems, NGS pipelines, and scalable cell models✅ Making data usable for both scientists and ML teams✅ The future of AI-guided labs and closed-loop experimentation✅ How shifting away from animal testing could accelerate human-relevant drug discoveryWhether you're in pharma, biotech, or AI for science, this episode is packed with insights on where R&D is headed next.
- Jun 4, 202550 min
Applying Google's Search Recipe to Pharma R&D Data - With Douglas Selinger from Plex Research
ere it is 🎙 "Tech and Drugs – Podcast" Episode #9 with 🧬💻 Douglas "Doug" Selinger from Plex ResearchThe theme for today: Applying Google's Search Recipe to Pharma R&D DataIn this episode of Tech and Drugs, I sit down with Douglas "Doug" Selinger, founder and CEO of Plex Research, whose unique approach is reshaping how scientists utilize data in drug discovery. While many companies are busy building predictive AI models, Doug and his team at Plex Research are leveraging techniques inspired by Google's internet search algorithms to make sense of vast and disparate datasets in pharma and biotech.Doug brings decades of experience, from pioneering microarray technologies in George Church's lab at Harvard to leading computational biology initiatives at Novartis. In 2017, he founded Plex Research to tackle the persistent challenges of data overload, silos, and underutilized information.We cover:✅ Doug's path from early genomics research to developing an innovative search-driven analytical platform designed specifically for scientists✅ How Plex's "focal graph" method integrates massive chemical biology and omics' datasets to reveal hidden connections in biological data✅ Overcoming Pharma’s persistent "data silo" problem by creating algorithms that adapt to the data scientists actually have✅ Real-world examples of Plex Research unlocking novel insights into disease mechanisms, biomarker identification, and precision oncology✅ Why transparency and explainability remain critical for AI adoption among scientists✅ The future potential of autonomous AI systems, combining knowledge graphs and large language models (LLMs), guided by human insightWhether you're navigating the complexities of data-rich environments or curious about pragmatic AI applications, this conversation provides actionable insights for improving decision-making in drug R&D.💬 How do you see search-inspired AI approaches changing drug discovery? Share your thoughts in the comments!
- May 21, 202547 min
Building a Data-Driven Pharma Organization Through Analytics & AI with Shionogi's Anindita “Ani” Sinha
Here it is 🎙 “Tech and Drugs – Podcast” Episode #8 with 👩🔬📊 Anindita “Ani” SinhaThe theme for today: Building a Data-Driven Pharma Organization Through Analytics & AIIn this episode of Tech and Drugs, I sit down with Anindita “Ani” Sinha, Vice President of Commercial Operations at Shionogi, whose journey from the microbiology lab to leading analytics, marketing, and field teams has shaped her vision for the future of pharma. With a BA in Biochemistry from Columbia and a PhD in Microbiology from Yale, plus nearly 15 years at Celgene, Bayer, Pfizer, and more, Ani shares how she:We cover:✅ How Ani went from academic research to consulting and then built “analytics first” teams in big pharma✅ Why AI is a powerful tool—but only when you “trust, verify, and know your data’s limits”✅ The critical steps to laying a solid data foundation: understanding, prioritizing, and connecting your datasets✅ Democratizing insights with self-service analytics and AI-driven platforms—finding the sweet spot between structure and flexibility✅ Strategies for attracting and retaining top tech-savvy talent in a highly regulated industry✅ What’s next: next-best-action models, predictive analytics, and cultivating an AI-ready workforceWhether you’re a scientist, data enthusiast, or industry leader, this conversation is packed with practical insights to help you harness analytics and AI for smarter decision-making in drug development and commercialization.💬 What data or AI challenges are you facing in life sciences? Share your thoughts in the comments!
About Tech and Drugs - Podcast
Welcome to Tech and Drugs, the podcast exploring how data and AI are revolutionizing Pharma and Biotech. Each episode features candid conversations with industry experts tackling real-world challenges, sharing success stories, and lessons learned. Explore how digital transformation accelerates breakthroughs and bridges the gap between tech and science. What You’ll Discover: • How AI is driving drug discovery and development. • Insights from the forefront of TechBio innovation. • Practical lessons for navigating digital transformation.
Customized Recaps
AI-powered recaps with compact key takeaways, quotes, and insights.
Straight to Your Inbox
Get key takeaways from Tech and Drugs - Podcast in a 5-minute read.
Save Hours Every Week
Stay current on your favorite podcasts without falling behind.
Frequently Asked Questions
What is Podzilla's Tech and Drugs - Podcast daily summary?
It's a free AI-powered email that summarizes new episodes of Tech and Drugs - Podcast as soon as they're published. You get the key takeaways, notable quotes, and links & mentions — all in a quick read.
How does the Tech and Drugs - Podcast podcast summary work?
When a new episode drops, our AI transcribes and analyzes it, then generates a personalized summary tailored to your interests and profession. It's delivered to your inbox every morning.
Is this an official Tech and Drugs - Podcast product?
No. Podzilla is an independent service that summarizes publicly available podcast content. We're not affiliated with or endorsed by Thibault Geoui.
Can I get summaries of other podcasts too?
Absolutely! The free plan covers up to 3 podcasts. Upgrade to Pro for 15, or Premium for 50. Browse our full catalog at /podcasts.
How often does Tech and Drugs - Podcast release new episodes?
Tech and Drugs - Podcast publishes monthly. Our AI generates a summary within hours of each new episode.
What topics does Tech and Drugs - Podcast cover?
Tech and Drugs - Podcast covers topics including Science, Life Sciences. Our AI identifies the specific themes in each episode and highlights what matters most to you.
Start getting Tech and Drugs - Podcast summaries tomorrow morning.
Free forever for up to 3 podcasts. No credit card required.
Free forever for up to 3 podcasts. No credit card required.