Ion Genomics Podcast

Andrew P. Han

Ion Genomics brings you in-depth but also wide-ranging conversations with leading figures in genomic science and technology. Hosted by veteran science journalist Andrew P. Han, the Ion Genomics Podcast is a weekly window into the latest advances driving exploration of human biology. For more science and business news, check out www.iongenomics.bio and subscribe to the newsletter.

  1. Sep 18

    How Well Do AI Models Understand Wet Lab Work? With Benchling’s Nicholas Larus-Stone

    Nicholas Larus-Stone is Benchling’s Head of AI and coauthor of a new benchmarking study putting large language models (LLMs) like Claude and ChatGPT to work redesigning wet lab protocols.  The models did just fine, but didn’t blow the Benchling team away. “They can certainly be helpful at certain biological tasks, but they've by no means solved some of the kind of biology problems that people really care about,” Larus-Stone said. That said, he believes that pharmaceutical companies should be spending more on AI usage. That’s just one of several spicier takes we got into in our conversation.  Listen for more of Larus-Stone’s thoughts on why benchmarking LLMs is important, how open-source models can be competitive against proprietary ones, how he has fostered cross-pollination between software engineers and scientists by founding Bits in Bio, and whether he likes the term “TechBio.”  Show NotesBenchling’s Bench-Bench protocol study white paper Benchling blog post about the benchmarking study Bits in Bio Website Bits in Bio 2025 Annual Report Other AI benchmarking studies  From Jure Lescovec’s lab and the Biomni team: Qu et al. “BiomniBench: Process-level Evaluation of LLM Agents for Real-world Biomedical Research” bioRxiv. May 12, 2026. Guo et al. “PromptBio-Bench: Benchmarking LLM-based Bioinformatics Agents for End-to-End Data Analysis.” BioRxiv. June 1, 2026.  Other podcast episodes referenced https://www.iongenomics.bio/p/ai-agents-are-coming-for-the-lab

  2. Sep 11

    Mitochondria Are NOT Just the Powerhouse of the Cell, with Gordon Freedman

    Gordon Freedman and I both developed an interest in mitochondria due to our love of cycling and to understand the limits of performance. Whereas I sought to find a racer’s edge by delving into the biology underlying endurance sports, Freedman sought answers to a simpler question: Why can’t I push as hard as I used to be able to? Follow us down the rabbit hole to a world where there are multiple genomes to consider — one of them bacterial in nature — and a dearth of experimental tools has made it hard to connect mitochondria and their functions to other questions in biology and health. But there’s also hope that by connecting mitochondria to research areas such as cancer and neurodegenerative disease, scientists can peer further into the darkness than they could with only the light of the nuclear genome.  Show notes:  Gordon’s website, MitoWorld Distribution of pools of mitochondria in skeletal muscle cells. Image credit: Parry et al.  Parry et al. “Impact of Capillary and Sarcolemmal Proximity on Mitochondrial Structure and Energetic Function in Skeletal Muscle.” The Journal of Physiology. April 2, 2024. Guo, Y., Xue, Y. Mitochondria as convergence hubs for innate immunity pathways. Communications Biology. (June 8, 2026). Shen et al. “Mitochondria as Cellular and Organismal Signaling Hubs.” The Annual Review of Cell and Developmental Biology. July 8, 2022. IMDB page for A Brief History of Time. https://www.imdb.com/title/tt0103882/

  3. Jul 10

    AI Agents are Coming for the Lab, With Tahoe Bio CSO Johnny Yu

    My guest this week, Johnny Yu, has seen firsthand how the new code-writing capabilities of LLMs has widened horizons for the use of AI in biology. Tahoe Bio, a company he cofounded, has built its own AI agents, which are helping it rethink how to use AI in drug discovery and development. We discuss two other recent agentic AI developments from recent weeks. A publication in Science from Jure Leskovec's Stanford University Lab on Biomni, a multi-purpose, general intelligence that he hopes will help researchers get more out of their efforts. “What if every biomedical scientist had a tireless expert collaborator?," he said. "One that could actually go read literature, one that could actually go run the analysis, understand the data, design the experiments across any area of biology?” Started in 2024 and put up as an open-source project in 2025, Biomni — already being commercialized by a startup, Phylo — heralds a new wave of technologies that stand on the shoulders of the large language models behind products like Google Gemini and Anthropic's Claude.  Just last week, Anthropic launched Claude Science, another wide-ranging research aide that is also based on AI agents. And a recent leap in Claude’s ability to write code means even more are likely on the way. Researchers are already lining up to try them out. According to Leskovec and his Phylo cofounders Kexin Huang and Jerry Qu, more than 10,000 people have already started using Biomni. For more, check out the post on iongenomics.bio.

  4. Jun 26

    Maximal Cancer Diagnostics with Sid Sijbrandij and Jacob Stern

    In 2024, Sid Sijbrandij got the news that no cancer patient wants to hear: his tumor was back and his doctors told him they had nothing left to offer.  Sid, a tech entrepreneur who up until that point had been running his company, GitLab, went all in, doing as much testing and as many treatments as he could.  It seems to have worked. Moreover, Sid’s team thinks they’ve been able to figure out what went right, thanks to heaps of molecular data they’ve collected, including single-cell sequencing data. “It's very difficult, if not impossible, to do causative work in an N-of-1 study, but because we have this longitudinal sampling over the course of Sid's case, we can start to build a mechanistic hypothesis,” said Jacob Stern, a single-cell data expert on Sid's team and veteran of 10x Genomics. “Which seems to be that there was a bunch of combination immunotherapy that helped to rev up the immune system over the course of 2024.” Join Sid, Jacob, and I as we discuss the "maximal diagnostics” approach and how Sid plans to bring it to other patients who find themselves in a similar situation.During our chat, Sid mentions that he got a treatment from a company started by a friend he made at the Y Combinator startup accelerator. That company is Shasqi, founded by José Oneto. To see a timeline of Sid’s experience and all the data he and his team collected diagnosing and treating his disease check out osteosarc.com. Sid has also written about his experience on his personal Substack. For more information about Sid’s policy proposals, check out slide 17 of his embedded PowerPoint at https://sytse.com/cancer/ For more information about the cancer “playbooks” offered by the Sijbrandij Foundation’s Future of Cancer Care Today program, see: https://sijbrandijfoundation.org/fcct More information about the companies Sid is investing in to bring aspects of his maximal diagnostics approach to market is at Evenone.ventures.

  5. Jun 19

    Protein Sequencing-by-Subtraction with Pumpkinseed Cofounder/CEO Jen Dionne

    “We right now are developing our technology to be able very soon to sequence roughly hundred-length proteins that are on each of those sensors within a 24-hour period. You can think about this as being essentially 10 billion letters per day: 100 million sensors times those 100-mers on each sensor and then sequencing letter by letter.” That’s the scale that Pumpkinseed CEO and Cofounder Jen Dionne thinks her company can reach for analyzing proteins. The technology, developed in her lab at Stanford University, uses Raman spectroscopy to fingerprint molecules and Edman degradation to achieve sequencing-by-subtraction of peptides: 30 amino acids at a time now, possibly up to 300, or full-length proteins, in the future.  The ability to capture 10 billion amino acids per day would represent several orders of magnitude better throughput than the best and fastest proteomics methods available today, whether via mass spectroscopy or other single-molecule technologies being developed by competitors like Quantum-Si or Nautilus.  Remarkably, that’s still a long way from achieving the data acquisition rate that state-of-the-art high-throughput sequencers can achieve, but it’s enough to start thinking about making the type of impact that the first next-generation sequencers had on biological research.  Join us as we discuss the underlying physics behind Pumpkinseed’s technology, Jen’s journey from lab to C-suite, the applications they’re already pursuing, and her love of sports, including the World Cup.  For more information, check out pumpkinseed.bio or email Jen.  Links to papers discussed in the episode: Hu et al. Rapid genetic screening with high quality factor metasurfaces. Nature Communications, July 26, 2023. Zhang et al. From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis. ACS Nano, July 1, 2024. Stiber, et al. Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy. BioRxiv, February 23, 2026.

Ratings & Reviews

5
out of 5
4 Ratings

About

Ion Genomics brings you in-depth but also wide-ranging conversations with leading figures in genomic science and technology. Hosted by veteran science journalist Andrew P. Han, the Ion Genomics Podcast is a weekly window into the latest advances driving exploration of human biology. For more science and business news, check out www.iongenomics.bio and subscribe to the newsletter.