Mendelspod Podcast

What if the hardest part of scaling cell therapy turned out to be a materials problem not a biological one—and the solution looked like a sponge?On today’s show, Theral speaks with Yev Brudno, Associate Professor in the School of Pharmacy and also the Department of Biomedical Engineering at the University of North Carolina at Chapel Hill, about a deceptively simple technology that could dramatically accelerate manufacturing and lower the cost of cell therapies. Brudno’s lab works at the intersection of chemistry, biomaterials, and cell biology, with a focus on removing the manufacturing and scalability barriers that have kept powerful therapies like CAR-T out of reach for most patients.At the center of the conversation is a dry, porous biomaterial sponge—developed initially by accident—that boosts viral transduction efficiency from roughly 10% to as high as 90% by forcing cells and viral vectors into intense, highly efficient contact. The sponge works across multiple delivery systems, including retroviruses, lentiviruses, AAVs, and even lipid nanoparticles, effectively functioning as a low-cost, scalable alternative to complex microfluidic systems. Brudno explains how this discovery reframes genetic modification as a physical- and materials-science problem rather than a purely biological one.The discussion goes beyond mechanism into real-world impact. Brudno describes how these sponges—now commercialized for research use by Takara Bio USA—could compress weeks-long CAR-T manufacturing workflows into hours, enabling bedside or community-hospital cell engineering without the need for $100-million cleanroom facilities. The episode closes with a broader reflection on the future of cell therapy.Once again, some of the most transformative advances might come from curious bench science and happy accidents rather than prediction alone. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

For today’s show, we return to discussing the exciting new Cellanome platform. Joining Theral are Pier Federico Gherardini, VP of Computational Biology at Cellanome, and Matthew Spitzer, Associate Professor at University of California, San Francisco, whose lab is using Cellanome’s CellCage technology to study immune cells in dynamic, interactive contexts.0:00 From static snapshots to observing cell function in real time4:45 Pairing phenotype with function like we never could before7:30 Can see cell-cell interaction19:40 Early applicationsRather than relying on static single-cell snapshots, the Cellanome platform enables longitudinal observation of live cells—tracking division, interaction, and function over time—before pairing those behaviors with transcriptomic and molecular readouts. As Gherardini explains, “This creates essentially a new data type where you observe cells over time… and then you can pair all of that functional information with the molecular readouts that you get from sequencing.”For Spitzer, that shift fundamentally changes what can be known. Traditional approaches often force scientists to infer function indirectly, correlating phenotype measured in one experiment with behavior measured in another. With CellCage, his lab can finally measure both in the same individual cell. “Now we have measured the function of the cell and the phenotype for the same exact individual cell,” Spitzer says, “and this allows us to really understand how those core characteristics are linked in a much more detailed way.”For Spitzer, a major advance comes from observing cell–cell interactions as they unfold. Where previous methods could show proximity in a tissue section, they could not reveal outcomes. Using Cellanome, Spitzer’s team can now watch whether a T cell activated by a dendritic cell actually proliferates, produces effector molecules, or kills a tumor cell—and then trace those outcomes back to specific molecular programs. This has already revealed surprising heterogeneity within supposedly uniform cell populations, identifying rare but highly potent immune cells that would have been invisible in bulk assays.Looking ahead, both guests see immediate applications in cell therapy development, target discovery, and functional CRISPR screening—areas where measuring what cells actually do matters more than what they merely express. We close with a sense that cell biology is entering a new phase—one where function, interaction, and time are no longer inferred, but directly observed, measured, and modeled. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

Half of oncologists in the U.S. are now ordering MRD testing, according to Adam ElNaggar, MD of Natera — but the other half, he says, “are still figuring out how to use it, or that it even exists.”In this episode, we talk with ElNaggar about the rapid rise of ctDNA-based monitoring and how it’s changing the very rhythm of cancer care. From Natera’s “tumor-informed” SignateraTM assay to its new “tissue-free” LatitudeTM test, the company is reshaping oncology around the molecular traces that cancer leaves behind.“ctDNA-negative patients have an extremely low likelihood of showing disease on imaging,” he explains. “So rather than scanning every few months, we can tailor follow-up to when it’s actually needed—and spare the anxiety and cost that come with it.”The conversation also covers Natera’s EmpowerTM hereditary cancer panel, which has expanded testing to all patients with ovarian and endometrial cancer, and a new Hereditary Cancer Alert program that nearly doubled testing rates among eligible patients. ElNaggar describes how hereditary and MRD testing now reinforce one another, helping clinicians catch missed cases and close the loop for families.We finish with a look ahead: a future where ctDNA status becomes a staging element, where clinical trials are shortened by molecular endpoints, and where multi-omic assays—combining DNA, methylation, and protein—push oncology toward truly personalized medicine.“We’re reaching the point,” says ElNaggar, “where staging won’t just be about pathology—it’ll be about biology.”Note about trials mentioned:IMvigor010 compared adjuvant atezolizumab to observation (surveillance) in an unselected muscle-invasive bladder cancer (MIBC) populationIMvigor011 prospectively randomized only ctDNA-positive MIBC patients to atezolizumab versus placeboSee all SignateraTM Publications here. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

Aging may be the last great frontier of precision medicine—not a single disease, but the slow re-patterning of immunity, metabolism, and resilience that determines how well and how long we live.In this wide-ranging and genuinely mind-bending conversation, Alan Landay and Tom Blackwell make a compelling case that aging itself is finally becoming a legitimate—and testable—target of medicine.For Landay, the path into aging biology began decades ago through HIV. Antiretroviral therapy transformed HIV from a fatal disease into a chronic one—but something didn’t add up. Patients were surviving, yet developing cardiovascular disease, neurocognitive decline, and metabolic disorders years earlier than expected. The immune system recovered on paper, but inflammation never fully resolved. That realization led Landay to view HIV as a model of accelerated aging, and to ask whether the same inflammatory processes drive aging in the broader population. As he explains, “we realized that persistent inflammation was the driver—pushing comorbidities forward in time. That’s when HIV stopped being just an infectious disease and became a window into aging itself.”Over the past decade, Landay has brought the full toolkit of systems biology to that question—proteomics, metabolomics, glycomics, microbiome analysis, and epigenetic clocks—to understand why some bodies grow frail while others remain resilient. A central theme is the gut: age-related changes in the microbiome weaken the intestinal barrier, allowing inflammatory signals to leak into circulation and quietly accelerate biological aging.Blackwell approaches the same problem from the clinic. As a geriatrician, he sees that most people ultimately die from one of three conditions—heart disease, cancer, or dementia—and that aging is the common denominator behind them all. His bold question is not whether we can treat these diseases individually, but whether we can slow the biological aging process that gives rise to them. That question underpins his ongoing clinical trial testing tirzepatide, a GLP-1–based therapy, not for weight loss, but for its potential to slow aging itself. ““There is no drug in the world proven to slow aging,” Blackwell says. “We haven’t proven this one either—but we’re finally running the experiment that can give us a real answer.”At the heart of the discussion is a shared fascination—and healthy skepticism—around aging clocks and biomarkers. Both researchers are using advanced epigenetic and proteomic clocks, including the DunedinPACE measure, to track whether interventions truly change the rate at which people age biologically. The clocks are powerful, but not yet definitive. The episode also explores how geroscience has moved from the fringe to the mainstream: NIH-wide initiatives, ARPA-H funding, repurposed drugs, and growing FDA openness to aging as a trial framework. Rather than chasing immortality, both guests emphasize healthspan—more years of mobility, cognition, and social engagement. “Our vision isn’t to live longer in a nursing home. It’s having a lot more 98-year-olds who drive themselves to clinic, go on dates, and still love their lives,” says Blackwell. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

This is a free preview of a paid episode. To hear more, visit www.mendelspod.comThe RNA revolution didn’t end with COVID. It’s only just beginning.Today Theral is joined by Andrew Geall, co-founder and Chief Development Officer of Replicate Bioscience, to explore why self-replicating RNA may represent the next major leap in vaccines and therapeutics. While first-generation mRNA proved what was possible in a pandemic, Andrew argues …

Perhaps more than in any other field, AI is impacting drug discovery and development. To begin the year we’re joined by two AI software-as-service companies, one on the target discovery side and the other built for new compound identification for those targets.Theral speaks with Aqib Hasnain, Product Lead at Mithrl, and Cheng Hu, co-founder and CEO of Technetium Therapeutics, about how scientists can go from AI generated insights to AI generated assets, from AI-driven fast science, to AI-driven fast drug discovery.Aqib describes Mithrl as a virtual lab partner focused on shrinking the time between experiments by letting scientists interrogate their own data directly. One of the biggest lessons in building Mithrl, he says, was how much transparency matters. Biologists need to understand the methodology through and through, and this translates directly to how Mithrl works.“Scientists need to be able to scrutinize and trace everything—because it’s their responsibility to make the next decision.”Cheng explains Technetium’s vision of an “AI-driven hatchery of novel medicines,” using design-based, physics-guided approaches to move from target discovery to small-molecule hits in weeks rather than years as has been the case screening libraries of millions of compounds. Reflecting on the promise of AI co-scientists, he points to the industry’s biggest unmet need. “There’s a very serious deficit of novel therapeutic targets and also a very serious deficit of novel chemicals.”Together, the conversation explores how these two AI tools for target discovery and hit generation are beginning to reshape drug discovery workflows—and how a new ecosystem of services is developing that is redefining the field. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

In our most listened to episode this year, Certis Oncology CEO Peter Ellman breaks down how his company is reinventing cancer research by building orthotopic patient-derived tumor models that more faithfully mimic human cancer — and using them to improve both drug development and treatment decisions. What is meant by orthotopic? That’s when patient tumors are placed in the “correct place” inside mice to create more faithful cancer models.Ellman shares the deeply personal origin story behind Certis and explains why their models have changed lives. He discusses the company’s AI-driven predictive platform, now patented, that aims to double drug success rates and usher in truly personalized oncology.Happy New Year 2026! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

As sequencing continues to become cheaper, more attention is being paid to sample prep. Today we’re following up with the company, Volta Labs, a genomics applications company transforming sample prep for NGS by increasing robustness and precision, and lowering operating costs. CEO Udayan Umapathi reflects on what has been a breakout first commercial year for Callisto, the company’s sequencer-agnostic, digital-fluidics platform for sample prep. When he was last on the show, Callisto had just launched. One year later, it is deployed across North America, Europe, and Asia, with rapid uptake in clinical labs, pediatric oncology centers, and high-throughput sequencing sites.Udayan says the scale of adoption surprised even the team. “We said we wanted to be the front end of every sequencing technology. We’ve actually done that,” he notes, adding that more than ten applications now support short- and long-read sequencing.What’s driving the momentum? Three things keep coming up from customers: true walk-away automation, the ability to run any chemistry on any sequencer, and major improvements in quality and cost. Labs without automation engineers can now “simply buy a kit and run software…without having to learn sample prep,” Udayan explains.A standout story this year has been pediatric oncology, where whole-genome sequencing and hybrid-capture workflows have shown strong performance on Callisto. Customers such as Prinses Máxima Center and UMC Utrecht are using the platform across Illumina, Oxford Nanopore, Ultima, and other chemistries, achieving the sequencer-agnostic vision Volta set out from the start.Looking ahead, Udayan sees sequencing as still early in its evolution and believes sample prep has vast room for innovation. “One platform to do Illumina, one platform to do Oxford Nanopore, one platform to do Ultima… long read, short read—we do it all,” he says. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

Few startups have launched with such quiet anticipation—or such a remarkable founding pedigree—as Cellanome. Backed by veterans of the genomics revolution, the company aims to do for cell biology what Illumina did for sequencing: make it measurable, dynamic, and multidimensional.In this debut conversation, Cellanome CEO Omead Ostadan traces his path from the early days of Applied Biosystems and Solexa to what he calls “the multi-omics of the cell.” He describes a breakthrough platform capable of observing living cells in real time, combining imaging, molecular analysis, and computation in ways that bring biology closer than ever to its native state.“Our hypothesis,” says Ostadan, “is that you are now creating an environment that most resembles the natural environment in which these cells operate. Anything you’re measuring is much more likely to resemble what you’re going to see in real biology.”Using what the company calls CellCage technology, the Cellanome R3200 system can isolate and sustain thousands of living cells or co-cultures—neurons with microglia, for instance—allowing researchers to track interactions, responses, and phenotypic changes over time. Ostadan believes this kind of structured, longitudinal, multimodal data will be foundational for the next generation of AI-driven biological models.“The next leap in biology,” he says, “requires a fundamentally different mode of data. That has been our focus from the start—to generate data that most closely resembles what’s happening at the foundational basis of biology across all organisms.”Now in full commercialization, Cellanome has multiple units installed in the U.S. and preparing for expansion into Europe and Asia. For Ostadan, who has helped bring multiple life-science platforms to market, this moment feels singular: “I’ve never been as excited about the potential of a technology as I am about what we have at Cellanome,” he says. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe

At the end of each year we look for a guest who in many ways defines the year. Today we sit down former NHGRI director Eric Green to reflect on the most turbulent year in his 31-year career at NIH. After leading the National Human Genome Research Institute for more than 15 years, Green’s appointment was abruptly non-renewed—a decision he learned about with “two or three days notice that I was going to have to retire from federal service.” What followed, he says, was a wave of terminations and forced retirements across NIH that left NHGRI “in trauma” as entire communications, education, and policy groups disappeared overnight.Yet alongside this institutional upheaval, Green describes a scientific landscape moving at astonishing speed—from the maturation of genome editing and long-read sequencing to the rise of multi-omics and the accelerating push toward routine healthy newborn genome sequencing. He believes widespread newborn sequencing is no longer a distant vision but “within striking distance,” driven by global studies, new U.S. programs, and rapidly falling costs.The conversation also explores the political pressures shaping genomics today, especially around the collection of heterogeneous genomic data and the cultivation of a diverse workforce. Green argues that scientists must learn to explain their work in human terms—as stories about patients and cures, not grants and budgets. He says it might also be a good idea to not use the “d” word (for example, “assortment” rather than “diversity”) in grants for now, silly as that is.Despite the personal and institutional losses of the past year, Green remains committed to the future of U.S. biomedical science which continues to surge in the headlines each day. In a reference to Dickens, he says it is literally the best and worst of times.Now entering what he calls “version 3.0,” Green sees his role as genomics evangelist, educator, and advocate—helping ensure that the momentum of genomic medicine continues even as the nation’s scientific infrastructure undergoes profound stress.“I am officially on call to help rebuild the NIH… It’s very easy to destroy a place, and very hard to rebuild it.” This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mendelspod.com/subscribe