Mendelspod Podcast

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.


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The 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.


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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!


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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.


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