For years, precision oncology has largely been discussed through the lens of breakthrough drugs. But there’s another story running underneath modern cancer care: the quiet rise of companion diagnostics. These tests are increasingly deciding who receives those therapies in the first place. In many cases, the real bottleneck is no longer discovering a drug target. It’s building a reliable system for identifying the right patient at the right moment in the disease. That challenge sits at the center of this conversation with Rita Shaknovich, Chief Medical Officer for Life Sciences and Diagnostis, and Karina Kulangara, Associate Vice President of R&D in Companion Diagnostics at Agilent Technologies.

Agilent has always had a major role in this field. Rita and Karina explain how companion diagnostics evolved from the original Herceptin test into a vision for a much broader ecosystem spanning pathology, automation, regulation, and global clinical deployment.

We dive into Agilent’s recent FDA approval expanding PD-L1 IHC 22C3 PharmDx into ovarian cancer1, a development both guests describe as particularly meaningful given the historically poor outcomes associated with the disease. As Rita puts it: “Precision medicine is based fundamentally on scientific truth . . . it brought real results for patients. It brings better survival for patients, fewer side effects from the medication.”

Karina offers one of the clearest explanations we’ve heard for why immunohistochemistry or IHC has endured so long in modern oncology. “It’s the ability to detect protein biomarker in the spatial context of the tissue,” she explains, emphasizing that location and cellular context can fundamentally shape how therapies work.

What emerges is a picture of precision oncology that is becoming less exotic and more routine. We’re talking not just new drugs, but an entire clinical and technological infrastructure which is designed to match therapies to biology more effectively and over time.

Green takes us on a tour around the world of multi-omics, which he says is not a branding exercise but a practical response to the limits of sequence data by itself. Genomics remains foundational, but many clinical questions require additional layers of biology, including RNA, epigenomics, proteomics, and single-cell analysis. As he puts it, “DNA sequence alone may not reveal it.”

The discussion highlights rare disease as one of the clearest examples. Genome sequencing can solve roughly half of suspected cases, Green notes, but many patients remain undiagnosed because the relevant signal may lie in RNA splicing, epigenetic regulation, structural variation, or downstream protein effects. In those settings, multi-omic approaches can provide the missing evidence needed to move from uncertainty to diagnosis.

In oncology, the challenge is different. Cancer genomes can be highly complex and heterogeneous, making it difficult to distinguish driver events from background noise. That is one reason why researchers and clinicians are increasingly incorporating methylation markers, transcriptomic data, and proteomic signals into early detection, disease sub typing, and monitoring strategies.

Green also emphasizes that the next bottleneck may be less about generating data than interpreting it. “The human brain is not going to be the thing that’s going to crack this nut,” he says. “It’s going to be AI and computational biology.”

The result is an overall picture of where the field may be headed as we go from genomic medicine to a broader molecular medicine with multiple data types that will improve diagnosis, stratify disease, and guide care worldwide.

That may finally be changing.

In today’s episode Theral speaks with Dr. Yan Zhang, President of Proteomic Sciences at Thermo Fisher Scientific, about the rapid evolution of large-scale p…

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On today’s show, Rob Osborne, Senior Vice President of R&D at Biomodal, discusses new evidence that separating two epigenetic marks—5-methylcytosine and 5-hydroxymethylcytosine—can improve early cancer detection from liquid biopsy. In a recent Nature Communications Medicine study, his team showed that analyzing these signals independently in circulating DNA significantly enhanced detection of Stage I colorectal cancer compared with approaches that combine them.

The advance does not require new sequencing hardware. Biomodal’s approach uses a sample preparation kit compatible with existing platforms, paired with bioinformatics tools, potentially lowering the barrier to adoption while expanding the information content of standard sequencing workflows.

The underlying insight is biological as much as technical. Most methylation assays collapse 5mC and 5hmC into a single signal, masking early transitions in gene regulation. Osborne describes this as “squishing them into one output,” a simplification that can obscure meaningful changes in disease onset and progression.

By separating the signals, the study identified patterns that emerge earlier in tumor development, offering a more sensitive window into disease biology.

But the deeper message of the interview is that this work may only scratch the surface. “I think that we’re just at the beginnings of really understanding this biology,” Osborne says.

Drawing on her background in cancer research and now as CEO of Concr, Dr. Irina Babina joins us to argue that the future of oncology may depend less on g…

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On today’s show, Sir Shankar Balasubramanian revisits the accidental origins of Solexa sequencing, born not from a sequencing project at all, but from curiosity-driven experiments watching DNA polymerase at work. What followed helped transform DNA sequencing from a specialized pursuit into a routine engine of modern biology. But as Shankar makes clear, the biggest surprise may not have been genomics itself—it was how next-generation sequencing became a universal readout for biology, powering everything from single-cell and spatial biology to entirely new ways of probing molecules and mechanisms.

Our conversation then turns to his latest venture, Biomodal, and the emerging world of 6-base sequencing. Shankar explains why distinguishing 5mC and 5hmC matters, and how six-base sequencing may improve early cancer detection. 6-base sequencing could also aid researchers in the exciting frontier of neurobiology.

As always with great scientists, the story widens beyond any single technology. Shankar closes by reminding us that discovery follows better measurement. As our tools improve, biology will continue to surprise us.

“That is what research is. It’s stepping into the unknown,” he says.

Todays’ guest, Erdinc Sezgin, is an Associate Professor at Karolinska Institute and recipient of the Biophysical Society Early Independent Career Award. His lab is bringing physics to biology. For example, Sezgin studies the cell membrane not as a passive wrapper, but as an active, dynamic system whose physical properties of fluidity, viscosity, charge, and organization help determine how cells signal and survive. His hope is to improve ways to measure these biophysical properties.

Sezgin discusses his recent collaboration with Pixelgen Technologies, where Molecular Pixelation was used to study how changing membrane charge reshapes the cell surface. By knocking out a lipid-regulating complex, Sezgin and his colleagues showed that living cells can adopt surface features that alter immune recognition and may help explain how cancer cells evade destruction. It’s a reminder that major biological insights often arrive hand-in-hand with new tools that make previously hidden phenomena measurable.

The conversation closes on a broader point about scientific boundaries. Biology is not separate from physics or chemistry, but an expression of them in living systems.

“Cells don’t have physics, chemistry, biology. . . It is life,” he says.

You’ve heard of 5-base genomics. How about 6-base? It turns out that separating 5-methylcytosine (mC) and 5-hydroxymethylcytosine (hmC) is pretty important.

Peter Fromen has had a front-row seat to the evolution of sequencing, from the rise of high-throughput genomics at Illumina to long-read technologies at PacBio. Now, as CEO of Biomodal, he’s focused on integrating genetics and epigenetics into a single workflow—and showing that the regulatory layer of the genome may be where the next breakthroughs lie.

Chapters:

0:00: Why epigenetics needed a reset
12:07 The colorectal cancer study and early detection signal
16:41 Building the 6-base ecosystem
21:23 Commercial traction and the road to the clinic

In today’s program, Fromen explains why distinguishing between mC and hmC changes how we read biology. Biomodal’s recent colorectal cancer study begins to demonstrate that value in practice.

“We ultimately ended up generating an AUC of 95%,” he says, describing early-stage detection results that point to the power of combining both signals.

More broadly, he frames hydroxymethylation as an early indicator of disease.

“hmC is essentially the canary in the coal mine for early disease detection.”

We also discuss the practical side—what a 6-base workflow looks like in the lab and where the company sits commercially as it pushes toward clinical validation.

Will this be the new standard for how we read biology?

What is the value of someone’s genome over their life? Is a genome today what it was 10 years ago? How does the adoption of genomic testing compare to other areas in medicine, such as imaging or electronic health records?

Today we take a pretty comprehensive look at genomic testing in practice with Damon Hostin, Head of Market Access, Clinical Solutions at Illumina. Damon brings a rare perspective to this conversation. He’s been in the field since the Celera era, when sequencing was helping define modern genomics, and he’s also worked on the front lines in a large community health system, CommonSpirit Health. At Illumina, he speaks regularly with payers and other stakeholders.

Across oncology, rare disease, reproductive health, and pharmacogenomics, Damon describes a field that has clearly moved into standard of care in key areas—but is still very much in the phase of identifying the “eligible but under-tested.” Adoption is real, but it’s incomplete.

Chapters:

0:00 Genomic medicine arrives
4:51 Genomics, imaging, and the EMR
11:23 Oncology—from diagnostics to decision-making
18:16 Rare disease and reproductive genetics
28:51 The lifetime value of a genome
36:03 Cost, quality, and what a genome is

A central idea running through the podcast is that the genome is no longer a one-time diagnostic. Its value compounds over time as databases grow, variants are reinterpreted, and new therapies emerge.

At the same time, even the basic notion of what a “genome” is, is beginning to shift. With the rise of multi-omic data—transcriptomics, proteomics, methylation—the question is no longer just cost per genome, but what kind of biological insight we’re actually measuring. “A genome isn’t a genome isn’t a genome,” Damon says.

He ends with a line that neatly reframes the entire debate around cost: “When you look at the cost of healthcare . . . the cost of the genomics is almost nothing.”

Genomic medicine is here. We’re now wrestling with how to scale it, how to use it earlier, and how to make it part of the everyday infrastructure of care.

Note: For more discussion and analysis on this topic, check out this upcoming Virtual Roundtable Discussion at GenomeWeb.

In this conversation, Fei walks us through how Slide-tags—now commercialized as Takara Bio Trekker technology—set out to close that gap. Instead of mapping gene expression onto a grid, his team flipped the problem: barcoding the cells in place, then reading them out with single-cell sequencing. The result is something closer to a GPS system for cells.

What this unlocks is not just better maps, but better biology. Better questions. In cancer, Fei describes the discovery of local immune “circuits” that determine whether tumors respond to immunotherapy. And more broadly, spatial data turns tissue itself into a kind of experiment itself. Is this the biology of the future? “The spatial context is a natural experiment that has happened.”

Chapters:

0:00 The problem: structure vs gene expression
1:36 A GPS for cells
8:59 Immune circuits and cancer response
20:04 Tissue as experiment
26:24 New questions for biology

Across applications, Fei emphasizes that the real shift is conceptual. Spatial biology is not just about adding location to sequencing. It’s about learning how to ask new questions—ones that treat cells not as isolated units, but as participants in research.

But beneath the market excitement and the GLP-1 headlines, something more interesting is going on. A field that for years seemed technically promising but perpetually constrained is becoming wide open.

To see into that open terrain, we’re joined by Charlie Johannes, founder of EPOC Scientific and president of the Peptide Drug Hunting Consortium, along with Tomi Sawyer, a founder of the Consortium and founder of Maestro Therapeutics. We asked them for a high-level look at a field being reshaped by advances in chemistry, screening, delivery, and by a growing sense that peptides may be uniquely positioned to open up biology that other modalities have only partly been able to reach.

And yet both are clear: the field is not mature. AI is accelerating biology, which still depends on existing knowledge. Prediction remains limited, especially with non-natural chemistry. And the core challenge may now be human—how to turn an overwhelming amount of data into real innovation. As Johannes puts it, “Turning knowledge into innovation is the real challenge.”

Chapters:

1:31 Why peptides are suddenly hot again
6:10 Between small molecules and biologics
10:14 Oral delivery, screening
15:45 AI, automation, and the limits of prediction
32:17 The Consortium and where the field is heading

This is not a finished revolution—it’s a launch. The field, Sawyer says, is “in the Artemis II rocket right now heading towards the moon.” The peptide story is now much bigger than obesity drugs. Where does the field stand today? What has changed, and what remains difficult?

This episode is the first in a new partnership between Mendelspod and Peptide and Protein News, a media platform covering peptide and protein drug development. You can see what they’re up to at peptideandprotein.com.

• 0:00 A long journey inspired by PCR

• 7:20 What is sequencing by expansion?

• 14:00 On scale and accuracy

• 19:40 Multi-omics vision?

• 24:40 What will be the killer app?

• 30:00 Biggest challenge for launch

Kokoris recounts the long path from co-founding Stratos Genomics in 2007 to Roche’s acquisition in 2020, when his team’s “wildly ambitious chemistry” finally found its match in Genia’s high-density nanopore platform. “Our approach to efficiently sequencing DNA,” he explains, “is to not sequence DNA. We rescale the problem—expand the molecule about 50-fold—so we can read it with much higher signal-to-noise.”

The result is astonishing speed. Working with the Broad Institute and Boston Children’s Hospital, SBX delivered whole-genome results in under four hours, with the sequencing step itself taking only about 15 minutes. Kokoris attributes the achievement to a confluence of chemistry and compute.

SBX’s duplex mode achieves Illumina-level accuracy (F1 > 99.8 %) while maintaining single-molecule simplicity. Its tunable flexibility lets small labs run a handful of samples in hours or large centers run thousands per day. Kokoris describes it as a technology built on impatience and rule-breaking, designed to give scientists options they’ve never had.

Looking ahead to the 2026 research-use launch, he’s characteristically bold:

“For me, success means SBX becoming the new standard in sequencing. Innovation can’t stop—it has to keep evolving, because biology is complex and we’ve got a lot more to do.”

This show was originally published Nov 11, 2025.

That question opens today’s interview with Steve Austad, Distinguished Professor at the University of Alabama at Birmingham and one of the leading thinkers in the biology of aging. It quickly becomes clear why he’s been such an important voice in bringing aging research from the margins into the center of science. As he puts it, the field was once “where scientists went to die,” but with modern genetic and molecular tools, it has become one of the most active areas in biomedicine.

Steve’s approach, laid out in his book for the empiricist (I’m an amateur), Methuselah’s Zoo, is deceptively simple: look at the animals. From birds and bats to clams that live for centuries, he shows that lifespan follows a clear evolutionary logic. Safer, more stable environments favor slower aging. “If it’s unstable and unsafe… it makes sense… to reproduce fast,” he explains, while protected environments allow organisms to invest in long-term maintenance. It’s a framework that turns curiosity into theory—and theory into something testable.

Chapters:

1:31 Where scientists went to die
4:11 The opossum problem
8:00 Air, land, sea
14:23 The longevity quotient
33:30 Not forever, just longer

What makes Steve such a compelling guide is his tone. He’s low-key, almost amused at times, but unwavering on the science. Aging, he reminds us, isn’t programmed for our benefit—“evolution does not care how long you live.” That doesn’t mean we can’t intervene. The field is now moving into human trials, even if key tools like aging clocks are still imperfect. He has little patience for talk of immortality—calling it “completely delusional.” Still, he’s optimistic. Adding a decade or two of healthy life—not forever—is the goal today.

Joining us on the program are Chris Hourigan, Director of the Fralin Biomedical Research Institute Cancer Research Center (DC) at Virginia Tech, bringing the academic and clinical AML lens, and Gary Pestano, Chief Scientific Officer at Biodesix, offering the industry and diagnostic development perspective.

Hourigan reminds us that MRD itself isn’t new. What was missing were the tools. From counting cells under a microscope to flow cytometry and now highly sensitive molecular techniques including droplet digital PCR, MRD has evolved into a quantitative, actionable signal.

Coming from the side of commercializing and scaling assays, Pestano underscores the central challenge of distinguishing meaningful signal from background noise. “There is a lot circulating in our blood. The key is what is meaningful, what is not meaningful,” he explains. Sensitivity alone isn’t enough. Target selection, bioinformatic filtering, validation at scale, and real-world reproducibility all determine whether MRD can truly guide care.

The field is very much still work in progress, say both.

Looking ahead, they point toward quantification as the next frontier. MRD is no longer just about detecting what remains. It’s about deciding what happens next.

“We’ve been talking about MRD as if it’s a binary concept” says Hourigan. “I can imagine in the future, there’s going to be windows, and we will tune therapy to what comes next.”

Thank you to Bio-Rad for sponsoring today’s show. Bio-Rad is your trusted partner for absolute quantification and reproducible results in oncology research. Bio-Rad helps you move from data to confident decisions. Learn more at bio-rad.com/oncology.

For today’s program, George Sledge, Chief Medical Officer at Caris Life Sciences, discusses new findings from the TAILORx trial showing how multimodal AI—combining molecular sequencing, digital pathology, and clinical data—can improve long-term prediction of breast cancer recurrence.

Sledge explains that breast cancer recurrence may actually reflect two different biological processes unfolding over time. Molecular signals captured through RNA analysis appear most informative for predicting recurrence in the first five years, while computational analysis of digital pathology images becomes especially powerful for predicting recurrence later in the disease course.

“The best results come from looking at multiple omic levels,” Sledge says, describing a shift away from single biomarker tests toward integrated biological analysis.

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Theral speaks with Sudhakaran Prabakaran, computational biologist at Northeastern University and founder of NonExomics, about his provocative new book, “Eclipsed Horizons: Unveiling the Dark Genome.” Drawing on his lab’s work cataloging more than 250,000 non-canonical proteins, Prabakaran argues that regions outside traditional gene definitions are constantly generating novel open reading frames—previously unrecognized proteins that may shape adaptation, speciation, and disease.

Chapters:

(00:00) Identical Genomes, Wildly Different Fish

(04:00) The Dark Proteome Wakes Up

(10:00) Protein Pop-Up Shops

(20:00) Homo Minimus and the Space Thought Experiment

(30:00) Precision Medicine Beyond the Exome

From rapidly diversifying cichlid fishes to human accelerated regions (HARs) of the human genome linked to schizophrenia, he makes the case that protein birth and death is continuous, cheap, and exploratory. In his framing, the “dark genome” functions less like debris and more like a flexible evolutionary sandbox—capable of producing latent biological parts that can be deployed under stress or even extreme environments like spaceflight.

The book goes beyond ENCODE’s demonstration of activity and asks what that activity is for, crossing into that taboo in biology, teleonomic analysis. Weaving together proteomics, evolutionary biology, information theory, and even speculative extensions into space biology, Prabakaran suggests that genomes may be structured not just to preserve past adaptations, but to enable future ones.

For those of you staying put on the ground, the implications are very tangible for precision medicine. His company NonExomics is using non-canonical protein signatures to stratify cancer patients and refine difficult diagnoses, arguing that the next wave of biomarkers may lie outside the exome.

Provocative? Certainly. Grounded in emerging proteomics tools and real clinical cases? Also yes. This conversation probes directly into that mysterious future of biology.

That’s Stephen Kingsmore, president and CEO of Rady Children’s Hospital (he just announced his retirement), explaining the impact of a new genome mapping technology from Illumina.

Whole-genome sequencing has transformed diagnosis, but some of the hardest pediatric cases persist because the structure of the genome has remained difficult to resolve. Today on Mendelspod, we cover Illumina’s newly launched proximity mapped reads, showing how long-range genomic context can be captured directly on existing Illumina sequencers and integrated into the lab workflow. The conversation traces how this added structural clarity is already improving diagnostic confidence and, critically, enabling highly precise n-of-1 therapies such as antisense oligonucleotides (ASOs).

Olivia Kim-MacManus, a pediatric neurologist and ASO trial leader, shows how the new diagnostic precision directly feeds therapeutic design.

“All of these genetic therapy approaches hinge on precise diagnostics,” she notes, emphasizing that allele-specific and haplotype-aware targeting is essential for ASOs and other emerging gene-based interventions.

From the product and workflow side, Ali Crawford joins us as Senior Director of Science Research at Illumina, detailing how the technology works without requiring new instruments or complex workflows, eliminating the need for separate library preparation steps.

“You just order the kit and go,” she says, highlighting how preserving spatial information on the flow cell unlocks variant calls and structural insight that were previously inaccessible with their standard short-read sequencing.

When genome structure comes into better focus, treatments are no longer theoretical.

Now, under CEO John Hanna, the company looks less like a single-test diagnostics firm and more like a clinical ecosystem.

Hanna brings an unusual vantage point. He began his career in health insurance before moving into molecular diagnostics—giving him insight into both innovation and reimbursement. That dual perspective shaped CareDx’s recent evolution: focus tightly on a defined clinical niche—transplantation—while expanding horizontally into the tools, software, and services that surround it.

Today, CareDx operates across three segments: lab products (including high-resolution HLA typing kits using PCR, NGS, and nanopore), a growing software and patient solutions business, and its flagship genomics portfolio led by AlloSure, its donor-derived cell-free DNA assay. What distinguishes the company now is its “solution selling” approach—engaging transplant centers not just with a test, but with workflow software, quality reporting tools, specialty pharmacy, and EMR integration.

“Our solution selling strategy is working,” he says today.

At the scientific core remains the effort to replace invasive biopsies with molecular monitoring. AlloSure’s innovation—detecting donor-derived cell-free DNA without requiring donor genotyping—made routine blood-based rejection monitoring scalable. Yet adoption is not purely technical.

“The biggest challenge with our space is building belief that molecular testing can replace tissue biopsy.”

Clinician education, clinical trials, and guideline inclusion remain central to shifting standards of care. CareDx has leaned heavily into this, hiring medical leadership specifically to translate data into practice. The company is also layering AI on top of its molecular assays. AlloSure Plus integrates genomic results with EMR-derived clinical variables to generate a rejection risk score. CareDx’s operational mantra has been to put the burden of complexity on the company, not the clinician.

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In this episode of Mendelspod, we return to the kind of ambitious, shared genomics project that helped define the field a decade ago. The Global Parkinson’s Genetics Program (GP2) has now genotyped more than 100,000 participants worldwide, with roughly one third of samples coming from historically underrepresented populations. That scale and diversity are already reshaping how Parkinson’s disease is studied — and how it may eventually be treated.

My guests are Andrew Singleton, co-lead of GP2, and Ignacio (Nacho) Mata, a geneticist at Cleveland Clinic and founder of the Latin American Research Consortium on the Genetics of Parkinson’s Disease (LARGE-PD). Together, they describe how globally representative datasets are not a political aspiration, but a scientific necessity — especially in an era of precision medicine.

Singleton explains that studying Parkinson’s across populations doesn’t just broaden participation; it increases scientific power.

“The more we learn about individual populations, the more we understand about disease as a whole — and the more chances we have to come up with treatments for disease as a whole,” he says.

Mata brings a complementary perspective from years of building Parkinson’s genetics infrastructure in Latin America. He emphasizes that without inclusion in genetic and biomarker research, entire populations risk being excluded from the next generation of molecularly targeted therapies.

“If we don’t have our patients studied for genetics or biomarkers, then those patients will not have access to the new treatments,” he notes, adding that GP2 is designed to narrow rather than widen existing health disparities.

We explores how GP2’s open-science structure has been key to its success and could serve as a model for other global research projects. GP2 has invested heavily in training and infrastructure so that researchers around the world can lead analyses locally, rather than simply contributing samples.

As both guests make clear, this is only the beginning. With hundreds of thousands of samples committed and a new generation of globally distributed investigators, GP2 is laying the groundwork for biologically defined subtypes of Parkinson’s and for more precise diagnostics and disease-modifying therapies.

When genomics gets big enough — and inclusive enough — scale itself becomes a discovery.

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.