Mendelspod Podcast

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Can we scale our way to a better understanding of biology?
When we first had the CEO and founder of Ultima Genomics on the show, the company had just emerged from stealth with an ambitious vision. Coming from the semiconductor industry, Gilad Almogy believed that dramatically reducing the cost of DNA sequencing would enable scientists to study biology at an entirely new scale. And that scale would lead to discoveries we couldn’t yet imagine. A few years later, Ultima has announced the $60 genome and is partnering on some of the largest biological research projects ever undertaken.
Almogy returns today to discuss the company’s progress and how the arrival of AI has accelerated his original vision. Ultima’s new UG200 platform offers greater throughput, improved coverage and paired-end sequencing, expanding the technology’s applications beyond large-scale counting experiments into whole-genome sequencing and clinical testing.
Among the company’s major collaborations are the Billion Cells Project with the Chan Zuckerberg Initiative and the Arc Virtual Cell Atlas. Both aim to generate enormous datasets of cellular responses to perturbations, providing training data for AI models that could eventually predict how cells behave. Almogy argues that biology may be too complex to model using traditional mathematical approaches alone. As he puts it, “A cell is a video. It’s not an image.” He believes AI could do for biology what mathematics did for physics.
The conversation also explores Ultima’s population genomics partnerships with Mayo Clinic and Singapore. Mayo’s Precure Initiative aims to combine whole-genome sequencing and proteomics with electronic health records from a million patients, while Singapore’s national precision medicine program will test how genomic information can improve clinical care. Almogy sees these efforts as complementary to the virtual cell projects, approaching biology from the level of entire populations rather than individual cells.
Finally, Almogy discusses the growing importance of longitudinal sequencing and liquid biopsy. Ultima’s ppmSeq technology, designed to detect variants at frequencies as low as one part per million, could help enable more sensitive MRD testing in cancer treatment.
The future of biology will require models at several scales, from individual cells to entire populations, along with dynamic models that follow how human health changes over time. These models will need vast amounts of data. The hope is that AI will find insights in this data that we haven’t yet imagined, ultimately making biology more predictive and leading to earlier disease detection and better medicine.

Precision oncology is entering a new phase. Rather than simply profiling a tumor and matching it to a drug, physicians are increasingly able to follow a patient’s cancer over time, measuring treatment response, detecting residual disease, and adjusting therapy as the disease evolves.
Jerry Radich of Fred Hutch Cancer Center has been at the forefront of this evolution. His pioneering work in chronic myeloid leukemia (CML) helped establish molecular monitoring as a critical part of cancer care and prefigured the rise we see in MRD testing today. Some CML patients can even discontinue treatment after achieving a sustained deep molecular response. Radich discusses how this remarkable success has become a model for other blood cancers.
He’s now helping lead myeloMATCH, a national precision oncology initiative that brings together clinical trial groups across North America. With some 350 participating sites and molecular results typically available in less than 48 hours, the program is matching patients with acute myeloid leukemia to clinical trials based on their cancer’s genetic profile. Radich sees an opportunity not only to personalize treatment but to accelerate drug development by using molecular response as an earlier measure of efficacy.
We also explore the limits of molecular profiling, the emerging role of the immune system, and why increasingly sensitive tests may transform how we understand cancer. Looking ahead, Radich imagines a future in which patients could monitor their disease burden almost continuously, perhaps even through wearable or implantable devices.
Radich is co-chairing the upcoming APOAPE conference in Seattle on January 15, bringing oncologists and pathologists together to connect advances in molecular diagnostics with real-world treatment decisions. The conference is free for healthcare professionals.
Learn more about the APOAPE conference


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In the US, we have the All of Us Research Program. In the UK, they have Our Future Health, an ambitious new population health research program that aims to make healthcare more preventive than reactive. Launched just four years ago, it has already recruited nearly three million volunteers toward a goal of five million, making it one of the world’s largest health research initiatives.
Today we’re joined by Raghib Ali, CEO and Principal Investigator of Our Future Health, to discuss how the program builds on the success of UK Biobank while pursuing a different goal. Rather than simply studying the causes of disease, Our Future Health aims to establish the evidence needed to move healthcare from diagnosis and treatment toward prediction and prevention.
Ali discusses the program’s plans to combine polygenic risk scores with clinical and lifestyle data to develop integrated disease risk scores. A new clinical trials platform will test whether personalized prevention actually improves outcomes. The ultimate ambition is to bring successful approaches into routine NHS care.
Perhaps most encouraging is the public response. More than a million participants have come from historically underrepresented groups, raising the possibility that precision medicine could help reduce health inequalities rather than widen them.
As Ali puts it, the goal is to move from a national sickness service to a true national health service.


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In recent months on Mendelspod, we’ve explored how new sequencing and proteomics technologies are revealing biology in regions of the genome (and proteome) that have long escaped our attention. From repeat expansion disorders to new approaches in cancer diagnostics, the dark genome is increasingly becoming clinically relevant.
Today we’re revisiting a conversation from earlier in the year that asks an even bigger question. What if much of this unexplored genomic territory is not simply functional, but a reservoir of evolutionary possibility?
Last March, we talked with Sudhakaran Prabakaran, computational biologist at Northeastern University, founder of NonExomics, and author of Eclipsed Horizons: Unveiling the Dark Genome.
Drawing on his lab’s work cataloging more than 250,000 non-canonical proteins, Prabakaran argued that regions outside traditional gene definitions may be continually generating new proteins with implications for adaptation, evolution, and disease.
From rapidly diversifying cichlid fishes to human accelerated regions (HARs) of the human genome linked to schizophrenia, Sudhakaran 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. His company, NonExomics, is also exploring how these previously overlooked proteins might become biomarkers for cancer and other diseases.
As our recent interviews have demonstrated, we’re entering a new era of genomic discovery. Prabakaran challenges us to think about just how much biology remains to be found.


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Repeat expansions are places where the genome has remained stubbornly dark. Long-read sequencing is beginning to illuminate them, and now that new visibility is moving into clinical testing.
Today we’re joined by Simon Sadedin, Head of Clinical Bioinformatics at Victorian Clinical Genetics Services in Australia, and Alex Lindell, Senior Director of Product Marketing at Oxford Nanopore.
Until now, testing for repeat expansions has largely meant building a separate assay for each disorder. A patient might be tested for Fragile X, get a negative result, and then move on to another test, sometimes waiting months at each step. Some repeat expansions have been difficult to test for at all. Simon’s group is trying to replace that serial approach with a single assay covering roughly 60 repeat expansion loci, which is now being submitted for clinical accreditation.
The promise goes beyond simply finding an expansion. Long reads can reveal its length, sequence, methylation and mosaicism, while adaptive sampling makes it possible to target these difficult regions in software rather than building a new wet lab assay for each one.
Some say we are at a new threshold in genomics, where parts of the genome that have remained dark are finally becoming accessible to both discovery and clinical medicine.


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