Sano combines genetic testing, recruitment, and long-term engagement in one platform, accelerating enrollment and simplifying operations for precision medicine
Cambridge, England
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🎙️Tune in to Episode 258 of #TheGeneticsPodcast 🚀
This week, we're joined by Dr. Inigo Martincorena, Group Leader at the Wellcome Sanger Institute. Listen in to hear how normal tissues carry widespread cancer-driver mutations (that rarely become cancer), what this reveals about autoimmune disease, and where new sequencing technologies are taking the field next.
Available here👇
🎧 eu1.hubs.ly/H0yzhcq0
📽️ eu1.hubs.ly/H0yzhjS0
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The therapeutic modality most teams would flag first for genetic complexity isn't where most of that complexity actually sits.
We analyzed 4,565 actively recruiting clinical trials across the US, UK, EU, Japan, and South Korea to see where genetic and rare disease relevance is concentrated by treatment modality.
Small molecule trials are the largest modality in the pipeline. Gene therapy and RNA therapy get most of the attention on genetic eligibility, and their rates are higher, 94% and 59%. But in raw numbers, small molecule trials alone produce more genetic-flagged trials than gene therapy, RNA therapy, and protein replacement combined.
A pipeline screen that only flags the modalities everyone already associates with genetics will miss most of where the volume actually is.
We broke down all 15 modality categories in our latest whitepaper.
🔗 Link in the comments below.
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🏆 The FDA just approved the first ever treatment for a fatal childhood disease that previously had none.
The therapy for Sanfilippo Type A is a single dose gene therapy, and it was approved largely on natural history data rather than a placebo controlled trial, since no placebo arm was feasible in a fatal pediatric disease.
In this blog, we cover important points that may be relevant for other sponsors in this space, including:
🔹 Nearly eight years of natural history data served as the trial's external control
🔹 A scientific bottleneck that's closing, replaced by a growing operational one around finding and confirming eligible children
🔹 Long-term follow-up data that becomes the evidence base for whatever comes next
Learn more here: eu1.hubs.ly/H0yt-XK0
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A positive genetic test doesn't tell you when cancer will arrive, only that the risk is real.
In the latest episode of The Genetics Podcast, Dr. Marleah Dean Kruzel, a communication researcher and hereditary cancer previvor, talks about what actually helps people live with that kind of uncertainty long term.
Our recap of the conversation covers a few of the ideas that stood out:
🔹 A test result as an answer, not a guarantee of certainty
🔹 A simple framework for assessing, reframing, and acting on uncertainty
🔹 Family disclosure as an ongoing conversation, not a single moment
🔹 Family planning decisions that hold both the clinical options and the emotional weight
Her point isn't that uncertainty goes away. It's that it can be named, worked with, and carried differently once you have a process for it.
📖 Read the recap or listen in full: eu1.hubs.ly/H0yrBhD0
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Genetic testing needs aren't showing up where most sponsors are watching for them.
In a new industry whitepaper, we analyzed 4,565 actively recruiting clinical trials across the US, UK, EU, Japan, and South Korea, classifying each one for genetic relevance, rare disease status, therapy area, and treatment modality.
Some key trends include:
✅ Genetic involvement now appears in nearly half of all oncology trials
✅ Treatment modality shows the widest range of any factor we measured
✅ A small group of biotechs carry most of the industry's rare disease trial volume
For teams building recruitment, testing, or account strategy around a therapy area, this data suggests treatment modality deserves as much attention as disease category when scoping where genetic complexity will land.
🔗 Explore the full whitepaper here:
eu1.hubs.ly/H0ymj-70
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🎙️Tune in to Episode 257 of #TheGeneticsPodcast 🚀
This week, we're joined by Dr. Marleah Dean Kruzel, Professor of Communication at the University of South Florida. Listen in to hear how her ART framework helps people manage the uncertainty of a positive hereditary cancer test result, and what she's learned about navigating difficult conversations with family and partners.
Available here👇
🎧 eu1.hubs.ly/H0ypCGx0
📽️ eu1.hubs.ly/H0ypCGy0
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🎙️Episode 257 of #TheGeneticsPodcast is live! 🚀
This week, Patrick is joined by Dr. Marleah Dean Kruzel, Professor of Communication at the University of South Florida. Tune in as they discuss:
🧬 Growing up with breast cancer across four generations of her family, and her own path to a positive genetic test result
🧠 The ART framework she developed for managing hereditary cancer uncertainty
👪 The complexities of communicating genetic risk within families and with future partners
🏥 How healthcare systems need to evolve to support people living with genetic risk information over their lifespan
Listen by following the link below 👇 or simply search “The Genetics Podcast” on your go-to podcast platform.
🎧 eu1.hubs.ly/H0ypCFG0
📽️ eu1.hubs.ly/H0ypCFb0
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A negative test result usually feels like an ending. In rare disease research, it can be the start of something else.
FDA draft guidance states that natural history data can play a role at every stage of drug development, including as an external control arm. That kind of reuse is valuable because fewer than 5% of the 10,000-plus known rare diseases have an approved treatment.
In one ultra-rare program, Sano kept 84% of individuals who tested negative for the target variant engaged as a longitudinal, re-contactable group.
Treating a trial cohort as a compounding asset changes what a "negative" result is worth. The full case for it is on our blog.
🔗 Link in the comments.
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AI can cut a drug discovery timeline dramatically, but there's still a lot if can't change.
In last week's episode of The Genetics Podcast, Dr. Dave Hallett, Chief Scientific Officer at Recursion, breaks down where AI is genuinely accelerating drug discovery and where the hype is getting ahead of the biology.
We cover key takeaways in our recap blog, including:
✅ How AI is speeding up chemistry design, target discovery, and trial simulation
✅ Why whole body physiology, toxicity, and long term effects still sit beyond what models can predict
✅ How most failed drug programs trace back to picking the wrong biological target in the first place
Learn more here: eu1.hubs.ly/H0yjM4m0
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🧬 The FDA recommends up to 15 years of long-term follow-up for gene therapies that use integrating vectors, up to 15 years for genome editing, and up to five years for AAV vectors, each set by product-specific risk assessment.
Follow-up frequently continues after licensure, and the agency may recommend a patient registry to support it. For a sponsor carrying several genetic-medicine assets, that obligation spans more than a decade per program.
Meeting it depends on staying connected to patients through site turnover, relocation, and the years between milestones. The cohort has to remain re-contactable long after the last dose.
📖 Learn more about the operational barriers to long-term follow-up and how sponsors work around them here: eu1.hubs.ly/H0yjnkL0
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In the latest episode of The Genetics Podcast, Dr. Danny Miller of the University of Washington and Seattle Children's Hospital makes the case for long-read sequencing, a single test that can capture the kinds of genetic changes usually spread across several separate tests. The cost gap with standard sequencing has already closed.
Our recap blog covers key takeaways, including:
✅ One long-read test can catch far more structural variation than standard sequencing
✅ Cost is no longer the barrier, pricing is now close to standard sequencing
✅ Bigger public reference datasets are making results easier to interpret
✅ Making genome data more open could turn it into a live part of a patient's ongoing care
Read more here: eu1.hubs.ly/H0y4_Vt0
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Rare disease recruitment gets even harder when eligibility depends on genetics or biomarkers.
Patients may be extremely rare, geographically dispersed, or still undiagnosed, and by the time enrollment pressure hits, sponsors may already be working with a limited set of options.
Our latest blog looks at why patient identification needs to start earlier in development, and how connecting genetic testing, diagnostics, patient engagement and trial execution can make recruitment more predictable.
We’ll be digging into this with our partner Labcorp at #DPHARM2026 next week, sharing examples from rare disease programs and exploring what a more connected patient-finding model can look like in practice.
Catch Ben Jackson and Pete Thornton:
Wednesday, September 16
⏰ 3:15–3:35 PM
📌 Constitution B
Or swing by booth 308 to chat with the Sano team in person.
🔗 Read the blog: eu1.hubs.ly/H0ydxjv0
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🎙️Tune in to Episode 256 of #TheGeneticsPodcast 🚀
This week, we're joined by Dr. Dave Hallett, Chief Scientific Officer at Recursion. Listen in to hear where AI is genuinely changing drug discovery (and where it isn't yet), how Recursion's perturbational maps uncovered a new neurodegeneration target, and what it takes to build conviction in a novel drug target.
Available here👇
🎧 eu1.hubs.ly/H0ycVCV0
📽️ eu1.hubs.ly/H0ycVCX0
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📣 Two large drugmakers recently paused trials of their autoimmune cell therapies following inflammatory reactions, including cases that proved fatal. The pauses are prompting a hard look at manufacturing, disease biology, and how precisely trials select patients.
Our latest blog covers key takeaways from these announcements, including:
🔹 Autoimmune diseases vary widely between patients, so broad eligibility criteria may not be precise enough
🔹 Some developers already exclude higher risk patients, hinting at where the field is headed
🔹 Better biomarker and clinical data could reshape how future trials define who qualifies
None of this diminishes the promise of these therapies. It signals a field moving from early, compelling results toward the harder work of understanding how they behave across heterogeneous patient populations.
📖 Read more here: eu1.hubs.ly/H0y9pBx0
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Around 81% of patients screened for rare disease trials are found to be ineligible, and more than half of the volunteers who consent are never randomized.
Every one of those patients represents months of genetic screening, site coordination, and relationship-building. When the trial closes, most sponsors let that work disperse and start the next program from zero.
The cohort gets booked as a fixed cost of one study. A different accounting treats it as infrastructure that carries across programs and years.
We wrote about how that shift changes the financial aspect of rare disease development.
🔗 Link in the comments below.
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🎙️Tune in to Episode 255 of #TheGeneticsPodcast 🚀
This week, we're joined by Dr. Danny Miller, Assistant Professor of Pediatrics and Laboratory Medicine and Pathology at the University of Washington and Attending Physician at Seattle Children's Hospital. Listen in to hear the case for making long-read sequencing the first genetic test every patient gets, how his lab is building a long-read reference dataset from 1000 Genomes, and his vision for genome-informed care from newborn screening through the NICU.
Available here👇
🎧 eu1.hubs.ly/H0y227f0
📽️ eu1.hubs.ly/H0y22800
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The FDA recently opened the door a little wider for drugs to reach approval on a single clinical trial.
New draft guidance clarifies when one well-controlled trial, backed by supporting evidence, can be enough to prove a drug works. The change lands hardest in rare disease and pediatric programs, where running a second trial is often neither practical nor possible.
✅ One trial can now be enough if it's paired with strong supporting evidence
✅ That trial still has to enroll a broad, genuinely representative patient population
✅ Supporting evidence can include natural history data, real world data, or related trial data
✅ Both requirements depend on finding and staying connected to the right patients over time
Learn more here: eu1.hubs.ly/H0xYXQ70
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Site capacity is contracting at the moment cell and gene therapy asks the most of it.
In a Tufts Center for the Study of Drug Development study, 70% of site staff said trials have become much more difficult to manage. A WCG survey found half of sites reduced the number of studies they agreed to run in the prior year. Complex protocols with narrow eligibility, specialized procedures, and long-term follow-up are exactly the studies that stretch already-strained teams.
When site readiness is assessed late and in isolation from diagnostic and data planning, activation slips, eligibility workflows break where diagnostic access varies, and follow-up data quality suffers.
Programs that deliver assess site capability early and in coordination with diagnostic and data strategy. They select sites against the real demands of the protocol rather than a generic profile.
🔗 Learn more in the report linked below.
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