Sano Genetics

💰 The most expensive recruitment mistakes in clinical trials get made before the first patient is ever contacted. Lindsey Wahlstrom, patient engagement expert and founder of Rona's FunLab, put it directly in a rare disease-focused webinar: "Recruitment challenges are locked in at the moment of protocol lock. If you are not engaging families prior to that point, you might struggle with recruitment. It's not a marketing thing. It's a design thing." By the time a trial opens, eligibility criteria, visit schedules, consent materials, and site workflows are already fixed. Those decisions determine whether eligible patients can realistically be identified, confirmed, and enrolled. Approximately 85% of trials fail to recruit enough patients. Pouring budget into advertising cannot fix a protocol that was designed without input from the patients it was built to serve. Earlier patient engagement in protocol development is one of the clearest ways to reduce downstream recruitment failure. ❓ How early do patient advocates get involved in the trials you work on?

🎙️Tune in to Episode 241 of #TheGeneticsPodcast 🚀 With Encoded Therapeutics making recent progress in Dravet syndrome gene therapy, we’re revisiting Patrick’s conversation with Salvador Rico, Chief Medical Officer at Encoded. Listen in for lessons from XLMTM, the realities of gene therapy development, and what it takes to turn genetic insight into meaningful medicines. Available here👇 🎧 eu1.hubs.ly/H0vJsc40 📽️ eu1.hubs.ly/H0vJqDl0 #Genetics #Genomics #PrecisionMedicine #GeneTherapy

💡 Screen failure in precision medicine trials is typically framed as a recruitment problem, but it’s more often a design problem. Across Sano-supported rare disease programs, eligibility rates among participants who complete onboarding run as high as 98%. This means the funnel works. The fracture point comes after eligibility confirmation, when participants are asked to order a genetic testing kit. Across studies, the proportion of eligible participants who actually order a kit ranges from 28% to 97%. That variance is enormous, and it is almost entirely shaped by how the testing pathway was designed. At-home testing options, clear instructions, timely follow-up, genetic counseling access, and transparent communication about results all determine whether an eligible participant continues or drops out at exactly the moment they are asked to take a concrete step. Sponsors who focus only on top-of-funnel volume miss this entirely. The real question is what happens to eligible participants after confirmation. 📖 To learn more, visit the article linked in the comments below.

New data from the LiveWell study shows that CLDI, a longitudinal measure derived from routine NHS blood tests, identifies clinically significant liver fibrosis with an AUC of 0.884, compared to 0.572 for FIB-4, the most widely used first-line test. The study, sponsored by Sano and funded by Innovate UK, recruited 994 participants from a single NHS site in under a year. It was conducted alongside partners Predictive Health Intelligence, Tawazun Health, and Somerset NHS Foundation Trust, and results were presented today in a late-breaking abstract at the EASL Congress in Barcelona. The practical implications are significant. CLDI uses data that already exists in NHS systems with no new tests or infrastructure required. Patients at high risk can be referred directly to transient elastography, creating a one-step pathway from identification to diagnostic confirmation. For the research community, this matters too. With more than 130 active MASLD studies currently underway, patient identification is one of the biggest constraints on trial efficiency. More accurate population-level screening accelerates recruitment and reduces screen failure. A wider validation study involving 8,000 patients is now in progress, with results expected later this summer. Read the full press release: eu1.hubs.ly/H0vFnFC0 #LiverDisease #MASLD #PrecisionMedicine #ClinicalTrials #EASL2026

🧠 What if treating Huntington’s disease requires looking beyond the mutant protein? For years, much of the field has focused on lowering mutant huntingtin. But Dr. Vincent Dion’s work points to another possibility: targeting the genetic instability that drives disease progression itself. In the latest recap from The Genetics Podcast, we cover key takeaways from Vincent’s conversation on: 💡 Why DNA repair can become a disease driver in Huntington’s 💡 How CRISPR nickase editing can contract toxic CAG repeat expansions 💡 Why correction could offer a different path from long-term gene silencing 💡 What it takes to move a basic science discovery toward first-in-human studies Read the full recap here: eu1.hubs.ly/H0vFqQX0 #Genomics #HuntingtonsDisease #GeneEditing #PrecisionMedicine

🎙️Tune in to Episode 240 of #TheGeneticsPodcast 🚀 This week, we’re joined by Dr. Vincent Dion, Group Leader at the UK Dementia Research Institute at Cardiff University. Listen in to hear how somatic repeat expansions drive Huntington’s disease, why DNA repair can make these mutations worse, and how CRISPR nickase editing could shrink disease-causing repeats at the DNA level. Available here👇 🎧 eu1.hubs.ly/H0vxyv10 📽️ eu1.hubs.ly/H0vxzj90 #GeneEditing #HuntingtonsDisease #Genomics

📊 Traditional recruitment metrics count activity. Precision medicine requires metrics that count outcomes. Screens completed and tests ordered tell you how busy the funnel is. But what they don’t tell you is whether the right patients are moving through it. In genetically stratified trials, a high volume of screens with low eligibility confirmation rates signals a targeting problem rather than a recruitment success. The metrics that actually predict trial performance are pre-screening completion rates, time from initial contact to genetic confirmation, referral-to-enrollment conversion, and retention through study completion. Retention is particularly underweighted. Participants who disengage before completing the study leave behind incomplete datasets. In precision medicine, where each participant represents a highly specific and rare data point, partial data is a significant loss. Sponsors who track engagement metrics across the full trial lifecycle get early warning signals before enrollment shortfalls become schedule delays. ❓ Which of these metrics does your team currently review on a weekly basis?

🧠 Some of the most important biology in neurodegenerative disease may be hiding in regions of the genome that have been hardest to study. Our new recap of last week’s episode of The Genetics Podcast with Dr. Paul Valdmanis, Associate Professor at the University of Washington, explores how long-read sequencing is reshaping what researchers can see in Alzheimer’s disease, ALS, and other complex conditions. 🔗 Read the recap here: eu1.hubs.ly/H0vqsJH0 #TheGeneticsPodcast #Neurodegeneration #Alzheimers #ALS #Neurogenomics

⚠️ Screen failure is often treated as a recruitment problem. In precision medicine trials, many of the biggest barriers are already built into the trial design before recruitment begins. Our latest article looks at why eligible participants can still drop out before enrollment, especially when genetic confirmation is required. 🧬 Using data from rare disease trials Sano has supported, the article explores where the funnel commonly breaks and practical ways to design trials around conversion quality, including clearer testing pathways, earlier patient input, better site enablement, and participant journeys that help people move from interest to action. Read the full article here: eu1.hubs.ly/H0vqtbt0 #PrecisionMedicine #ClinicalTrials #TrialOperations #GeneticTesting #RareDisease

🧠 Alzheimer’s research is becoming more precise, more complex, and more patient-centered. In our latest blog, we bring together insights from four episodes of The Genetics Podcast to explore what this shift could mean for the future of Alzheimer’s precision medicine. The conversations cover biomarkers, APOE genetics, microglia, disease timing, population diversity, and patient involvement. 📖 Read the blog here: eu1.hubs.ly/H0vl-3q0 #TheGeneticsPodcast #AlzheimersDisease #PrecisionMedicine #Genomics #Biomarkers #DementiaResearch

🎙️Tune in to Episode 239 of #TheGeneticsPodcast 🚀 This week, we’re joined by Dr. Paul Valdmanis, Associate Professor at the University of Washington. Listen in to hear about the impact of APOE4 on risk in Alzheimer’s disease, how long-read sequencing is uncovering hidden genetic variation in Alzheimer’s and ALS, and what rare variants and cryptic splicing can teach us about neurodegeneration. Available here👇 🎧 eu1.hubs.ly/H0vkJl50 📽️ eu1.hubs.ly/H0vkJxn0 #Genomics #Neurodegeneration #GeneTherapy

Case study: sponsors.sanogenetics.com/hubfs/content/…

When we talk about patient engagement as a cumulative asset, this is what it looks like in practice. 🧬 For a GBA1+ Parkinson's disease gene therapy trial, Sano ran two parallel recruitment streams: 1️⃣A digital patient-finding campaign to identify new participants meeting genetic and demographic criteria 2️⃣Targeted outreach to individuals already in Sano's database from previous Parkinson's programs Of the GBA1+ participants identified, 42% came from that existing database. These were patients who had engaged with a prior program, stayed connected, and were ready when a relevant new trial opened. The wider results: 📊 Kit volume exceeded initial targets by 94% ⚡ First participant scheduled screening on the same day as site activation ♻️ Program ended with a recontactable cohort available for the next phase This is what compounding engagement looks like. 🔗 Full case study in comments, no form required!

🎙️Tune in to Episode 238 of #TheGeneticsPodcast 🚀 This week, we’re joined by Dr. Bin Yu, Chancellor's Distinguished Professor at UC Berkeley. Listen in to hear why linear models may not tell the whole story in genetics, how a stability-driven random forest approach revealed novel epistatic interactions in cardiomyopathy, and why predictability, computability, and stability should guide how we do data science in biology. Available here👇 🎧 eu1.hubs.ly/H0v6mK00 📽️ eu1.hubs.ly/H0v6n3t0 #Biostatistics #Genetics #MachineLearning

💰 Precision medicine sponsors often rebuild patient recruitment from scratch with every new trial. This is one of the most expensive habits in drug development. Every program that ends without preserving its patient relationships, genomic data, and engagement infrastructure forces the next team to start over. New outreach. New education. New trust-building. The same costs are incurred again. Participants who complete one trial and have a positive experience are measurably more willing to join future studies. That willingness is an asset that many sponsors don’t take advantage of. A reusable, consented patient cohort reduces acquisition costs, shortens recruitment timelines, and supports natural history studies, label expansion, and post-approval research. Each interaction with a participant strengthens the dataset. The infrastructure built to run one precision trial can help drive the next three, if sponsors treat engagement as a cumulative investment rather than a per-study expense. 💡 What would change in your development strategy if every trial left behind a ready-to-activate patient cohort?

🎙️ In last week's episode of The Genetics Podcast, Dr. Sarah Marzi (Senior Lecturer at King’s College London, UKDRI) explains why Alzheimer’s and Parkinson’s sit at the intersection of genetics, environment, and cell state. Our recap blog covers key takeaways from the discussion, including: 🧠 The effect of environmental exposures like pesticides on Parkinson's risk 🧠 The role of microglia across neurodegenerative diseases 🧠 How APOE4 affects disease risk in Alzheimer's Learn more here: eu1.hubs.ly/H0t-NVL0

🧬 Precision trials should not start from zero every time. Sponsors invest heavily to identify, educate, screen, consent, genotype, and support rare patients. When that infrastructure disappears after a single study, future programs rebuild the same foundations again. In our latest article, we explore how lifecycle patient engagement can create a reusable data and relationship layer across trials, registries, long-term follow-up, and future development programs. The sponsors that treat engagement as long-term infrastructure will be better positioned to recruit, learn, recontact, and scale across their portfolios. 📖 Learn more by following the link in the comments below.