Unlearn.AI

Back from NEALS 2026 in Clearwater, and grateful for every conversation. 🌴 We connected with ALS researchers, clinicians, and sponsors about how digital twins can help small and early-phase studies deliver clearer, more trustworthy readouts. We also presented our poster, “𝗔𝗜-𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝘄𝗶𝗻𝘀 𝗮𝗻𝗱 𝗣𝗹𝗮𝘀𝗺𝗮 𝗡𝗳𝗟 𝗳𝗼𝗿 𝗧𝗿𝗶𝗮𝗹 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗶𝗻 𝗔𝗟𝗦,” which showed how digital twin adjustment took a trial designed at 50% power up to 72% on key endpoints. Our ALS model is trained on data from more than 13,600 people with ALS and forecasts outcomes on ALSFRS-R, vital capacity, and plasma NfL. Thank you to everyone who stopped by, and to our partners across the ALS community. Missed us? Explore more of our ALS work here: na2.hubs.ly/H08JWxn0 #NEALS2026 #ALS #DigitalTwins #ClinicalTrials #AI

📣 Big shoutout to our Clinical Data Scientist, Ann-Kathrin Schalkamp, who presented “AI-Powered Digital Twins: Applications and Opportunities in Clinical Trials” at the EHDN Plenary Meeting in Kraków last week. A participant’s digital twin is a forecast of how that person would progress on placebo, built from their baseline data alone. Added to a randomized trial as a pre-specified covariate, it makes the treatment effect easier to see, using a method EMA qualified in 2022 and FDA concurred with. Ann-Kathrin showed what that means for trial planning. She took 444 real participants the model had never seen during training, selected with the entry criteria today’s disease-modifying HD trials use, and checked the model’s two-year forecasts against what actually happened to them. Sized like a current trial, a study of those 444 people could run with 64 fewer on placebo at the same power. Or keep all 444 and cut the chance of missing a drug that works from one in five to one in eight. Our Huntington’s Digital Twin Generator was trained on clinical data from 25k+ trial participants across Enroll-HD, REGISTRY, TRACK-HD, PREDICT-HD and completed trials. None of it would exist without the people and families who contributed to those studies, and the teams who built them. Thank you to EHDN and the session chairs for the invitation, and to everyone who stayed for the panel. More on digital twins in Huntington’s disease: na2.hubs.ly/H08B2YS0 #EHDN2026 #HuntingtonsDisease #DigitalTwins #ClinicalTrials

Heading to #NEALS2026 in Clearwater? Come find us at Poster #212. We’ll be presenting “AI-Generated Digital Twins and Plasma NfL for Trial Planning and Statistical Efficiency in ALS,” including how pre-specified digital twin adjustment (PROCOVA) would take a study designed at 50% power to 67% on ALSFRS-R and 72% on SVC. 📍 Poster #212 🗓️ October 29, 4:50–6:30 PM ET Stop by, or reach out to find time to connect while we’re there. #ALS #DigitalTwins #ClinicalTrials

#UnlearnerSpotlight 🚀 “I love the freedom to propose new ideas and actually see them through, and I get to work alongside incredibly talented people who I learn from every day. Most of all, I like knowing my work helps speed up clinical trials and get treatments to patients faster.”

🎉 We’re excited to welcome Ian Fleming as Unlearn’s new VP of Product. Ian brings 25 years of experience in the life sciences industry. He started with hands-on statistical work on clinical programs, then moved into building the technology that clinical and biometrics teams rely on, most recently building a team that delivered foundational components of a major clinical data platform and its AI infrastructure. Welcome to the team, Ian!

📄 Our latest whitepaper, A Field Guide to Digital Twins in Clinical Development, walks through each decision point in a study, from eligibility criteria and sample size in design, to stopping rules at interim, to interpreting the result after readout, and shows how digital twins fit at every step. It also covers the methods behind each use and the deployment principles we follow, drawn from the @FDA's draft guidance on AI in drug development. Download the field guide: na2.hubs.ly/H08nFyK0 #ClinicalTrials #DigitalTwins #DrugDevelopment #Biostatistics #AI

🇵🇱 Heading to #EHDN2026 in Kraków, October 22–24? Catch our presentation, "AI-Powered Digital Twins: Applications and Opportunities in Clinical Trials." Huntington's disease progresses differently in every patient, which makes treatment effects hard to detect. A #digitaltwin for each participant helps: more power, a smaller control arm, and more participants on the investigational treatment. In planning one HD registrational study, digital twins reduced the required sample size by up to 29%. Connect with us in Kraków.

🚀 Big shout-out to our Principal Biostatistician, Run Zhuang, for presenting "Machine Learning Generated Digital Twins as External Controls” at the ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop. Run showed how AI-generated #digitaltwins serve as external controls in non-randomized #trials to improve efficiency and reduce bias to establish causal effects. Thank you to everyone who stopped by! #RISW2026

4️⃣ days out from our webinar: More Drugs, Faster: Can Clinical Development Keep Up? Dr. Jon Walsh (Unlearn), Dr. Tala Fakhouri (Parexel, formerly FDA/CDER), and Dr. Barbara Bierer (Harvard, MRCT Center) on what faster discovery demands of sponsors, regulators, and the people running trials. 📅 Monday, September 28, 11 AM PT / 2 PM ET. Can't attend live? Register and we'll send the recording. ➡️ Register: na2.hubs.ly/H07_k1z0

#UnlearnerSpotlight 🚀 “My favorite part about working at Unlearn is the ‘lightbulb moment’ when customers see how our offerings can improve their day-to-day work.”