Unlearn, an innovative AI-enabled company focused on creating digital twins of clinical trial participants, has recently announced a strategic partnership with Trace Neuroscience, a leading biotechnology company specializing in genomic therapies for neurodegenerative diseases, to advance research in the field of ALS (Amyotrophic Lateral Sclerosis).
Founded in 2017, Unlearn leverages machine learning technology to develop digital replicas of individuals participating in clinical trials before they are randomized into control groups. These digital twins offer valuable insights into the health outcomes of participants, enabling researchers to conduct smaller and faster clinical trials by reducing the number of individuals needed for the control group.
One of Unlearn’s key offerings is the Digital Twin Generator (DTG) specifically designed for ALS research. This machine learning model is trained on a vast dataset of over 13,000 longitudinal clinical records from prominent ALS research platforms such as APST, the PRO-ACT database, and the Northeast ALS Consortium (NEALS). The DTG ALS predicts how an individual may progress under standard care or in a placebo group, creating a personalized digital twin for each trial participant based on their data.
In this collaborative effort, Trace Neuroscience will utilize Unlearn’s DTG ALS and its advanced Unlearn Platform for their Phase 1/2 clinical trial targeting the UNC13A protein, a genetic marker directly linked to ALS progression. By simulating ALS disease progression and analyzing the relationship between clinical endpoints, baseline disease status, and biomarkers over time, Unlearn’s technology will play a crucial role in informing clinical trial protocol decisions and optimizing trial design for Trace Neuroscience.
Dr. Eric Green, the CEO of Trace Neuroscience, expressed his enthusiasm for the partnership, stating, “This collaboration brings together two powerful approaches—AI and genomic medicine—to rethink how ALS trials are designed. Working with Unlearn to mine their extensive, well-curated database through the use of the ALS DTG will enable us to explore smarter designs and make confident and informed decisions as we plan our Phase 1/2 trial. Ultimately, these insights can help us to move faster for people living with ALS who are waiting for new treatment options.”
Unlearn’s remarkable progress in the field of AI-enabled clinical research has been underscored by significant funding milestones. Last year, the company secured $50 million in Series C funding, bringing its total fundraising efforts to over $130 million. In a testament to its growing influence, Unlearn also partnered with German-based APST Research in December to integrate data from an extensive longitudinal study into its DTG ALS, further enhancing its capabilities in predicting disease progression.
Moreover, Unlearn has established partnerships with other biotechnology companies like ProJenX and QurAlis Corporation to accelerate ALS-focused clinical programs using its cutting-edge genAI technology. These collaborations underscore the growing recognition of Unlearn’s digital twin technology as a valuable tool for enhancing the efficiency and efficacy of clinical trials in the pursuit of novel treatments for neurodegenerative diseases like ALS.
In a broader context, the adoption of digital twin technology is gaining momentum across various industries, with companies like Mesh Bio and Twin Health exploring its applications in managing chronic diseases and providing personalized healthcare solutions. As Unlearn continues to drive innovation in AI-enabled clinical research, its partnerships and advancements in digital twin technology are poised to shape the future of precision medicine and therapeutic development for complex neurological conditions like ALS.
