At the heart of this collaboration is the integration of the digital twin generator developed by Unlearn into ALS studies and tests. The digital twin is not a robot or a 3D body reproduction, but a set of data designed to reflect the characteristics of each human organism as accurately as possible. Trained on more than 13,000 clinical records from numerous databases, this artificial intelligence model enables the rigorous simulation of disease progression in each patient, while assessing the complex interactions between initial health status, biomarkers and therapeutic responses. The contribution of Unlearn's technology to ALS testing is twofold: on the one hand, it enhances the statistical power of trials by generating virtual control groups, thus reducing the need for volunteers, which amounts to at least 3,000 people for the latest phase of clinical testing. Secondly, it refines protocol design decisions - inclusion criteria, study duration - with a degree of precision unheard of in the industry.
"Collaborating with Unlearn to exploit their vast, rich and rigorously structured database [...] will enable us to consider smarter protocols and make informed and confident decisions in preparing for the first stage of testing. Ultimately, these analyses could enable us to advance more rapidly in the development of new therapeutic treatments for people with ALS" confided Dr. Eric Green, co-founder and CEO of Trace Neuroscience.
This partnership is a further demonstration of the relevance of digital twins in the healthcare sector, where AI is playing an increasingly important role. Founded in 2017 and valued at $265M, Unlearn is taking advantage of this collaboration to highlight the robustness of its platform and accelerate its deployment in new therapeutic areas, beyond ALS(Parkinson's, Alzheimer's, ...). By combining predictive AI with high-quality biomedical data, Unlearn is redefining the way innovative therapies can be tested and validated.
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