At Unlearn, we’re committed to advancing AI to drive innovation in clinical research, particularly in the fight against amyotrophic lateral sclerosis (ALS). We’re thrilled to have recently announced a partnership with APST Research. Founded by renowned ALS Key Opinion Leader Prof. Thomas Meyer, APST is at the forefront of ALS observational studies. Prof. Meyer’s contributions to ALS research include his involvement in Biogen’s studies on tofersen,  the first FDA-approved drug for SOD1-associated ALS.

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This partnership positions us with one of the most robust and sophisticated ALS datasets in the world—a unique advantage in a field where few pharmaceutical companies have conducted large-scale ALS trials. APST’s longitudinal study captures clinical data, patient-reported outcomes, and biomarker analyses collected through regular follow-ups, ensuring exceptional scientific rigor. This includes assessments such as ALSFRS-R (ALS Functional Rating Scale-Revised), SVC (slow vital capacity), FVC (forced vital capacity), disease history, demographic information, and, notably, neurofilament light chain (NfL) measurements.

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NfL is a biomarker for neuron death and is highly prognostic in ALS. Its levels rise during early ALS onset and stabilize as the disease progresses, providing critical insight into disease progression. NfL has become a standard biomarker in early-stage ALS clinical trials, often serving as a primary endpoint in Phase 2 studies. Importantly, tofersen demonstrated that reducing NfL levels could indicate potential efficacy—a finding that underscores its value as both a clinical endpoint and a prognostic tool for patient decline.

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With this addition, our Digital Twin Generator (DTG) for ALS model will now incorporate over 18,000 patient records, significantly improving the accuracy of its forecasts for disease progression in ALS trial participants, which we call their digital twins. By leveraging this dataset, we can address critical open questions about how NfL variability impacts patient prognosis and its role in optimizing trial designs. This partnership further underscores our commitment to acquiring high-quality datasets for our cutting-edge ALS models, enabling smaller control arms and allowing more trial participants to access experimental treatments. 

The collaboration with APST is about creating meaningful impact for patients with ALS. Together, we will co-author research publications that demonstrate how integrating this dataset improves digital twin performance in clinical trials. Additionally, we’ll provide digital twins to APST to support their research initiatives and explore how this technology can help answer critical questions about ALS.

The fight against ALS is far from over, but partnerships like this bring us closer to breakthroughs that could change lives. At Unlearn, we remain dedicated to transforming clinical trials with AI and digital twins, one innovation at a time.