Although the majority of ALS patients survive only 2-5 years after diagnosis, the rate of disease progression varies significantly. This heterogeneity poses a major challenge for clinical trial design, since large cohorts of ALS patients are required to detect significant treatment effects. In the Nov 2 Nature Biotechnology, a team of researchers led by Prize4Life and the Dialogue for Reverse Engineering Assessments and Methods (DREAM) published results of a crowdsourcing project, which leveraged the PRO-ACT ALS clinical trials database to identify algorithms capable of predicting an individual’s ALS disease progression based on their short-term clinical data. The algorithms outperformed predictions by ALS clinicians, and are estimated to enable a 20% reduction in the number of patients required for future ALS clinical trials.
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