The ALS Association has announced the award of a grant made to Dr. David Ennist, Chief Science Officer at¬†Origent Data Sciences, Inc.¬† The $180,000 grant will fund a research project titled “Prospective Validation of an ALS Disease Progression Algorithm in the Clinic Setting.”

A neat description of ALS as a disease with average onset of about age 60, that is slightly more prevalent in men, and with an average survival of 3 to 5 years masks the true variability of a disease with a wide range of onset (age 17 to 95), and a broad rate of disease progression with large fractions of patients who succumb within 2 years of onset or survive greater than 7 years. Previous efforts to build disease patient-level predictive algorithms for ALS progression have relied on data collected from human clinical trials. One potential shortcoming of past efforts is the restriction of training data to patients who would typically qualify to participate in ALS human clinical trials. Those “qualifying” patients often are restricted to having disease onset within the last 2 years and ALSFRS-R scores above 26, and thus tend to be earlier in the disease than the majority of patients seen at ALS clinics. This new project seeks to develop a machine learning model that will provide individualized disease progression predictions for the majority of ALS patients, both those who choose and are selected to participate in clinical research trials as well as patients from the broader ALS clinic population.

To address this issue, Origent will first incorporate patient records from ALS treatment clinics into our existing suite of ALS models, then prospectively validate the use of these models for the general population of patients at multiple prominent ALS clinics in North America.

A full list of all grant awards can be found at the ALSA website.

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