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The purpose of the research is to determine if changes seen during sulforaphane treatment (a compound that comes from eating certain vegetables) can better be understood using digital biomarkers. These digital biomarkers are things like heart rate, muscle movement etc. and are measured using non-invasive devices (like a watch) and are aimed at complementing the traditional clinical scores already in use in current trials (e.g. Aberrant Behavior Checklist (ABC), Social Responsiveness Scale (SRS) and Ohio Autism Clinical Impressions Scale (OACIS)).
Full description
This study is a pilot open label treatment trial with SF (sulforaphane) in 10 individuals that have completed with moderate to severe autism, age 13-30 years that have completed participation in ClinicalTrials.gov Identifier: NCT02677051. This study will measure digital biomarkers of the nervous systems. Digital biomarkers are obtained by using non-invasive wireless (wearable, like wearing a watch) biosensors that co-register in tandem multiple biorhythms self-generated by the person's nervous systems. These sensors gather a very large amount of data from measures such as EEG (electroencephalogram), EKG (electrocardiogram), kinematics and others. These measures are done at the same time as the clinical evaluations and so results can be compared. Because the data are based on the unique fingerprint-like signatures of the person's nervous systems, it is possible to ascertain the person's progression in response to treatment and compare it to baseline states. The project will also compare these self-emerging clusters between subjects, possibly identifying patterns that correlate with sub-phenotypes or with similarities in response to treatment. Changes in things such as natural behaviors, an individual's ability or desire to interact socially and ability or desire to communicate will alter the signature profiles from baseline. Since these changes are dynamic in nature, trends of the evolving patterns and separate changes that are a consequence of the treatment vs. changes that are part of the natural neurodevelopment can be detected. This may be a valuable tool in future studies of underlying etiology. The technology used to perform these measures and the software to analyze the data are evolving rapidly. Last, with the characterized signatures and possibly overlapping patterns generated in this and in other projects it is foreseeable that a clinically relevant tool for measures in autism will follow.
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10 participants in 1 patient group
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Central trial contact
Elizabeth B Torres, PhD; Edward S Stenroos
Data sourced from clinicaltrials.gov
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