Orlando, Florida – December 1st, 2023
Beacon Biosignals, a global leader in precision neuroscience, will showcase their pioneering work at the American Epilepsy Society (AES) 2023 conference, advancing the understanding and treatment of epilepsy and related conditions. In addition to their vibrant booth (#917), Beacon is delivering four impactful poster presentations, highlighting machine learning capabilities for detecting epileptiform activity and real-world evidence observations in genetic SCN2A-developmental and epileptic encephalopathy.
Characterizing neurological and psychiatric conditions at scale is encumbered by the logistical difficulty in acquiring electroencephalogram (EEG) data. Beacon tackles this challenge head-on with its AI-powered Dreem headband, now 510(k) cleared for computing sleep endpoints equivalent to traditional in-lab polysomnography (PSG). Beacon’s Dreem headband will be prominently displayed alongside their cutting edge EEG analytics platform in their inaugural booth.
Beacon’s algorithms are powered by an industry-leading real-world evidence database, enriched with detailed metadata and expert clinical annotations. The Clinico-EEG Database empowers biopharma partners to uniquely understand trial populations, de-risk inclusion/exclusion criteria, and prospectively identify treatment-responsive biosignal endpoints. As the world leader in machine learning-enabled EEG, PSG, and clinical outcome analysis, Beacon Biosignals is collaborating with biopharma companies, academic institutions and patient foundations to enhance our understanding of brain health.
AES 2023 Poster Presentation Highlights:
3.090: Unraveling EEG Spectral Abnormalities in SCN2A Developmental And Epileptic Encephalopathy:
· Key Finding: SCN2A-DEE disrupts the expected pattern of healthy EEG spectral development, with persistently elevated relative delta in subjects with Loss of Function variants.
3.091: Correlation Between Interictal Epileptiform Discharge Burden and Gross Motor Developmental Delay:
· Key Finding: Utilizing SpikeML™, Beacon Biosignals demonstrated a positive correlation between interictal epileptiform discharge burden and gross motor developmental delay in SCN2A subjects with Gain of Function variants.
3.171: SeizureML™ Matching Experts in Identifying Interictal Ictal Injury Continuum EEG Pattern:
· Key Finding: Introducing SeizureML™, a deep-learning model matching experts in characterizing interictal-ictal injury continuum (IIIC) EEG patterns, including classically ictal patterns, seizures or status epilepticus, as well as rhythmic, periodic, and sporadic patterns.
3.276: Association Between Anti-seizure Medication Burden and EEG Spectral Features:
· Key Finding: Higher anti-seizure medication (ASM) counts were associated with more severe encephalopathic EEG changes in SCN2A-DEE.
About Beacon Biosignals
Beacon's machine learning platform for EEG enables and accelerates new treatments that transform the lives of patients with neurological, psychiatric or sleep disorders. Through novel machine learning algorithms, EEG wearables, large Clinico-EEG RWE datasets, and advances in cloud-based scientific computing, Beacon Biosignals is changing the way patients are treated for disorders of the brain. For more information, visit https://beacon.bio/. To work together, visit https://beacon.bio/contact. Follow us on Twitter (@Biosignals) or LinkedIn (https://www.linkedin.com/company/beacon-biosignals).
For media inquiries, please contact Jacquelyn Miller (jacqui@avallonmiller.com), (617) 468-8243