Biomarkers for Opioid Use Disorder (OUD)

Highland Instruments, Inc., Cambridge MA

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Abstract

Proprietary: This proposal includes trade secrets and other proprietary or confidential information of Highland Instruments and is being provided for use by the National Institutes of Health (NIH) for the sole purpose of evaluating this SBIR proposal. No other rights are conferred. This proposal and the trade secrets and other proprietary or confidential information contained herein shal further not be disclosed in whole or in parts, outside of NIH without Highland Instrument's permission. This restriction does not limit the NIH's right to use information contained in the data if it is obtained from another source without restriction. This legend applies to the Abstract, Specific Aims, Research Plan (al components), Commercialization Plan, and Human Subject's Sections of this proposal. Abstract The U.S. is suffering from a national opioid epidemic characterized by significant costs, overdoses, and deaths. OUD is diagnosed using qualitative criteria (i.e., clinical scales and questionnaires (e.g., DMSV criteria)), and toxicology screening with various degrees of testing accuracy. Biomarkers for OUD with diagnostic and prognostic value represent an unmet need that has been recognized by NIDA and the FDA. Conventional OUD treatments (i.e., pharmacological and psychosocial interventions) are characterized by limited or diminishing efficacy, ceiling effects, and/or serious side effects. The availability of validated OUD biomarkers would be a key step in the development and approval of better treatments. Ultimately, the scarcity of OUD biomarkers represents a significant unmet need in the fight against opioid addiction as recognized by NIDA and the FDA with their support for development of Medical Device Development Tools (MDDT) and biomarker tests for OUD. Advances in neuroimaging techniques, and in particular recent evidence supports electroencephalography (EEG) as a very promising candidate to investigate the correlation between addiction and brain state. Building on EEG data gathered during our OUD clinical study aimed at developing a new medical device for OUD treatment, we propose to explore the use of high-density electroencephalography (EEG) to identify candidate biomarkers for OUD for diagnosis, disease monitoring and prediction of OUD treatment response. We will enroll 50 OUD patients at various stages of treatment as well as 20 non-OUD healthy controls. For these subjects, we will gather current and historical drug use data, clinical data (including questionnaires on cravings and mood), and toxicology (hair, urine). Next, we will record high-density EEG at rest and during a Craving/Cue Exposure task. EEG analysis will focus on power analysis, scalp maps, and source reconstruction. We will extract a battery of EEG-based measures and assess whether they are able to differentiate between clinical characteristics of the patients such as stability of treatment, cue exposure craving response, polysubstance use, and duration of disease. Finally, we will repeat the analysis in our historical data from OUD patients undergoing brain stimulation to determine if the EEG-based measures are responsive to brain stimulation treatment. Ultimately this project will aim at developing candidate EEG biomarkers which could potentially be used for OUD diagnosis, disease and treatment monitoring, and prediction of treatment response.