Innovations In Clinical Neuroscience

CNS Summit 2016

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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Innovations in CLINICAL NEUROSCIENCE [ V O L U M E 1 4 , N U M B E R 1 – 2 , J A N U A R Y – F E B R U A R Y 2 0 1 7 , S U P P L E M E N T ] S12 fasting lipid profiles and BPRS scores. Results indicated an inverse relationship between the low density lipoprotein ( LDL) and BPRS total score (r= -0.169, p=0.01). This suggests individuals with low LDL levels have higher BPRS total scores. Results also indicated an inverse relationship between the total c holesterol and BPRS total score (r= - 0.133, p=0.044). This suggests individuals with low total cholesterol levels have higher BPRS scores at screening. Correlations between lipid profiles and individual positive items were non-significant. Conclusion: The results of this analysis indicate that cholesterol levels are negatively related to BPRS total scores at screening. This association may be clinically substantial; however, it does not prove causality. It has been suggested that a reduced level of serum total cholesterol and LDL may be associated with increased aggression and overall symptoms of schizophrenia. These results may be relevant to clinical trials in that while it is standard to screen for high cholesterol, there could be a potential benefit in analyzing the LDL levels to assess the relationship to intrusive symptoms. Lipid profiles could potentially become an important biomarker to consider in the future. Disclosures/funding: None reported. MOBILE TECHNOLOGY Clinical trial of Clickotine ® , a Digital Therapeutics ™ solution for smoking cessation: design and total health execution methodology Presenters: Steinerman J 1 , Klein D 1 , Silver T 1 , Berger A 1 , Luo S 1 , Schork N 1 Affiliations: 1 Click Therapeutics, New York, New York Objective: The objective of this review was to describe the efficient and effective execution of a clinical trial of a digital therapeutic for smoking cessation. Design: Clickotine is a mobile health solution for smoking cessation that combines evidence-based behavioral interventions with a unique engagement strategy that leverages personalization and contextualization. The potential utility of Clickotine was assessed in an open-label, eight-week study that focused on user-engagement, safety, tolerability, and smoking behavior e fficacy. Key entry criteria included age 18 to 65 years, smoking five or more cigarettes per day, an interest in quitting smoking, ownership of an iPhone, living in the United States, and providing i nformed consent. The study employed remote telehealth interactions only. Designated sponsor representatives interacted directly with participants, while medical and scientific team members monitored and analyzed de- identified data. Participants were recruited via social media and a pre- screening telephone call. Informed consent and study questionnaires were delivered via an internet portal, complementing in-app data capture. Procedures for medical monitoring and biochemical verification of smoking cessation were in place throughout the study, which was institutional review board approved. Results: After 63 days of social media recruitment, 2,050 contacts were received and 617 telephone pre-screens were conducted, resulting in 452 participants providing online informed consent. Participants totaling 416 ultimately made up an intention-to-treat population broadly representative of United States smokers who want to quit. Baseline characteristics and details of telehealth trial execution were presented. Conclusion: Digital health enterprises can execute high-quality clinical trials by implementing social media recruitment, digital data capture, and remote interactions, while sparing resources and prioritizing participant convenience. Disclosures/funding: This study was funded by Click Therapeutics, New York, New York. JS is a consultant and shareholder of Click Therapeutics and an employee and shareholder of Teva Pharmaceuticals, Malvern, Pennsylvania. DK is an officer and shareholder of Click Therapeutics. TS is an officer and shareholder of Click Therapeutics. AB is an employee and shareholder of Click Therapeutics. SL is a consultant of Click Therapeutics. NS is an officer and shareholder of Click Therapeutics. Evaluating the use of an artificial intelligence platform on mobile devices to measure adherence in subjects with a n acute exacerbation of schizophrenia Presenters: Shafner L 1 , McCue M 2 , Rubin A 2 , Dong X 2 , Hanson E 2 , Mahableshwarkar A 2 , Hanina A 1 , Macek T 2 Affiliations: 1 AiCure, New York, New Y ork; 2 Takeda Development Center Americas, Inc., Deerfield, Illinois Objective: The need to minimize medication nonadherence is particularly important in central nervous system (CNS) clinical trials. An artificial intelligence (AI) platform was assessed in measuring and increasing medication adherence in subjects with schizophrenia in a Phase 2, randomized, double-blind study. Design: Subjects in the TAK-063 study who were stable after three or more weeks of inpatient treatment and were discharged were followed up as outpatients for the remainder of the six-week period. Subjects were given devices with the AI application downloaded and asked to use the application for dosing administrations. The primary adherence measure for the study was based on scheduled pill counts; AI platform adherence data were tested for exploratory purposes. Results: The AI platform was used by 26 subjects for 372 subject days; 744 adherence parameters were collected. Five subjects discontinued early (19.2%). For subjects who completed the trial, mean (standard deviation [SD]) cumulative adherence rates based on visual confirmation of drug ingestion (AI application) and on pill count were 82.5 percent and 99.7 percent, respectively. The mean time to use the AI platform was 86.8 seconds per pill. Conclusion: Subjects with acutely exacerbated schizophrenia who were eligible for discharge from the inpatient setting and who completed the study demonstrated high rates of adherence using the mobile AI application. Subjects were able to easily use the technology. Use of the platform did not appear to increase the dropout rate. This study demonstrates the feasibility of using AI platforms to ensure high adherence, provide reliable adherence data, and rapidly detect nonadherence in CNS trials. Disclosures/funding: Adam Hanina and Laura Shafner are employees of AiCure,

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