Innovations In Clinical Neuroscience

CNS Summit 2016

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

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[ 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 ] Innovations in CLINICAL NEUROSCIENCE S19 Disclosures/funding: All authors are full-time employees of Worldwide Clinical Trials, King of Prussia, Pennsylvania, and h ave no conflicts of interest. TRIAL METHODOLOGY/ STUDY PROTOCOL C ould a paradigm shift in consumptive disorders research benefit patients and sponsors alike? A smoking cessation case study reinforces "the manner in which we look at things determines what we see!" Presenters: Wilcox C 1 , Oskooilar N 2 , Morrissey J 3 , Rosenberg D 2 , Tong M 1 Henry M 2 , Badgett L 3 , Grosz D 3 Affiliations: 1 Pharmacology Research Institute [PRI] Newport Beach, California; 2 PRI Los Alamitos, California; 2 PRI Encino, California Objective: Our objective was to investigate the potential benefit of re- analyzing data (i.e., "changing the paradigm") currently used for "Go vs. No- go" clinical development decisions. Rationale: The evaluation of potential new medicines for nearly all central nervous system (CNS) indications focuses on symptom severity reduction (usually ≥50%), not total elimination. The current regulatory threshold for successful efficacy in smoking cessation is a total (100%) and sustained elimination. This is an arbitrarily high bar. Additionally, we question how many efficacious smoking cessation treatments may have fallen victim to Type II errors using these criteria. Design: We conducted a randomized, double-blind, 12-week, placebo-controlled, dose selection study. Seventy-five smokers were screened and 59 were randomly assigned to one of three treatment groups: lorcaserin 10mg once daily, lorcaserin 10mg twice daily, or placebo in a 3:3:2 ratio. The primary efficacy endpoint was the end-expiratory carbon monoxide (CO)- confirmed continuous abstinence rate (CAR) from Study Weeks 9 to 12, defined as zero reported smoking via Nicotine Use Inventory (NUI) with exhaled CO measurement 10ppm or less. Results: None of our initial results demonstrated any statistically significant findings. Analyses based on revised success criteria produced highly significant results. Using either NUI=0 or CO≤10ppm, high-dose lorcaserin demonstrated significantly better efficacy when compared to placebo (p<0.02) and low d ose lorcaserin (p<0.005). When we looked at harm/risk reduction, defined by NUI values of 5 or less and a CO value of 10ppm or less, hereto lorcaserin 20mg was significantly more efficacious than p lacebo (p<0.02) and low-dose lorcaserin (p<0.01). Conclusion: "Don't let the perfect be the enemy of the good" (Voltaire, 1694–1778). Although lorcaserin 10mg once daily and twice daily did not demonstrate statistically significant results via pre-specified protocol criteria of 100-percent sustained cessation, a different conceptual and statistical lens produced quite robust results. When re-analyzed utilizing our harm reduction criteria, high-dose lorcaserin was statistically significantly superior to both placebo and low-dose lorcaserin at multiple time points, including Endpoint/Week 12. High-dose lorcaserin appears to have clinical and commercial potential as an efficacious smoking cessation agent. We believe it warrants further investigation, with or without a paradigm shift in the definition of successful treatment. Disclosures/funding: The authors have no conflicts of interest relevant to the study. Funding for this retrospective analysis was provided internally by Pharmacology Research Institute. Discrepancies between CGI-S score and PANSS item level scores—an exploratory analysis Presenters: Kott A, Daniel D, Affiliations: Bracket Global, Wayne, Pennsylvania Objectives: The objective of this study was to identify and characterize factors associated with discrepancies in the rating of the Clinical Global Impression-Severity (CGI-S) scale versus the Positive and Negative Syndrome Scale (PANSS) in a large database of schizophrenia clinical trials rating data. Design: We retrospectively analyzed 67,698 subject visits from 15 multicenter, double-blind, placebo-controlled schizophrenia trials. CGI-S versus PANSS item level discrepancies were operationally defined as ratings where CGI-S score was at least three points below the highest individual PANSS item score. Using univariate logistic regression models, we assessed the effect of overall and i ndividual symptom severity, PANSS total versus CGI-S discrepancy, region, study type, visit type, and changes in raters on the presence of the discrepancies. Results: In this database, the p revalence of CGI-S versus PANSS item level discrepancies was 1.33 percent (904/67,698). Visit type, study type, and region had significant effects on the presence of item discrepancies. Increased item severity and different raters significantly increased the odds of PANSS item CGI-S discrepancies, while the odds significantly decreased with increasing overall severity. Conclusion: We found a prevalence of more than one percent of PANSS item level versus CGI-S discrepancies. In their majority, these discrepancies were distinctly different from PANSS total score versus CGI-S discrepancies. We identified multiple factors significantly impacting on the presence of these item level discrepancies. We conclude that algorithms assessing possible PANSS-CGI discrepancies should consider individual item severity in addition to total scores. Further research is necessary to replicate and understand better the findings. Disclosures/funding: Both authors are full time employees of Bracket. Evaluating the use of an artificial intelligence platform on mobile devices to measure adherence in subjects with an 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 York; 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

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