STUDY OBJECTIVES:To investigate the prescription patterns for hypnotics among patients <18 years in Japan. METHODS:We conducted a descriptive epidemiologic study using a claims database in Japan. We included patients aged 0-17 years with first-time prescriptions for hypnotics between June 2021 and June 2023. Hypnotics were classified as melatonin, melatonin receptor agonists (MRAs), dual orexin receptor antagonists (DORAs), Z-drugs, and benzodiazepines. We described the types of hypnotics, dosages, prescription duration, comorbidities, and concomitant medications for overall and by age groups. RESULTS:The study included 21 145 patients; 1983 aged 0-6 years, 3901 aged 7-11 years, 6664 aged 12-14 years, and 8597 aged 15-17 years. The initial prescribed hypnotics were melatonin (33.9%), MRAs (30.9%), DORAs (18.8%), Z-drugs (10.1%), and benzodiazepines (6.3%). Melatonin was more likely to be prescribed to patients age 0-11 years, MRAs to those aged 0-17 years, and DORAs to patients ages 15-17 years. The most common mental health-related comorbidities were autism spectrum disorder (32.5%), depression (23.4%), attention-deficit hyperactivity disorder (19.8%), and anxiety disorder (18.2%). CONCLUSIONS:Melatonin was most frequently prescribed in children for a longer duration than other hypnotics, while MRAs were prescribed across all age groups and DORAs mainly to adolescents. These age-specific patterns suggest that the drug selection was conducted according to patient's age, since pediatric insomnia might be correlated with psychiatric disorders related to developmental stage. Future research should investigate the long-term effects of hypnotic prescriptions with consideration of comorbid conditions.
[Background] Drug-induced convulsions represent a significant toxicological risk in drug development, requiring reliable biomarkers that can detect early signs of convulsive activity. We have experienced that our compound induced a convulsion in a clinical trial (”Compound X"; sodium channel blocker). For Compound X, we conducted an electroencephalogram (EEG) study in non-human primates (NHPs) but found no EEG abnormalities at dose levels lower than convulsive dose. Then, we co-developed a machine learning-based convulsion prediction model using heart rate variability (HRV) data from NHPs, trained on both convulsant and non-convulsant compounds (Kuga et al., 2024). This model calculates a “convulsive index" by identifying deviations in autonomic nervous system activity. Recently, we refined the model to reduce false positives caused by non-convulsant compounds that influence HRV. [Objectives] Here, we introduced an evaluation result of Compound X with the refined model and discussed the usefulness of our model for the preclinical convulsion assessment. [Methods] Telemetry-implanted male NHPs (n = 4) received oral doses of Compound X (0 [vehicle], 3, 10, and 30 mg/kg) in a Latin square design. Heart rate data were collected for approximately 6 h post-dose and analyzed using our refined model to calculate the convulsive index. For the 10 and 30 mg/kg doses, approaching convulsion-inducing levels in NHPs, retrospective toxicokinetic analysis was conducted to compare the Cmax in NHPs with the blood concentration at which convulsions occurred in humans. [Results] No convulsions were observed in any animal. However, the mean convulsive index increased in a dose-dependent manner. Apparently higher index values were observed in 1 animal at 10 mg/kg and 2 animals at 30 mg/kg (approximately 8-fold higher than the individual vehicle-treated values). The Cmax values in these 3 animals were close to the blood concentration at convulsion occurrence in humans (approximately 0.5 to 2 times that in humans). [Conclusions] These findings suggest that our HRV-based model can sensitively detect autonomic changes associated with convulsion risk prior to convulsion occurrence. The convulsive index may serve as a valuable preclinical biomarker, and future applications in human studies could support proactive safety assessments and the prevention of unexpected convulsions.
The dose escalation part of the first-in-human study of E7130 in patients with advanced solid tumors determined the Recommended Phase 2 Dose (RP2D) of E7130 (480 μg/m2 Q3W). The dose expansion part (presented here) examined safety/preliminary efficacy in patients with squamous cell carcinoma of the head and neck (SCCHN) and urothelial carcinoma (UC). Patients ≥ 20 years of age with previously treated SCCHN/UC were treated at the RP2D. The primary objective was to characterize tolerability/safety. Secondary objectives included preliminary efficacy (including objective response rate [ORR], progression-free survival [PFS], and duration of response [DOR] by investigator per Response Evaluation Criteria In Solid Tumors version 1.1 [RECIST v1.1] and overall survival [OS]). Treatment-emergent adverse events (TEAEs) were recorded. In patients with SCCHN, tissue biomarker analyses were performed. Kaplan-Meier method was used to estimate PFS, DOR, and OS. The Greenwood formula and log-log transformation were used to estimate 95% CIs. Eight patients (SCCHN, n = 2; UC, n = 6) were treated with the RP2D; 10 additional patients (SCCHN, n = 7; UC, n = 3) were treated at a reduced dose (410 μg/m2 Q3W). All patients had ≥ 1 TEAE; 66.7% had serious TEAEs. Patients with UC treated at the RP2D had an ORR of 66.7%; no other responses were observed. Median PFS/OS in patients with SCCHN treated at 480 μg/m2 were 2.8/7.7 months and at 410 μg/m2 were 3.5/5.0 months. Median PFS/OS in patients with UC treated at 480 μg/m2 were 6.6/10.7 months and at 410 μg/m2 were 2.6/11.9 months. Biomarker analyses indicated tumor microenvironment amelioration. Further evaluation is needed to optimize efficacy and safety of E7130 in patients with SCCHN and UC. Trial Registration: ClinicalTrials.gov identifier: NCT03444701.
Study Objectives This analysis was conducted to determine whether lemborexant (LEM) treatment affects ratings of patient-reported sleep quality and to identify subjective and objective parameters associated with improved subjective sleep quality. Methods This was a post hoc analysis of two global phase 3 trials (Study 303: 12-month, randomized, double-blind, placebo-controlled trial; Study 304: 1-month, randomized, double-blind, placebo-controlled, active-comparator trial) of LEM for patients with insomnia. A 9-point Likert scale (higher numbers indicating better quality) was used to assess subjective sleep quality (sQual). Subjective and objective sleep parameters were assessed by electronic sleep diaries and polysomnography, respectively. Spearman’s rank correlation analysis and stepwise regression analysis were performed to explore the associations between sleep parameters and sQual. Results The analyses included 949 patients from Study 303 and 743 patients from Study 304. LEM showed significantly larger increases from baseline in sQual than placebo in both studies (least square mean change: placebo 0.89, LEM5 1.17 (p<0.05); LEM10 1.21 (p<0.05) at Month 6 in Study 303, and placebo 0.93, LEM5 1.46 (p<0.001), LEM10 1.35 (p<0.05) at Month 1 in Study 304). Of subjective sleep parameters, changes in morning alertness showed the strongest association with changes in sQual. The changes in subjective total sleep time and wake after sleep onset were moderately correlated with sQual positively and negatively, respectively. These findings were further confirmed using stepwise regression analyses. Conclusions LEM improved ratings of sQual more than placebo. To improve self-reported sleep quality, lemborexant treatment should focus on improving morning alertness. Clinical Trial Registration Study 303 (ClinicalTrials.gov NCT02952820): Long-term Study of Lemborexant in Insomnia Disorder (SUNRISE 2). https://clinicaltrials.gov/study/NCT02952820, Study 304 (ClinicalTrials.gov NCT02783729): Study of the Efficacy and Safety of Lemborexant in Subjects 55 Years and Older with Insomnia Disorder (SUNRISE 1). https://clinicaltrials.gov/study/NCT02783729
