Smart Capsule for Automatic Adherence Monitoring
Smart Capsule for Automatic Adherence Monitoring
批准号:
8792745
负责人:
Glen Flores
金额:
$55.6万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-03-01 至 2016-02-29
关键词:
AdherenceAdverse effectsBiocompatibleCellsClinicalClinical ResearchClinical TrialsComputer softwareCustomDataDatabasesDoseDrug InteractionsDrug abuseElectronicsEnvironmentEnvironmental MonitoringEnvironmental ProtectionGelatinHealthHealth Care CostsHealthcare SystemsIndividualIndustryLiquid substanceManualsManufacturer NameMarijuanaMeasurementMeasuresMechanical StressMedicalMethodologyMethodsMonitorOutcomeOutcome StudyPatient Self-ReportPatientsPerformancePharmaceutical PreparationsPhaseProcessProductionRandomizedReaderRecruitment ActivityReminder SystemsResearch DesignRiboflavinSafetyServicesSignal TransductionSmall Business Innovation Research GrantSouth CarolinaStomachSystemTechniquesTechnologyTest ResultTestingTimeUniversitiesWireless TechnologyWorkWristarmcapsulecostcost effectivedesigndiariesgroup interventionhigh riskimprovedlarge scale productionmanufacturing processmedical supplymedication compliancepillprototyperesponsesensorstability testingstandard measure
中文摘要
描述(由申请人提供):不良的服药依从性对患者、临床研究结果和总体医疗保健系统都有重大的负面影响。如果患者可靠地服用处方药,可以避免高达25%的医疗费用。在临床试验中,用药依从性尤其令人担忧。标准的依从性测量(药片计数和日记)是不准确的,而且仍然很昂贵,而可用的少数准确的依从性测量(例如,直接观察治疗)成本高昂,在后勤上难以在大型研究中实施。在以药物依从性差而臭名昭著的研究中,如药物滥用研究,不坚持将掩盖研究的真实结果,包括有效性、安全性、剂量反应和副作用,潜在地使研究
如果没有准确的用药依从性衡量标准,就毫无用处。这个快速跟踪SBIR项目将利用eTect的现有技术来创建Smart胶囊,为临床研究,特别是低依从性高风险的研究提供准确和实时的依从性监测。在第一阶段,我们将开发一种原型智能胶囊,方法是在插入00号胶囊的1号胶囊之间插入一个生物兼容的无线传感器或“标签”。在第二阶段,我们将开发一个定制系统,以生产大量可投入生产的智能胶囊。第二阶段还将包括一项60名患者的大麻依赖受试者试验,以评估智能胶囊系统的功能,将其整合到试验过程中的容易程度,以及改善对定向提醒系统的遵从性的可能性。第一阶段研究的具体目标是:1.修改现有的eTect ID-Cap标签,以在胶囊中(Cap-in-Cap)配置中获得最佳性能2.设计和制造智能胶囊原型3.在稳定性、溶出性、兼容性和环境测试中评估原型智能胶囊的性能。第二阶段研究的具体目标是:1.重新设计电子标签以支持大批量生产2.修改智能胶囊的制造工艺以生产大容量测试和临床试验用品3.评估智能胶囊在试点药物滥用临床试验中的表现
英文摘要
DESCRIPTION (provided by applicant): Poor medication adherence has a significant negative impact on patients, clinical study outcomes, and the healthcare system in general. As much as 25% of all healthcare costs could be avoided if patients reliably took their prescribed medications. Medication adherence is of particular concern in clinical trials. Standard measures of adherence (pill counting and diaries) are inaccurate and yet still costly, whereas the few available accurate measures of adherence (e.g. direct observed therapy) are cost prohibitive and logistically difficult to implement in large studies. In studies notorious for poor medication adherence, such as drug abuse studies, non-adherence will conceal the true outcomes of the study, including efficacy, safety, dose response, and side effects, potentially rendering the study
useless without accurate measures of medication adherence. This Fast-track SBIR project will utilize eTect's existing technology to create Smart Capsules that provide accurate and real-time adherence monitoring for clinical studies, particularly studies at high risk of low compliance. In Phase I we will develop a prototype Smart Capsule by inserting a biocompatible wireless sensor, or "tag", between a size 1 capsule inserted into a size 00 capsule. In Phase II we will develop a custom system for producing large quantities of production-ready Smart Capsules. Phase II will also include a 60 patient trial with marijuana-dependent subjects to evaluate the functionality of the Smart Capsule system, the ease by which it can be integrated into the trial processes, and it's potential to improve compliance with a targeted reminder system. The Specific Aims of the study in Phase I are to: 1. Modify the existing eTect ID-Cap Tag for optimum performance in 'capsule-in-a- capsule' (cap-in-cap) configuration 2. Design and manufacture prototype Smart Capsules 3. Evaluate the performance of prototype Smart Capsules in stability, dissolution, compatibility, and environmental tests. The Specific Aims of the study in Phase II are to: 1. Redesign the electronic tags to support high volume manufacture 2. Modify the Smart Capsule manufacturing processes to produce high volume supplies for testing and the clinical trial 3. Evaluate the Smart Capsule's performance in pilot drug abuse clinical trial
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Smart Capsule for Automatic Adherence Monitoring
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批准号:8811111
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项目类别:
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资助金额:$44.78万
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财政年份:2014
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负责人:Glen Flores
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依托单位:
Smart Capsule for Automatic Adherence Monitoring
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批准号:8592774
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项目类别:
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资助金额:$15.07万
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财政年份:2013
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负责人:Glen Flores
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依托单位:
海外基金