A novel robotic wastewater analysis system to quantify opioid exposure and treatment in residential communities
一种新型机器人废水分析系统,用于量化住宅社区中阿片类药物的暴露和处理
基本信息
- 批准号:10313450
- 负责人:
- 金额:$ 54.91万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-04-15 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdoptedAdoptionAlgorithmsAmericanBenchmarkingBiological MarkersBostonBuprenorphineCessation of lifeCitiesCodeCollaborationsCollectionCommunitiesDataData AnalyticsData SetData SourcesDeath RateDetectionDevelopmentDevicesDropsDrug ExposureDrug usageEnsureEpidemicFeedbackFentanylGeographyGoalsGoldGovernmentGovernment OfficialsGrantHeroinHigh Pressure Liquid ChromatographyHospitalsHourHumanIllicit DrugsInfrastructureInterventionMassachusettsMeasuresMedical emergencyMethadoneMethodsModelingModificationMorbidity - disease rateMunicipalitiesNaloxoneNaltrexoneNeighborhoodsNorth CarolinaOpioidOverdoseParentsPatternPharmaceutical PreparationsPhasePilot ProjectsPlantsPoliciesPopulationPublic HealthPublishingRainRecording of previous eventsReportingResolutionRoboticsSamplingSiteSmall Business Innovation Research GrantSufentanilSystemSystems AnalysisTechniquesTechnologyTestingTimeUnited StatesUpdateUrineVisualizationWeatherWomananalogbasedashboarddata analysis pipelinedata visualizationdesignfallshealth dataillicit opioidimprovedinnovationinsightinstrumentinterestmedical schoolsmodels and simulationnovelonline versionopioid abuseopioid epidemicopioid exposureopioid overdoseopioid useopioid use disorderoutreachoverdose deathprescription opioidresponsesample collectionsuccesstoolurinarywastewater samplingwastewater testing
项目摘要
Project Summary
This proposed Phase I/Phase II FastTrack SBIR project will lead to the demonstration of a
robust wastewater testing and analytics platform that government stakeholders can use to guide
localized actions to respond to the opioid epidemic. The opioid epidemic is the biggest drug
crisis in American history, resulting in over 130 deaths every day. Currently, stakeholders use
overdose death data to guide their opioid response strategies. However, this data is infrequently
updated, often aggregated at geographic levels which are too large to be actionable by public
health officials, and rarely provides insight into specific drug types (e.g. prescription vs. illicit
opioids, fentanyl, etc.). Novel data sources which provide localized, real-time, and drug-specific
insights are needed to inform response efforts in this rapidly changing epidemic.
Wastewater-based testing is a promising approach for measuring population-level drug
exposure, but has significant technical limitations before it can be useful to stakeholders on the
frontlines of the epidemic. Specifically, current wastewater testing approaches rely on sampling
at wastewater treatment plants, which yields city-level data at best. This represents a
heterogenous sample and is not useful to guide localized interventions.
Biobot is the first commercial wastewater testing technology designed and built to provide
actionable public health insights for municipal stakeholders tackling the opioid epidemic. Our
robotic wastewater analysis system measures opioid exposure and treatment (distinguishing
human use from discarding in the toilet), and operates at the neighborhood-level — the
geographic resolution relevant to municipal stakeholders. The premiere version of our platform
includes (1) an algorithm to select sampling sites (manholes) that represent residential
communities in a municipality; (2) a robotic sampling device that can be installed under sewer
access portals (e.g. manhole covers) to collect 24-hour composite samples; (3) a HPLC-MS/MS
method that detects a variety of urinary metabolites of prescription opioids, methadone,
buprenorphine, and naloxone; and (4) visualization in printed reports.
The goal of this Fast Track Phase I/Phase II application is to improve our platform to make it
adoptable in cities across the nation. In collaboration with leading toxicologists at Brigham and
Women’s Hospital and Harvard Medical School, we will address technological gaps to improve
data reliability and move from detection to consistent quantification of opioid exposure and
treatment. In Phase I, we will improve and expand our HPLC-MS/MS method, develop
simulation models to optimize sample collection, and address the variability challenge of
24-hour sampling. In Phase II, we will develop data correction methods to enable integration
with all existing sewer infrastructures, validate our data against reported overdoses in a pilot
study across six Massachusetts municipalities, and build a data analytics and visualization
platform for our end users.
Successful completion of the proposed project will lead to an optimized and validated
wastewater testing technology that provides accurate, spatially granular, and more real-time
data on opioid exposure and treatment. In parallel with the technological development, this grant
will allow us to demonstrate the value of our product to two key customers: the City of Boston
and the State of Massachusetts. These two government organizations are key champions to
pave the way for long-term adoption by our target customers.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Peter R Chai其他文献
Advising Around Cannabis for Sleep: Clearing Up the Smoke
关于大麻睡眠的建议:清除烟雾
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Stephanie Tung;Peter R Chai;M. Nayak;Ilana M Braun - 通讯作者:
Ilana M Braun
Peter R Chai的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Peter R Chai', 18)}}的其他基金
Ketamine for the treatment for opioid use disorder and suicidal ideation in the emergency department
氯胺酮用于治疗急诊科阿片类药物使用障碍和自杀意念
- 批准号:
10646993 - 财政年份:2023
- 资助金额:
$ 54.91万 - 项目类别:
A novel robotic wastewater analysis system to quantify opioid exposure and treatment in residential communities
一种新型机器人废水分析系统,用于量化住宅社区中阿片类药物的暴露和处理
- 批准号:
10549579 - 财政年份:2022
- 资助金额:
$ 54.91万 - 项目类别:
Ketamine for the treatment for alcohol use disorder in the emergency department: A pilot double-blind, placebo-controlled randomized clinical trial
氯胺酮在急诊科治疗酒精使用障碍:一项双盲、安慰剂对照随机临床试验
- 批准号:
10593244 - 财政年份:2022
- 资助金额:
$ 54.91万 - 项目类别:
Smart Steps: A context-aware adherence intervention to improve PrEP adherence among men who have sex with men (MSM) with substance use disorder
明智的步骤:情境感知的依从性干预措施可提高患有物质使用障碍的男男性行为者 (MSM) 的 PrEP 依从性
- 批准号:
10468388 - 财政年份:2022
- 资助金额:
$ 54.91万 - 项目类别:
Ketamine for the treatment for alcohol use disorder in the emergency department: A pilot double-blind, placebo-controlled randomized clinical trial
氯胺酮在急诊科治疗酒精使用障碍:一项试点双盲、安慰剂对照随机临床试验
- 批准号:
10703512 - 财政年份:2022
- 资助金额:
$ 54.91万 - 项目类别:
A novel robotic wastewater analysis system to quantify opioid exposure and treatment in residential communities
一种新型机器人废水分析系统,用于量化住宅社区中阿片类药物的暴露和处理
- 批准号:
10328984 - 财政年份:2020
- 资助金额:
$ 54.91万 - 项目类别:
A novel robotic wastewater analysis system to quantify opioid exposure and treatment in residential communities
一种新型机器人废水分析系统,用于量化住宅社区中阿片类药物的暴露和处理
- 批准号:
10381304 - 财政年份:2020
- 资助金额:
$ 54.91万 - 项目类别:
Development of Ingestible Biosensors to Enhance PrEP Adherence in Substance Users
开发可摄入生物传感器以增强药物使用者的 PrEP 依从性
- 批准号:
10401432 - 财政年份:2018
- 资助金额:
$ 54.91万 - 项目类别:
Development of Ingestible Biosensors to Enhance PrEP Adherence in Substance Users
开发可摄入生物传感器以增强药物使用者的 PrEP 依从性
- 批准号:
10674107 - 财政年份:2018
- 资助金额:
$ 54.91万 - 项目类别:
Development of Ingestible Biosensors to Enhance PrEP Adherence in Substance Users
开发可摄入生物传感器以增强药物使用者的 PrEP 依从性
- 批准号:
9924467 - 财政年份:2018
- 资助金额:
$ 54.91万 - 项目类别:
相似海外基金
How novices write code: discovering best practices and how they can be adopted
新手如何编写代码:发现最佳实践以及如何采用它们
- 批准号:
2315783 - 财政年份:2023
- 资助金额:
$ 54.91万 - 项目类别:
Standard Grant
One or Several Mothers: The Adopted Child as Critical and Clinical Subject
一位或多位母亲:收养的孩子作为关键和临床对象
- 批准号:
2719534 - 财政年份:2022
- 资助金额:
$ 54.91万 - 项目类别:
Studentship
A material investigation of the ceramic shards excavated from the Omuro Ninsei kiln site: Production techniques adopted by Nonomura Ninsei.
对大室仁清窑遗址出土的陶瓷碎片进行材质调查:野野村仁清采用的生产技术。
- 批准号:
20K01113 - 财政年份:2020
- 资助金额:
$ 54.91万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
A comparative study of disabled children and their adopted maternal figures in French and English Romantic Literature
英法浪漫主义文学中残疾儿童及其收养母亲形象的比较研究
- 批准号:
2633211 - 财政年份:2020
- 资助金额:
$ 54.91万 - 项目类别:
Studentship
A comparative study of disabled children and their adopted maternal figures in French and English Romantic Literature
英法浪漫主义文学中残疾儿童及其收养母亲形象的比较研究
- 批准号:
2436895 - 财政年份:2020
- 资助金额:
$ 54.91万 - 项目类别:
Studentship
A comparative study of disabled children and their adopted maternal figures in French and English Romantic Literature
英法浪漫主义文学中残疾儿童及其收养母亲形象的比较研究
- 批准号:
2633207 - 财政年份:2020
- 资助金额:
$ 54.91万 - 项目类别:
Studentship
A Study on Mutual Funds Adopted for Individual Defined Contribution Pension Plans
个人设定缴存养老金计划采用共同基金的研究
- 批准号:
19K01745 - 财政年份:2019
- 资助金额:
$ 54.91万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
The limits of development: State structural policy, comparing systems adopted in two European mountain regions (1945-1989)
发展的限制:国家结构政策,比较欧洲两个山区采用的制度(1945-1989)
- 批准号:
426559561 - 财政年份:2019
- 资助金额:
$ 54.91万 - 项目类别:
Research Grants
Securing a Sense of Safety for Adopted Children in Middle Childhood
确保被收养儿童的中期安全感
- 批准号:
2236701 - 财政年份:2019
- 资助金额:
$ 54.91万 - 项目类别:
Studentship
Structural and functional analyses of a bacterial protein translocation domain that has adopted diverse pathogenic effector functions within host cells
对宿主细胞内采用多种致病效应功能的细菌蛋白易位结构域进行结构和功能分析
- 批准号:
415543446 - 财政年份:2019
- 资助金额:
$ 54.91万 - 项目类别:
Research Fellowships














{{item.name}}会员




