A novel robotic wastewater analysis system to quantify opioid exposure and treatment in residential communities

NIH RePORTER · NIH · R44 · $212,327 · view on reporter.nih.gov ↗

Abstract

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 dat...

Key facts

NIH application ID
9991436
Project number
1R44DA051106-01
Recipient
BIOBOT ANALYTICS, INC.
Principal Investigator
Peter R Chai
Activity code
R44
Funding institute
NIH
Fiscal year
2020
Award amount
$212,327
Award type
1
Project period
2020-04-15 → 2021-01-14