Signal Detection for Prescription Opioid Outbreaks

Inflexxion, Inc., Newton MA

Investigators

Linked publications & trials

Abstract

[unreadable] DESCRIPTION (provided by applicant): This application builds on programmatic research conducted at Inflexxion regarding the Addiction Severity Index Multimedia Version (ASI-MV) and other funded SBIRs that have resulted in the creation of ASI-MV Connect. This is a national, public health syndromic surveillance network of substance abuse treatment centers around the country that allows the collection and aggregation of client-level data on substances of abuse, including product-specific data on use and abuse of pharmaceutical medications, especially opioid analgesics. ASI-MV Connect is capable of tracking and identifying "signals" that may reflect local outbreaks of abuse of monitored substances, including abusable pharmaceuticals. The aims of the present application are (1) to develop a website that presents validated and automated, temporal and geospatial signal detection of ASI-MV Connect data and (2) to make ongoing, real-time signal detection available to stakeholders, such as pharmaceutical companies, the FDA, as well as state and local public health and criminal justice authorities. No other existing or competitive post-marketing surveillance system of which we are aware utilizes state-of- the-art syndromic surveillance methods (such as systems that monitor infectious disease or bioterrorism threats) to search for local outbreaks of drug abuse across the country. Recent FDA requirements direct pharmaceutical companies making new applications for abusable or addictive substances to develop risk minimization action plans (called RiskMAPs), which typically include postmarketing surveillance programs. The public health import is further underscored by recommendations of the White House Office of National Drug Control Policy to develop an early warning and response system for drug outbreaks. The full commercial and public health potential of ASI-MV Connect requires (1) research to enhance the field's knowledge of which statistical techniques should be used with drug use data, (2) demonstration of how self-report data of drug use by clients in substance abuse treatment reflect abuse rates in local communities, and (3) an easy-to-use, web- based tool accessible to stakeholders that automatically tracks and reports signals of multiple drugs of interest in a real-time, ongoing manner. Phase I will (1) explore the relative efficiency of various temporal and geospatial methods of signal detection with ASI-MV Connect data, (2) conduct a feasibility field test to explore the relationship of ASI-MV Connect data to other sources of community level drug abuse data, and (3) develop and test sample website designs that present real-time signal detection information to stakeholder groups (e.g., pharmaceutical risk management personnel, public health authorities, criminal justice authorities). The result of this work will be publishable performance studies of various signal detection methods for drug abuse along with a website that will be a genuine public health tool and permit stakeholders real-time access to abuse rates and signals around the country. This system will be perceived as highly valuable to pharmaceutical companies, the DEA, the FDA and other public health officials. PUBLIC HEALTH RELEVANCE: Many of the pharmaceutical companies with which we have worked, are extremely interested in Inflexxion's services in the risk management area. For companies in the opioid pain management area, a strong postmarketing surveillance program with state-of-the-art signal detection capabilities is essential to obtaining approval by regulatory agencies. Such a tool makes available to those focused on substance abuse surveillance and signal detection, data similar to what is available to health authorities that monitor infectious disease and bioterrorism threats. This system should be perceived by stakeholders as highly valuable. Thus, we believe this product has enormous commercial viability and public health importance. [unreadable] [unreadable] [unreadable] [unreadable]