Over the past few years, there has been a significant increase in the number of seizures and unintentional overdose fatalities related to illicit synthetic opioids in multiple states across the U.S. This NIH-funded project builds a system to monitor the emergence of new synthetic opioids in darknet markets or cryptomarkets. The proposed study is significant because it will provide new information about illicit synthetic opioids and will identify new illicit synthetic opioids as soon as they appear on those markets. The key innovation is the development of a semi-automated system able to a) collect and analyze advertisement data from cryptomarkets and b) identify new emerging substances advertised on these markets.
Dr Francois Lamy
Wright State University, Ohio, USA
Prof Amit Sheth
Wright State University, Ohio, USA
Prof Robert Carlson
Wright State University, Ohio, USA
Assoc/Prof Raminta Daniulaityte
Wright State University, Ohio, USA
Assoc/Prof Ramzi Nahhas
Wright State University, Ohio, USA
The study will collect and analyze data extracted from cryptomarkets to characterize illicit synthetic opioid marketing characteristics and trends in the U.S, and will identify new, emerging illicit synthetic opioid-related terms (e.g., substance names, product forms) as soon as they appear on these markets. It will be the first system to apply semi-automated computational techniques to monitor the supply of illicit synthetic opioids on cryptomarkets. The findings will inform public health interventions and policy responses.
The overall purposes of the proposed study are to (a) characterize illicit synthetic opioid marketing characteristics and trends, and (b) identify new, emerging illicit synthetic opioid terms (e.g., substance names, product forms) from three "cryptomarkets" located in the Deep Web. The Specific Aims of the study are to: 1) Develop a semi-automated knowledge-based system, eDarkTrends, to collect and process data about illicit synthetic opioids supplied on cryptomarkets; 2a) Describe and monitor US-based supply trends of illicit synthetic opioids on cryptomarkets (e.g., trends in availability of non-pharmaceutical fentanyl analogs, U-47700, MT-45), including types of illicit synthetic opioids, prices, advertised purity, dosage and product forms, quantity supplied, and drug combinations; 2b) Identify new illicit synthetic opioid substances and product forms soon after they appear on cryptomarkets.
Natural Language Processes and Data Mining techniques already developed by the team will be utilized in this project.
The project is in the start-up phase.
This study is highly significant because it will establish an advanced monitoring system able to: 1) identify new emerging illicit synthetic opioids soon after they appear on cryptomarkets; and 2) describe cryptomarket-based illicit synthetic opioid supply trends in the U.S in terms of types of illicit synthetic opioids, prices, advertised purity, dosage (e.g., 0.5mg), product forms, quantity available (e.g., 50 gel tabs), and drug combinations. The methods applied in this study will enhance early warning and illicit drug surveillance systems by enabling effective processing and analysis of cryptomarket data. In the future, this approach can be extended to other synthetic psychoactive drugs, besides the primary targets of this exploratory study and could be combined with drug-focused web-forums to extract information regarding their patterns of use and effects.