Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Tackling the Opioids Overdose Epidemic: Methods of Detection of Fentanyl, its Analogues, and Metabolites

Silva Ferreira, Rodrigo (2024) Tackling the Opioids Overdose Epidemic: Methods of Detection of Fentanyl, its Analogues, and Metabolites. Master's Thesis, University of Pittsburgh. (Unpublished)

This is the latest version of this item.

Download (3MB) | Preview


With an average of 195 daily deaths due to synthetic opioids overdose in 2021, the US have been facing an unprecedented opioids crisis. Fentanyl and its analogues have been a major source of concern, due to their high levels of addiction, fast-acting mechanisms, and detection challenges. Fast, effective, and accurate identification and quantification of fentanyl, its analogues, and metabolites (hereinafter collectively abbreviated as FAMs) in blood and urine are essential to help prevent overdose-related incidents and to enable agile medical response. Nevertheless, further understanding of analytical techniques used for separation and detection of fentanyl and its analogues is crucial, as it would allow for the development of more sophisticated and portable devices. Additionally, with the emergence of new analogues as fentanyl “designer” drugs (FDDs), the demand for novel detection methods is pressing. This thesis seeks to provide a comprehensive review of the US opioids crisis, with a focus on the different analytical techniques used for the separation and detection of FAMs. While traditional, well-established techniques, such as gas and liquid chromatography, are extremely relevant to understand and explore, this review also seeks to bring attention to novel techniques that rely on electrochemical-based detection. The recent emergence of electrochemical biosensors for drug detection applications could help establish new paradigms in terms of public health policy response to the US opioids crisis, as such devices could have major impacts in curbing and preventing the rise of fentanyl and analogues-related overdoses. This review explores electrochemical sensing as a viable detection method. Relying on recent discoveries, it shows how cyclic voltammetry, differential pulse voltammetry, chronoamperometry, or field-effect transistors could be used to detect fentanyl and its analogues. The challenges concerning sensitivity and selectivity are explored by understanding how carbon nanotubes (CNTs) could be used to selectively enhance electrochemical responses. Although there are some challenges with collecting, using, and interpreting electrochemical data from biological samples, recent advancements in the fields of statistical process control, machine learning, and predictive analytics could help pave the way towards rapid large-scale development of reliable, accurate, and fast electrochemical sensors capable of identifying and determining concentrations of FAMs.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Silva Ferreira, Rodrigoros114@pitt.eduros114
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorStar, Alexanderastar@pitt.eduastar
Committee MemberAmemiya, Shigeruamemiya@pitt.eduamemiya
Committee MemberLiu, Haitaohliu@pitt.eduhliu
Date: 13 May 2024
Date Type: Publication
Defense Date: 1 April 2024
Approval Date: 13 May 2024
Submission Date: 31 March 2024
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 145
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Chemistry
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: fentanyl, electrochemistry, opioids, detection, drugs
Date Deposited: 13 May 2024 13:57
Last Modified: 13 May 2024 13:57

Available Versions of this Item

  • Tackling the Opioids Overdose Epidemic: Methods of Detection of Fentanyl, its Analogues, and Metabolites. (deposited 13 May 2024 13:57) [Currently Displayed]


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item