PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
December 8, 2025ACS Sensors10 citations

From Lab to Body: Advanced Electrochemical Biosensors for Illicit Drug Detection via Nanomaterials, AI, and Wearable Tech

View Full Paper
MGM. GanesanCWChih-Lung Wang

Key Points

  • Illicit drug detection improves through the use of nanomaterials, elevating the capability of electrochemical biosensors.
  • Detection of opioids and cannabinoids is enhanced by integrating artificial intelligence analytics within wearable technology.
  • Assessment focuses on overcoming signal interference and fouling in drug sensing to ensure reliable real-time monitoring.
  • The findings suggest a shift towards decentralized drug monitoring, achieved through innovative biosensor technologies, promoting public health surveillance.

Abstract

Illicit drug detection is entering a transformative era, driven by the convergence of electrochemical sensing, nanomaterials engineering, and artificial intelligence. Traditional analytical approaches, despite their precision, are increasingly misaligned with the demands of real-time, on-site, and personalized monitoring. In recent years, electrochemical biosensors have emerged as a disruptive class of technologies capable of bridging this gap, offering miniaturized platforms that combine molecular specificity, rapid response, and adaptability to diverse biological matrices. This review captures the current momentum in the development of advanced electrochemical systems tailored for the detection of psychoactive substances, with a particular focus on opioids, stimulants, cannabinoids, and date rape drugs. We highlight how the integration of high-surface-area nanomaterials (e.g., MXenes, carbon nanostructures, metal organic frameworks) and programmable biorecognition interfaces (e.g., aptamers, synthetic polymers) has redefined the sensitivity, selectivity, and stability of drug sensors. Beyond material innovation, we explore how modern transduction strategies are being repurposed into flexible, wearable formats and seamlessly coupled with AI-driven data analytics to enable intelligent, autonomous sensing. Key technical challenges, including signal interference, fouling, multianalyte discrimination, and regulatory translation, are critically assessed alongside emerging solutions such as antifouling coatings, multiplexed recognition chemistries, and artificial intelligence (AI)-assisted calibration. Looking ahead, we outline a paradigm shift toward decentralized, user-adaptable drug sensing platforms that could radically improve forensic readiness, clinical toxicology, and public health surveillance. The path forward lies in translating these innovations into robust, field-deployable devices capable of meeting the complex demands of modern drug monitoring ecosystems.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ganesan et al. (2025) studied this question.

synapsesocial.com/papers/693624ba4fa91c937236c83ehttps://doi.org/10.1021/acssensors.5c02479
Ask AI
Helpful
Bookmark
Share
View Full Paper