ArticleACS applied materials & interfaces2023
Smart Multiplex Point-of-Care Platform for Simultaneous Drug Monitoring.
Article in ACS applied materials & interfaces, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 37 citations in OpenAlex.
- Trends in ready-to-use portable electrochemical sensing devices for healthcare diagnosis.Mikrochimica acta · 2025Review
- AI-Reinforced Wearable Sensors and Intelligent Point-of-Care Tests.Journal of personalized medicine · 2024Review
- The Evolution of Illicit-Drug Detection: From Conventional Approaches to Cutting-Edge Immunosensors-A Comprehensive Review.Biosensors · 2024Review
- Recent reports on the sensing strategy and the On-site detection of illegal drugs.RSC advances · 2024Review
- Nanomaterial-based Electrochemical Sensors for Multiplex Medicinal Applications.Current topics in medicinal chemistry · 2024Review
- Advancements in magnetic nanoparticle-based biosensors for point-of-care testing.Frontiers in bioengineering and biotechnology · 2024Review
- Sensors in the Detection of Abused Substances in Forensic Contexts: A Comprehensive Review.Micromachines · 2023Review
- Progress on Electrochemical Sensing of Pharmaceutical Drugs in Complex Biofluids.Chemosensors (Basel, Switzerland) · 2023Article
- Recent findings and advancements in the detection of designer benzodiazepines: a brief review.Arhiv za higijenu rada i toksikologiju · 2022Review
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, illicit drug use has become more widespread and is linked to problems with crime and public health. These drugs disrupt consciousness, affecting perceptions and feelings. Combining stimulants and depressants to suppress the effect of drugs has become the most common reason for drug overdose deaths. On-site platforms for illicit-drug detection have gained an important role in dealing, without any excess equipment, long process, and training, with drug abuse and drug trafficking. Consequently, the development of rapid, sensitive, noninvasive, and reliable multiplex drug-detecting platforms has become a major necessity. In this study, a multiplex laser-scribed graphene (LSG) sensing platform with one counter, one reference, and three working electrodes was developed for rapid and sensitive electrochemical detection of amphetamine (AMP), cocaine (COC), and benzodiazepine (BZD) simultaneously in saliva samples. The multidetection sensing system was combined with a custom-made potentiostat to achieve a complete point-of-care (POC) platform. Smartphone integration was achieved by a customized application to operate, display, and send data. To the best of our knowledge, this is the first multiplex LSG-based electrochemical platform designed for illicit-drug detection with a custom-made potentiostat device to build a complete POC platform. Each working electrode was optimized with standard solutions of AMP, COC, and BZD in the concentration range of 1.0 pg/mL-500 ng/mL. The detection limit of each illicit drug was calculated as 4.3 ng/mL for AMP, 9.7 ng/mL for BZD, and 9.0 ng/mL for COC. Healthy and MET (methamphetamine) patient saliva samples were used for the clinical study. The multiplex LSG sensor was able to detect target analytes in real saliva samples successfully. This multiplex detection device serves the role of a practical and affordable alternative to conventional drug-detection methods by combining multiple drug detections in one portable platform.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.