Biosensors for drug of abuse detection

Dashtian, Kheibar; Amourizi, Fereshteh; Shahbazi, Neda; Mousavi, Aida; Saboorizadeh, Bahar; Astaraei, Sana Safari; Zare‐Dorabei, Rouholah

doi:10.1016/b978-0-323-90222-9.00018-2

Cited by 8 publications

(6 citation statements)

References 200 publications

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“…These materials offer high selectivity and sensitivity, making them suitable for complex fluid environments. 15,16 Recently, metalorganic frameworks (MOFs) have gained significant attention due to their tunable structures, large surface area and ability for surface engineering. These characteristics make MOFs highly feasible for constructing sensing platforms tailored to specific applications.…”

Section: Introductionmentioning

confidence: 99%

Red-emissive carbon nanostructure-anchored molecularly imprinted Er-BTC MOF: a biosensor for visual anthrax monitoring

Dashtian¹,

Norouzi²,

Amourizi³

et al. 2023

Analyst

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Section: Introductionmentioning

confidence: 99%

Red-emissive carbon nanostructure-anchored molecularly imprinted Er-BTC MOF: a biosensor for visual anthrax monitoring

Dashtian¹,

Norouzi²,

Amourizi³

et al. 2023

Analyst

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“…Various nano-enabled optical biosensors have been employed to detect antibiotic abuse, comprising surface-enhanced Raman spectroscopy (SERS)-enabled sensors, fluorescence sensors and surface Plasmon resonance (SPR) sensors. 21,22 The fundamentals of these biosensors can be utilized and upgraded with innovative technologies to efficiently determine antibiotic abuse for combatting AMR.…”

Section: Towards Determining Antibiotic Abuse To Prevent Antimicrobia...mentioning

confidence: 99%

Perspective—Prospect of Nano-Enabled Optical Biosensors for Antibiotic Abuse Surveillance as an Early Prevention Tool for Antimicrobial Resistance

Chaudhary,

Rustagi,

Kaushik

et al. 2024

ECS J. Solid State Sci. Technol.

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Antimicrobial resistance (AMR) in humans is driven by pragmatic contagion diagnostics and incessant inadvertent antibiotics abuse (AB). The state-of-the-art AB monitoring involves developing nanomaterials-enabled optical biosensors with prompt and precise detection efficacy. This prospect highlights the diversified optical biosensors, including SPR, SERS, and fluorescent and colorimetric biosensors, for efficiently detecting AB. It also elaborates the fundamentals, challenges, potential alternatives, and prospects associated with these optical biosensing strategies for detecting AB as an effective AMR prevention/monitoring strategy. This will serve as a roadmap for future research and development dedicated to nano-enabled-optical biosensors for AMR monitoring through AB detection at community/individual sources.

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“…The deployment of biosensors in the field represents another key area of POC assessment that can significantly enhance environmental and public health monitoring. Drug-of-abuse testing is one area that has benefited greatly from in-field biosensing strategies [ 59 ]. For example, rapid testing kits for dangerous substances like fentanyl can increase safety for first responders and assist medical and other personnel in identifying hazardous substances [ 60 ].…”

Section: Sensing At the Point-of-carementioning

confidence: 99%

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities

Flynn,

Chang

2024

Diagnostics

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The integration of artificial intelligence (AI) into point-of-care (POC) biosensing has the potential to revolutionize diagnostic methodologies by offering rapid, accurate, and accessible health assessment directly at the patient level. This review paper explores the transformative impact of AI technologies on POC biosensing, emphasizing recent computational advancements, ongoing challenges, and future prospects in the field. We provide an overview of core biosensing technologies and their use at the POC, highlighting ongoing issues and challenges that may be solved with AI. We follow with an overview of AI methodologies that can be applied to biosensing, including machine learning algorithms, neural networks, and data processing frameworks that facilitate real-time analytical decision-making. We explore the applications of AI at each stage of the biosensor development process, highlighting the diverse opportunities beyond simple data analysis procedures. We include a thorough analysis of outstanding challenges in the field of AI-assisted biosensing, focusing on the technical and ethical challenges regarding the widespread adoption of these technologies, such as data security, algorithmic bias, and regulatory compliance. Through this review, we aim to emphasize the role of AI in advancing POC biosensing and inform researchers, clinicians, and policymakers about the potential of these technologies in reshaping global healthcare landscapes.

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Biosensors for drug of abuse detection

Cited by 8 publications

References 200 publications

Red-emissive carbon nanostructure-anchored molecularly imprinted Er-BTC MOF: a biosensor for visual anthrax monitoring

Red-emissive carbon nanostructure-anchored molecularly imprinted Er-BTC MOF: a biosensor for visual anthrax monitoring

Perspective—Prospect of Nano-Enabled Optical Biosensors for Antibiotic Abuse Surveillance as an Early Prevention Tool for Antimicrobial Resistance

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities

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