Abstract
Conventional diagnostic platforms often lack point-of-care, simple, economical, prompt and personalized detection features, whereas nanomaterial-supported intelligent biosensors belonging to the 5th/6th generation are vital vectors in medical diagnostics. The tunable and enhanced physicochemical properties of nanomaterials such as surface area, surface chemistry, band gap, and flexibility, nano-biosensors exhibit high sensitivity, specificity, and prompt and accurate detection. Despite substantial research and an exponentially growing market, projected to reach $46.4 billion by 2028, biosensors face considerable challenges in clinical implementation. This article underlines the manifold translational challenges, such as regulatory barriers, safety and toxicity concerns related to nanomaterials, technical and manufacturing issues, hesitancy in adopting new tools, and economic constraints. Besides discussing the perspectives of material scientists, medical doctors, data scientists, and public health professionals, this article presents a comprehensive overview of the current state and prospects of integrating next-generation nanomaterial-based artificial intelligence-supported biosensors into clinical practice. It emphasizes the need to address these barriers, which can enhance early disease detection, improve patient outcomes, and reduce the overall burden on healthcare systems. Their applications can be extended to one health management team with dedicated collaborations to achieve sustainable development goals.
| Original language | English |
|---|---|
| Article number | 041602 |
| Journal | ECS Sensors Plus |
| Volume | 3 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2 Dec 2024 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 17 Partnerships for the Goals
Keywords
- artificial intelligence
- biosensors
- diagnosis
- nanomaterials
- sustainability
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