Yadav A K, Verma D, Kumar A, Kumar P, Solanki P R
Special Center for Nanoscience, Jawaharlal Nehru University, New Delhi, 110067, India.
Amity Institute of Applied Sciences, Amity University, Noida, Uttar Pradesh, 201301, India.
Mater Today Chem. 2021 Jun;20:100443. doi: 10.1016/j.mtchem.2021.100443. Epub 2021 Feb 11.
The World Health Organization (WHO) has declared the COVID-19 an international health emergency due to the severity of infection progression, which became more severe due to its continuous spread globally and the unavailability of appropriate therapy and diagnostics systems. Thus, there is a need for efficient devices to detect SARS-CoV-2 infection at an early stage. Nowadays, the reverse transcription polymerase chain reaction (RT-PCR) technique is being applied for detecting this virus around the globe; however, factors such as stringent expertise, long diagnostic times, invasive and painful screening, and high costs have restricted the use of RT-PCR methods for rapid diagnostics. Therefore, the development of cost-effective, portable, sensitive, prompt and selective sensing systems to detect SARS-CoV-2 in biofluids at fM/pM/nM concentrations would be a breakthrough in diagnostics. Immunosensors that show increased specificity and sensitivity are considerably fast and do not imply costly reagents or instruments, reducing the cost for COVID-19 detection. The current developments in immunosensors perhaps signify the most significant opportunity for a rapid assay to detect COVID-19, without the need of highly skilled professionals and specialized tools to interpret results. Artificial intelligence (AI) and the Internet of Medical Things (IoMT) can also be equipped with this immunosensing approach to investigate useful networking through database management, sharing, and analytics to prevent and manage COVID-19. Herein, we represent the collective concepts of biomarker-based immunosensors along with AI and IoMT as smart sensing strategies with bioinformatics approach to monitor non-invasive early stage SARS-CoV-2 development, with fast point-of-care (POC) diagnostics as the crucial goal. This approach should be implemented quickly and verified practicality for clinical samples before being set in the present times for mass-diagnostic research.
由于感染进展的严重性，世界卫生组织（WHO）已宣布新型冠状病毒肺炎（COVID-19）为国际卫生紧急事件。由于其在全球范围内的持续传播以及缺乏合适的治疗和诊断系统，感染情况变得更加严峻。因此，需要高效的设备来早期检测严重急性呼吸综合征冠状病毒2（SARS-CoV-2）感染。如今，逆转录聚合酶链反应（RT-PCR）技术正在全球范围内用于检测这种病毒；然而，严格的专业知识、较长的诊断时间、侵入性和痛苦的筛查以及高昂的成本等因素限制了RT-PCR方法用于快速诊断。因此，开发具有成本效益、便携、灵敏、快速且选择性的传感系统，以检测生物流体中fM/pM/nM浓度的SARS-CoV-2，将是诊断领域的一项突破。显示出更高特异性和灵敏度的免疫传感器相当快速，并且不需要昂贵的试剂或仪器，降低了COVID-19检测的成本。免疫传感器的当前发展可能意味着快速检测COVID-19的最重要机会，无需高技能专业人员和专门工具来解释结果。人工智能（AI）和医疗物联网（IoMT）也可以配备这种免疫传感方法，通过数据库管理、共享和分析来研究有用的网络，以预防和管理COVID-19。在此，我们将基于生物标志物的免疫传感器与AI和IoMT的集体概念作为智能传感策略，采用生物信息学方法来监测非侵入性早期SARS-CoV-2的发展，以快速即时检测（POC）诊断为关键目标。在用于大规模诊断研究之前，应迅速实施这种方法并验证其对临床样本的实用性。
