标准化
计算机科学
系统工程
可靠性工程
工程类
操作系统
作者
Andrea C. Mora,Charles R. Mace
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2025-05-22
卷期号:10 (6): 3795-3805
被引量:4
标识
DOI:10.1021/acssensors.5c00667
摘要
The COVID-19 pandemic demonstrated the debilitating effect of overreliance on centralized sampling and testing, and generated significant momentum to investigate and validate sample types that are alternatives to the gold standard (e.g., anterior nasal vs nasopharyngeal swabs). As a result, sample collection is trending away from traditional methods at centralized health care facilities and toward at-home or point-of-care settings with devices that enable self-collection. With shifts away from regulated environments and trained personnel, it is important to remember that reliable measurements begin with standardized sample collection. To develop microsampling technologies for applications where the outcome can impact health care decisions, it is critical to (i) fully understand the sample collected (e.g., volume, composition, biological factors) and (ii) implement engineering controls for users and clinical workflow integration (e.g., usability, volume metering) to ensure precision and accuracy of a measurement. Blood sampling, once exclusively performed via venipuncture, has made the greatest strides toward remote collection with the introduction of lancet- and microneedle-based, capillary microsampling devices. However, challenges remain toward standardizing these methods, such as ensuring that measurements are hematocrit-independent. Other sample types (e.g., nasal fluid, saliva) face similar hurdles. In this Perspective, we review the current state of self-collection microsampling technologies and highlight the need to develop tools that can (i) standardize sample collection and (ii) seamlessly integrate with current clinical workflows. Ultimately, we advocate for continued innovation as technologies that support self-collection have the potential to greatly improve the diagnostic process for patients, reduce the burden on health care workers, and advance the shift toward decentralized testing.
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