High-throughput Diagnostics
High-throughput Diagnostics - Related Videos
08:19
Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics
0 Views •
Cited by 24 •
2009
Lensfree on-chip imaging and characterization of cells is illustrated. This on-chip cell imaging approach provides a compact and cost-effective tool for medical diagnostics and high-throughput cell biology applications, making it especially suitable for resource poor settings.
09:44
High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes
0 Views •
2015
Here we describe a cell-based reporter gene assay as a valuable tool to screen chemical libraries for compounds modulating post-transcriptional control mechanisms exerted through 3’ UTR.
06:19
High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography
0 Views •
Cited by 16 •
2023
This protocol details high-throughput crystallization screening, ranging from the 1,536 microassay plate preparation to the end of a 6 week experimental time window. Details are included about the sample setup, the imaging obtained, and how users can perform analyses using an artificial intelligence-enabled graphical user interface to quickly and efficiently identify macromolecular crystallization conditions.
11:00
High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR
0 Views •
Cited by 11 •
2016
High-throughput testing of DNA and RNA based pathogens by nanoscale PCR is described using a syndromic canine and equine respiratory PCR panel.
10:21
Microfluidic Applications for Disposable Diagnostics
0 Views •
Cited by 1 •
2008
In this interview, Dr. Klapperich discusses the fabrication of thermoplastic microfluidic devices and their application for development of new diagnostics.
FAQs
These components divide the diagnostic workflow into coordinated stages. Automated handling moves many patient samples through testing, multiplex assays measure several biomarkers in a single reaction, and miniaturized or microfluidic platforms support compact processing. Together, they increase testing capacity while limiting manual work. Their effectiveness still depends on maintaining reliable measurements across the entire system.
Analytical sensitivity and specificity help determine whether a system can detect relevant targets and distinguish them appropriately. High testing volume does not compensate for unreliable analytical performance, because inaccurate results can undermine interpretation and clinical decisions. Laboratories therefore need validation to establish that the testing approach performs consistently before relying on results for medical or public-health use.
Computational workflows organize and analyze the large amount of information produced when many samples or biomarkers are tested. Quality control helps monitor whether results remain consistent throughout processing and analysis. These functions are essential because increased throughput creates more data and more opportunities for variation. Together, they support dependable interpretation rather than simply faster result generation.
A typical workflow begins with automated handling of patient samples, followed by testing on multiplex, miniaturized, or microfluidic platforms. The resulting measurements then move through computational analysis and quality-control procedures before interpretation. Validation supports confidence in the workflow's performance at each stage. This sequence links laboratory processing with the final information used for medical decisions.
In medicine, these systems support infectious-disease screening, molecular and genetic testing, cancer biomarker assessment, and population surveillance. The specific value differs by use case, but each application benefits from processing many samples or targets efficiently. By increasing capacity and consistency, the approach can help laboratories deliver timely information for clinical decision-making and broader public-health response.
Scalable systems are particularly relevant when laboratories must assess many samples, such as during infectious-disease screening or population surveillance. Their combination of rapid processing, multiplex measurement, automation, and computational quality control helps address large testing demands. However, scalability must remain coupled with sensitivity, specificity, validation, and careful interpretation so that speed does not replace trustworthy results.