The era of automation arrived with the introduction of the AutoAnalyzer using continuous flow analysis and the Robot Chemist that automated the traditional manual analytical steps. Successive generations of stand-alone analysers increased analytical speed, offered the ability to test high volumes of patient specimens, and provided large assay menus. A dichotomy developed, with a group of analysers devoted to performing routine clinical chemistry tests and another group dedicated to performing immunoassays using a variety of methodologies. Development of integrated systems greatly improved the analytical phase of clinical laboratory testing and further automation was developed for pre-analytical procedures, such as sample identification, sorting, and centrifugation, and post-analytical procedures, such as specimen storage and archiving. All phases of testing were ultimately combined in total laboratory automation (TLA) through which all modules involved are physically linked by some kind of track system, moving samples through the process from beginning-to-end. A newer and very powerful, analytical methodology is liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS). LC-MS/MS has been automated but a future automation challenge will be to incorporate LC-MS/MS into TLA configurations. Another important facet of automation is informatics, including middleware, which interfaces the analyser software to a laboratory information systems (LIS) and/or hospital information systems (HIS). This software includes control of the overall operation of a TLA configuration and combines analytical results with patient demographic information to provide additional clinically useful information. This review describes automation relevant to clinical chemistry, but it must be recognised that automation applies to other specialties in the laboratory, e.g. haematology, urinalysis, microbiology. It is a given that automation will continue to evolve in the clinical laboratory, limited only by the imagination and ingenuity of laboratory scientists.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204236PMC

Publication Analysis

Top Keywords

clinical chemistry
12
automation
9
laboratory automation
8
clinical laboratory
8
laboratory
7
clinical
5
analytical
5
chemistry laboratory
4
automation 21st
4
21st century
4

Similar Publications

The emergence of self-propelling magnetic nanobots represents a significant advancement in the field of drug delivery. These magneto-nanobots offer precise control over drug targeting and possess the capability to navigate deep into tumor tissues, thereby addressing multiple challenges associated with conventional cancer therapies. Here, Fe-GSH-Protein-Dox, a novel self-propelling magnetic nanobot conjugated with a biocompatible protein surface and loaded with doxorubicin for the treatment of triple-negative breast cancer (TNBC), is reported.

View Article and Find Full Text PDF

Iron oxide nanoparticles (IONPs) have the potential to be utilized in a multitude of fields, including biomedicine. Consequently, the potential health risks associated with their use must be carefully considered. Most biosafety evaluations of IONPs have focused on examining the impact of the material's distinctive physicochemical attributes.

View Article and Find Full Text PDF

This study aimed to evaluate the histological success of pulpotomy in primary molars using white mineral trioxide aggregate (WMTA) mixed with 2.25% sodium hypochlorite (NaOCl) gel and to evaluate in vitro its physical and chemical properties. The study had a clinical stage and an in-vitro stage.

View Article and Find Full Text PDF

The study aims to address the critical issue of toxic side effects resulting from drug combinations, which can significantly increase health risks, clinical complications, and lead to drug being withdrawn from the market. A model named TSEDDI (toxic side effects of drug-drug interaction) has been developed to improve the identification of drug pairs that may induce toxicity or adverse reactions. By utilizing drug chemical structures and diverse proteins, we employ a convolutional neural network (CNN) to extract features from molecular images, enzyme proteins, transporter proteins, and target proteins.

View Article and Find Full Text PDF

Carbon dots (CDs) are versatile nanomaterials that are considered ideal for application in bioimaging, drug delivery, sensing, and optoelectronics owing to their excellent photoluminescence, biocompatibility, and chemical stability features. Nitrogen doping enhances the fluorescence of CDs, alters their electronic properties, and improves their functional versatility. N-doped CDs can be synthesized via solvothermal treatment of carbon sources with nitrogen-rich precursors; however, systematic investigations of their synthesis mechanisms have been rarely reported.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!