Automatic Processing of Chromatograms in a High-Throughput Environment

Liquid chromatography–tandem mass spectrometry for clinical diagnostics

Mass spectrometry is a powerful analytical tool used for the analysis of a wide range of substances and matrices; it is increasingly utilized for clinical applications in laboratory medicine. This Primer includes an overview of basic mass spectrometry concepts, focusing primarily on tandem mass spectrometry. We discuss experimental considerations and quality management, and provide an overview of some key applications in the clinic. Lastly, the Primer discusses significant challenges for implementation of mass spectrometry in clinical laboratories and provides an outlook of where there are emerging clinical applications for this technology.

Tandem mass spectrometry is increasingly utilized for clinical applications in laboratory medicine. In this Primer, Thomas et al. discuss experimental considerations and quality management for implementing clinical tandem mass spectrometry in the clinic with an overview of some key applications.

A new metric for relating macroscopic chromatograms to microscopic surface dynamics: the distribution function ratio (DFR)

Heterogeneous stationary phase chemistry causes chromatographic tailing that lowers separation efficiency and complicates optimizing mobile phase conditions. Model-free metrics are attractive for assessing optimal separation conditions due to the low quantity of information required, but often do not reveal underlying mechanisms that cause tailing, for example, heterogeneous retention modes. We report a new metric, which we call the Distribution Function Ratio (DFR), based on a graphical comparison between the chromatogram and Gaussian cumulative distribution functions, achieving correspondence to ground truth surface dynamics with a single chromatogram. Using a Monte Carlo framework, we show that the DFR can predict the prevalence of heterogeneous retention modes with high precision when the relative desorption rate between modes is known, as in during surface dynamics experiments. Ground truth comparisons reveal that the DFR outperforms both the asymmetry factor and skewness by yielding a one-to-one correspondence with heterogeneous retention mode prevalence over a broad range of experimentally realistic values. Perhaps of more value, we illustrate that the DFR, when combined with the asymmetry factor and skewness, can estimate microscopic surface dynamics, providing valuable insights into surface chemistry using existing chromatographic instrumentation. Connecting ensemble results to microscopic quantities through the lens of simulation establishes a new chemistry-driven route to measuring and advancing separations.

Data-driven quality assurance to prevent erroneous test results

Increasing laboratory automation and efficiency requires quality assurance (QA) approaches to ensure that reported results are precise and accurate. Prerequisites for designing optimal QA strategies include an in-depth understanding of the laboratory processes, the expected results, and of the mechanisms that can cause erroneous results. Oftentimes, a laboratory's own data, extracted from the laboratory information system, electronic medical record, and/or clinical data warehouse are necessary to master the aforementioned requirements. Data-driven QA utilizes retrospective and/or prospective laboratory results to minimize errors in the clinical laboratory due to pre-analytical or analytical vulnerabilities. Additionally, exploitation of this data may improve result interpretation. The objective of this review is to illustrate specific examples of data-driven QA approaches for several areas of the clinical laboratory and for different phases of the testing cycle.