Evaluate the comparability of two automated liquid handling systems for clinical toxicology assays

Automated liquid handling (ALH) platforms are increasingly implemented in clinical laboratories to improve analytical reproducibility and replace manual handling during sample analysis. In clinical toxicology laboratories, ALH platforms are primarily utilized to perform sample preparation and extraction prior to subsequent analysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). When performing analysis with complex human biological matrices, verifying the performance characteristics of ALH platforms is required to ensure the assays' accuracy and reproducibility. Here, we evaluated and compared the analytical performances of Perkin Elmer JANUS® and Tecan Fluent® ALH systems in parallel, based on their performance in two toxicology assays designed to identify and quantify various opiates, semisynthetic opiates, and their metabolites. The comparability of the instrument platforms was evaluated by comparing assay analytical measuring range, total analytical imprecisions, and patient samples measurement when the ALH platforms are incorporated as part of the clinical assay's workflow. We have shown that both ALH platforms meet quality and performance criteria suitable for clinical toxicology assays. Nevertheless, the two platforms exhibit biases when measuring unknown patient samples. Such variations in their analytical performances may cause discrepancies when comparing results obtained from two different ALH platforms. In conclusion, it is important to consider how variations in ALH platform performances can affect patient results interpretation when implementing them in clinical laboratories.

Iterative screen optimization maximizes the efficiency of macromolecular crystallization

Advances in X-ray crystallography have streamlined the process of determining high-resolution three-dimensional macromolecular structures. However, a rate-limiting step in this process continues to be the generation of crystals that are of sufficient size and quality for subsequent diffraction experiments. Here, iterative screen optimization (ISO), a highly automated process in which the precipitant concentrations of each condition in a crystallization screen are modified based on the results of a prior crystallization experiment, is described. After designing a novel high-throughput crystallization screen to take full advantage of this method, the value of ISO is demonstrated by using it to successfully crystallize a panel of six diverse proteins. The results suggest that ISO is an effective method to obtain macromolecular crystals, particularly for proteins that crystallize under a narrow range of precipitant concentrations.