Trends in molecular diagnostics: 12th European Meeting on Molecular Diagnostics, Noordwijk aan Zee, the Netherlands, 12-14 October 2022.

This report provides an overview of the highlights of the 12th European Meeting on Molecular Diagnostics held in Noordwijk aan Zee, The Netherlands, 12-14 October 2022. This 3-day conference covered many relevant topics in the field of molecular diagnostics in humans i.e. oncology, infectious diseases, laboratory medicine, pharmacogenetics, pathology, and preventive medicine. Other relevant topics included quality management, laboratory automation, diagnostic preparedness, and lessons learned from the COVID pandemic. More than 400 participants, the majority coming from European countries, attended the meeting. Besides high-quality scientific presentations, more than 40 diagnostic companies presented their latest innovations, altogether in an informal and inspiring ambiance.

Automated liquid-handling operations for robust, resilient, and efficient bio-based laboratory practices

Increase in the adoption of liquid handling devices (LHD) can facilitate experimental activities. Initially adopted by businesses and industry-based laboratories, the practice has also moved to academic environments, where a wide range of non-standard/non-typical experiments can be performed. Current protocols or laboratory analyses require researchers to transfer liquids for the purpose of dilution, mixing, or inoculation, among other operations. LHD can render laboratories more efficient by performing more experiments per unit of time, by making operations robust and resilient against external factors and unforeseen events such as the COVID-19 pandemic, and by remote operation. The present work reviews literature that reported the adoption and utilisation of LHD available in the market and presents examples of their practical use. Applications demonstrate the critical role of automation in research development and its ability to reduce human intervention in the experimental workflow. Ultimately, this work will provide guidance to academic researchers to determine which LHD can fulfil their needs and how to exploit their use in both conventional and non-conventional applications. Furthermore, the breadth of applications and the scarcity of academic institutions involved in research and development that utilise these devices highlights an important area of opportunity for shift in technology to maximize research outcomes.

Rapid design and implementation of an adaptive pooling workflow for SARS-CoV-2 testing in an NHS diagnostic laboratory: a proof-of-concept study.

Background: Diagnostic laboratories are currently required to provide routine testing of asymptomatic staff and patients as a part of their clinical screening for SARS-CoV-2 infection. However, these cohorts display very different disease prevalence from symptomatic individuals and testing capacity for asymptomatic screening is often limited. Group testing is frequently proposed as a possible solution to address this; however, proposals neglect the technical and operational feasibility of implementation in a front-line diagnostic laboratory. Methods: Between October and December 2020, as a seven-week proof of concept, we took into account scientific, technical and operational feasibility to design and implement an adaptive pooling strategy in an NHS diagnostic laboratory in London (UK). We assessed the impact of pooling on analytical sensitivity and modelled the impact of prevalence on pooling strategy. We then considered the operational constraints to model the potential gains in capacity and the requirements for additional staff and infrastructure. Finally, we developed a LIMS-agnostic laboratory automation workflow and software solution and tested the technical feasibility of our adaptive pooling workflow. Results: First, we determined the analytical sensitivity of the implemented SARS-CoV-2 assay to be 250 copies/mL. We then determined that, in a setting with limited analyser capacity, the testing capacity could be increased by two-fold with pooling, however, in a setting with limited reagents, this could rise to a five-fold increase. These capacity increases could be realized with modest additional resource and staffing requirements whilst utilizing up to 76% fewer plastic consumables and 90% fewer reagents. Finally, we successfully implemented a plate-based pooling workflow and tested 920 patient samples using the reagents that would usually be required to process just 222 samples. Conclusions: Adaptive pooled testing is a scientifically, technically and operationally feasible solution to increase testing capacity in frontline NHS diagnostic laboratories.

Clinical performance of the Elecsys® anti-SARS-CoV-2 combined in an algorithm with two specific anti-IgG immunoassays for the evaluation of the serological response of patients with COVID-19 in a population with a high prevalence of infection.

BACKGROUND: Anti-SARS-CoV-2 antibodies have been used in the study of the immune response in infected patients. However, differences in sensitivity and specificity have been reported, depending on the method of analysis. The aim of the present study was to evaluate the diagnostic accuracy of an algorithm in which a high-throughput automated assay for total antibodies was used for screening and two semi-automated IgG-specific methods were used to confirm the results, and also to correlate the analytical results with the clinical data and the time elapsed since infection. METHODS: We studied 306 patients, some hospitalized and some outpatients, belonging to a population with a high prevalence of COVID-19. One-hundred and ten patients were classified as SARS-CoV-2 negative and 196 as positive by polymerase chain reaction. RESULTS: The algorithm and automated assay alone had a specificity and a positive predictive value of 100%, although the sensitivity and negative predictive value of the algorithm was higher. Both methods showed a good sensitivity from day 11 of the onset of symptoms in asymptomatic and symptomatic patients. The absorbance of the total antibodies was significantly higher in severely symptomatic than in asymptomatic or mildly symptomatic patients, which suggests the antibody level was higher. We found 15 patients who did not present seroconversion at 12 days from the onset of symptoms or the first polymerase chain reaction test. CONCLUSION: This study highlights the proper functioning of algorithms in the diagnosis of the immune response to COVID-19, which can help to define testing strategies against this disease.

Converging global crises are forcing the rapid adoption of disruptive changes in drug discovery.

Spiralling research costs combined with urgent pressures from the Coronavirus 2019 (COVID-19) pandemic and the consequences of climate disruption are forcing changes in drug discovery. Increasing the predictive power of in vitro human assays and using them earlier in discovery would refocus resources on more successful research strategies and reduce animal studies. Increasing laboratory automation enables effective social distancing for researchers, while allowing integrated data capture from remote laboratory networks. Such disruptive changes would not only enable more cost-effective drug discovery, but could also reduce the overall carbon footprint of discovering new drugs.

Side-by-Side Comparison of Three Fully Automated SARS-CoV-2 Antibody Assays with a Focus on Specificity.

BACKGROUND: In the context of the COVID-19 pandemic, numerous new serological test systems for the detection of anti-SARS-CoV-2 antibodies rapidly have become available. However, the clinical performance of many of these is still insufficiently described. Therefore, we compared 3 commercial CE-marked, SARS-CoV-2 antibody assays side by side. METHODS: We included a total of 1154 specimens from pre-COVID-19 times and 65 samples from COVID-19 patients (≥14 days after symptom onset) to evaluate the test performance of SARS-CoV-2 serological assays by Abbott, Roche, and DiaSorin. RESULTS: All 3 assays presented with high specificities: 99.2% (98.6-99.7) for Abbott, 99.7% (99.2-100.0) for Roche, and 98.3% (97.3-98.9) for DiaSorin. In contrast to the manufacturers' specifications, sensitivities only ranged from 83.1% to 89.2%. Although the 3 methods were in good agreement (Cohen's Kappa 0.71-0.87), McNemar tests revealed significant differences between results obtained from Roche and DiaSorin. However, at low seroprevalences, the minor differences in specificity resulted in profound discrepancies of positive predictive values at 1% seroprevalence: 52.3% (36.2-67.9), 77.6% (52.8-91.5), and 32.6% (23.6-43.1) for Abbott, Roche, and DiaSorin, respectively. CONCLUSION: We found diagnostically relevant differences in specificities for the anti-SARS-CoV-2 antibody assays by Abbott, Roche, and DiaSorin that have a significant impact on the positive predictive values of these tests.