Designing a diagnostic Total Testing Process as a base for supporting diagnostic stewardship

Blood self-sampling devices: innovation, interpretation and implementation in total lab automation

The introduction of the vacuum tube in 1949 revolutionized blood collection, significantly improving sample quality and patient comfort. Over the past 75 years, laboratory diagnostics have evolved drastically, from manual to automated processes, reducing required test volumes by over 1,000 times. Despite these advancements, venous blood collection presents logistical challenges, including centralized scheduling and a large volume of biological waste due to the imbalance between the needed blood volume (often very little) and the collected volume (often in excess). The COVID-19 pandemic further emphasized the need for decentralized healthcare solutions and patient empowerment. Capillary blood collection, widely used in point-of-care testing, offers a promising alternative, particularly for patients facing frequently, or difficulties with, venous sampling. The Leiden University Medical Center in the Netherlands experienced a 15 % reduction in volume of laboratory tests during and after the pandemic, attributed to patient preference for local blood collection and testing. To address these challenges, self-sampling devices are emerging, empowering patients and streamlining sample logistics. However, challenges such as cost, transportation regulations, and sample volume adequacy persists. Robust devices tailored for total lab automation and sustainable practices are crucial for widespread adoption. Despite hurdles, the integration of self-sampling into diagnostic processes is inevitable, heralding a shift towards patient-centered, proactive healthcare. Practical recommendations include robust device design, ease of use, affordability, sustainability, sufficient quality and acceptability by seamless integration into laboratory workflows. Although obstacles remain, self-sampling represents the future of laboratory diagnostics, offering convenience, cost-effectiveness, interoperability and patient empowerment.

Quality Assurance for Multiplex Quantitative Clinical Chemistry Proteomics in Large Clinical Trials

BACKGROUND

To evaluate the clinical performance and effectiveness of a multiplex apolipoprotein panel in the context of cardiovascular precision diagnostics, clinical samples of patients with recent acute coronary syndrome in the ODYSSEY OUTCOMES trial were measured by quantitative clinical chemistry proteomics (qCCP). The ISO15189-accredited laboratory setting, including the total testing process (TTP), served as a foundation for this study. Consequently, tailored quality assurance measures needed to be designed and implemented to suit the demands of a multiplex LC-MS/MS test.

METHODS

Nine serum apolipoproteins were measured in 23 376 samples with a laboratory-developed multiplex apolipoprotein test on 4 Agilent 6495 LC-MS/MS systems. A fit-for-purpose process was designed with tailored additions enhancing the accredited laboratory infrastructure and the TTP. Quality assurance was organized in 3 steps: system suitability testing (SST), internal quality control (IQC) evaluation with adjusted Westgard rules to fit a multiplex test, and interpeptide agreement analysis. Data was semi-automatically evaluated with a custom R script.

RESULTS

LC-MS/MS analyses were performed with the following between-run CVs: for apolipoprotein (Apo) (a) 6.2%, Apo A-I 2.3%, Apo A-II 2.1%, Apo A-IV 2.9%, Apo B 1.9%, Apo C-I 3.3%, Apo C-II 3.3%, Apo C-III 2.7%, and for Apo E 3.3% and an average interpeptide agreement Pearson r of 0.981.

CONCLUSIONS

This is the first study of its kind in which qCCP was performed at this scale. This research successfully demonstrates the feasibility of high-throughput LC-MS/MS applications in large clinical trials. ClinicalTrials.gov Registration Number: NCT01663402.

Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy

Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.

Optimization of the STARlet workflow for semi-automatic SARS-CoV-2 screening of swabs and deep respiratory materials using the RealAccurate Quadruplex SARS-CoV-2 PCR kit and Allplex SARS-CoV-2 PCR kit

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic triggered the implementation of large-scale screenings in the health care and in the general population. Consequently, medical laboratories have to apply lean laboratory management to design workflows that are able to process large batches within short turnaround times while maintaining flexibility to use different SARS-CoV-2 reverse transcription polymerase chain reactions (RT-PCRs) and to be able to process a variety of clinical samples. We validated two SARS-CoV-2 PCR assays on the STARlet workflow: Allplex SARS-CoV-2 PCR kit and RealAccurate Quadruplex SARS-CoV-2 PCR kit. Furthermore, we optimized and validated the STARlet workflow for semi-automatic screening for SARS-CoV-2 in upper respiratory swabs and deep respiratory materials (sputa, bronchoalveolar lavage, and aspirate). Strikingly, guanidine-containing lysis buffers allow for easy processing and can enhance sensitivity of SARS-COV-2 screening since sampling in these buffers may preserve viral transcripts as evident by the higher copy numbers of the SARS-CoV-2 N gene. Moreover, using the principles of lean laboratory management, several bottlenecks that are typical for medical laboratories were addressed. We show that lean laboratory management resulted in significant reduction of the turnaround times of the SARS-CoV-2 PCR in our laboratory. This report thus describes a useful framework for laboratories to implement similar semi-automated workflows.IMPORTANCEThe SARS-CoV-2 pandemic triggered the implementation of large-scale screenings in the health care and in the general population. Consequently, medical laboratories had to adapt and evolve workflows that are able to process large batches within short turnaround times while maintaining flexibility to use different assays and to be able to process a variety of clinical samples. We describe how the need for increased outputs and greater flexibility was addressed with respect to clinical samples and assays (Allplex SARS-CoV-2 PCR and RealAccurate Quadruplex SARS-CoV-2 PCR). Strikingly, we found that upper respiratory swabs collected in guanidine-containing lysis buffers both improved the ease of processing as well as enhanced the sensitivity of the SARS-CoV-2 screening. This report thus describes a useful framework for laboratories to implement and optimize similar semi-automated workflows.