Performance evaluation and user experience of BT-50 transportation unit with automated and scheduled quality control measurements

OBJECTIVES

Even in the current era of hematology analyzer automation and peripheral equipment, quality control sample measurement remains a manual task, leading to variability in quality control data and increased workload. In this study, we evaluated the performance of quality control measurement using the BT-50 Transportation Unit (BT-50, Sysmex, Kobe, Japan), equipped with a scheduled automatic quality control function, to ensure measurement accuracy and streamline the workflow of hematology testing.

METHODS

We evaluated the automatic measurement performance of quality control samples using the BT-50 for six representative blood test parameters: WBC (white blood cell), RBC (red blood cell), HGB (hemoglobin), HCT (hematocrit), PLT (platelet), and RET% (reticulocyte percent). We evaluated the equivalence and compared measurement accuracy between the BT-50 and the manual method. We then compared the variability to other laboratories and confirmed the stability of quality control samples. We also evaluated changes in workflow and staff resources before and after the introduction of the BT-50.

RESULTS

The quality control measurement results for the BT-50 and the manual method were found to be equivalent for all six parameters. The variability measured by the BT-50 was lower for some parameters compared to the manual method. Furthermore, the workflow was streamlined by reducing manual processes, resulting in increased efficiency.

CONCLUSIONS

We confirmed the performance of quality control measurements using the schedule function of the BT-50. Introducing the BT-50 reduced the operator's workload, improved operational efficiency, and promoted the standardization of quality control measurements.

Concept of flexible no-code automation for complex sample preparation procedures

Driven by demographic changes and dwindling Science Technology Engineering Mathematics enrolments, our research introduces no-code automation as a strategic response, aimed at mitigating labor shortages while enhancing productivity and safety in the laboratory environment. Employing a user-friendly, no-code software platform, we automated a complex HPTLC assay, enabling laboratory personnel to configure and modify workflows without requiring specialized programming skills. The manuscript outlines the deployment of a collaborative robot (cobot), a programmable logic controller (PLC), and the utilization of self-developed open-source hardware components to establish automated stations for sample handling, incubation, spraying, detection, and storage within the assay process. The research addresses challenges such as the handling of fragile HPTLC plates and the seamless integration of automated stations, solved through innovative design solutions and adaptive programming methods. This investigation demonstrates the feasibility and efficiency of no-code automation in overcoming skilled labor deficits.

Laboratory testing consolidation and total laboratory automation improves service efficiency and effectiveness: a study of a medical center in Taiwan

BACKGROUND

Test consolidation and total laboratory automation (TLA) were implemented in a core laboratory with a high volume of specimens in a medical center in Taiwan to reduce the costs of laboratory services and improve laboratory workflow and performance.

METHODS

Using a retrospective research approach, 5 stat and 7 routine tests were used to analyze the in-laboratory to report turnaround time (IR-TAT). Mean, SD, medium, 90th percentile, outlier percentage of IR-TAT, full-time equivalents, productivity, tube touch moment (TTM), and financial impact were determined and compared pre- and post-TLA.

RESULTS

The mean IR-TAT of overall stat chemical tests for inpatient and outpatient were 32.8% and 11.9% reductions, respectively. The productivity of each medical technologist increased by 32.4% per month, and there was a reduction of 5 medical technologists compared with the number required to complete the same tests before consolidation. The TTM of staff per year post-TLA decreased by 74.1% tube touches.

CONCLUSION

The efficiency of laboratory services was improved by consolidation to the core laboratory along with TLA implementation coupled with logic rules such as delta-check and autoverification. Effectiveness was improved as measured by an increase in productivity, labor reduction, staff safety, and cost reduction.

Diagnostic performance of an automated robot for MALDI target preparation in microbial identification

The MBT Pathfinder is an automated colony-picking robot designed for efficient sample preparation in matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. This article presents results from three key experiments evaluating the instrument's performance in conjunction with MALDI Biotyper instrument. The method comparison experiment assessed its clinical performance, demonstrating comparable results with gram-positive, gram-negative, and anaerobic bacteria (scores larger than 2.00) and superior performance over simple direct yeast transfer (score: 1.80) when compared to samples prepared manually. The repeatability experiment confirmed consistent performance over multiple days and labs (average log score: 2.12, std. deviation: 0.59). The challenge panel experiment showcased its consistent and accurate performance across various samples and settings, yielding average scores between 1.76 and 2.19. These findings underline the MBT Pathfinder as a reliable and efficient tool for MALDI-TOF mass spectrometry sample preparation in clinical and research applications.

Comparison of Multiple Carbapenemase Tests Based on an Unbiased Colony-Selection Method

Carbapenemase-producing organisms (CPOs) present a major threat to public health, demanding precise diagnostic techniques for their detection. Discrepancies among the CPO tests have raised concerns, partly due to limitations in detecting bacterial diversity within host specimens. We explored the impact of an unbiased colony selection on carbapenemase testing and assessed its relevance to various tests. Using the FirstAll method for unbiased colony selection to reduce bias, we compared the results from different methods, namely the modified carbapenem inactivation method/EDTA-modified carbapenem inactivation method (mCIM/eCIM), the Carba5, the CPO panel, and the multiplex PCR (MPCR). We compared the FirstAll method to the conventional colony selection for MPCR with seven CPO species. In addition, we evaluated the test performance on seven CPO species using MPCR as a reference and the FirstAll method as the colony-selection method. The results revealed that the selections from the FirstAll method have improved rates of carbapenemase detection, in comparison to approximately 11.2% of the CPO isolates that were noted to be false negatives in the conventional colony-selection methods. Both the Carba5 test and the CPO panel showed suboptimal performance (sensitivity/specificity: Carba5 74.6%/89.5%, CPO panel 77.2%/74.4%) in comparison to the FirstAll method. The Carba5 test provided specific carbapenemase class assignments, but the CPO panel failed in 18.7% of the cases. The Carba5 test and the CPO panel results correlated well with ceftazidime-avibactam minimal inhibitory concentrations (MICs). The concordance for Class A/D with MICs was 94.7% for Carba5 and 92.7% for the CPO panel; whereas for Class B, it was 86.5% for Carba5 and 75.9% for the CPO panel. In conclusion, FirstAll, as the unbiased colony-selection method, was shown to impact carbapenemase testing. With FirstAll, the diagnostic performance of both the Carba5 and the CPO panel was found to be lower. Furthermore, the utilization of ceftazidime-avibactam guided by either the CPO panel or Carba5 was appropriate.

Heparin Induced Thrombocytopenia Testing

This article provides a comprehensive overview of Heparin-Induced Thrombocytopenia (HIT) with an emphasis on laboratory testing and advantages of automation. HIT is a critical condition arising from heparin exposure, leading to a contradictory combination of thrombocytopenia with an increased thrombosis risk. The article discusses HIT's history, clinical presentation, laboratory diagnosis, and management strategies. It highlights the importance of interdisciplinary collaboration for effective diagnosis and treatment, underscoring advancements in technology and targeted therapies that are shaping future approaches to HIT management.

An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

Evaluation of the Comparability of Wantai Wan200+ Instrument with Routine Laboratory Assays for 21 Different Analytes

Background: We compared the performance of 21 different assays performed by the Wantai Wan200+ (Wantai BioPharm, Beijing, China) with respect to other methods in use at the University Hospital of Padova (AOPD), Italy. Methods: The plasma (P) or serum (S) of 5027 leftover samples, collected from May to Sept 2023, was either analyzed or frozen at -20 °C. Beckman DXI800 (DXI), Roche Cobas 8000 e801 (RC), Snibe Maglumi 4000 plus (SM), DiaSorin Liaison XL (DL) and Binding Site Optilite (BS) equipment were used at the AOPD. P-procalcitonin (PCT), DXI; P-Troponin I (TnI), DXI; S-CA125, DXI; S-free PSA (f-PSA), DXI; S-total PSA (t-PSA), DXI; S-IL6, SM; P-Troponin T (TnT), RC; P-NT-proBNP, RC; P-Neuron-Specific Enolase (NSE), RC; S-CA15-3, DL; S-CA19-9, DL; S-AFP, DL; and S-CEA, DL were tested in fresh samples. P-Myoglobin (Myo), DXI; P-Cyfra21-1, RC; S-β2 microglobulin (B2MIC), BS; S-HE4, SM; S-PGI, SM; S-PGII, SM; S-CA72-4, SM; and S-CA50, SM were analyzed in frozen and thawed samples. Bland-Altman (BA), Passing-Bablok (PB) and Cohen's Kappa (CKa) metrics were used as statistics. Results: An excellent comparability profile was found for 11 analytes. For example, the t-PSA CKa was 0.94 (95%CI: 0.90 to 0.98), and the PB slope and intercept were 1.02 (95%CI: 0.99 to 1.03) and 0.02 (95%CI: 0.01 to 0.03), respectively; the BA bias was 2.25 (95%CI: -0.43 to 4.93). Ten tested measurands demonstrated a suboptimal comparability profile. Biological variation in EFLM (EuBIVAS) performance specifications was evaluated to assess the clinical relevance of measured biases. Conclusions: Evaluation of the Wantai Wan200+'s performance suggests that between-method differences did not exceed the calculated bias. Metrological traceability may influence the comparisons obtained for some measurands.

Survey of Laboratory Medicine's national response to the HSE cyberattack in the Republic of Ireland

BACKGROUND

On Friday 14 May 2021, the Health Service Executive (HSE) was subjected to a serious cyberattack on their information technology (IT) infrastructure. Healthcare workers lost access to HSE-provided clinical and non-clinical IT systems, including laboratory systems.

AIM

The aim of this national survey was to capture Laboratory Medicine's response across the Republic of Ireland during the HSE cyberattack.

METHOD

An electronic survey developed using Microsoft Forms® was emailed on 24 September 2021 to 58 local representatives of the PeriAnalytic and Laboratory Medicine Society (PALMSoc).

RESULTS

The survey was sent to 43 clinical laboratories across the Republic of Ireland. A total of 41 responses from 43 laboratories across all laboratory disciplines were received (95% response rate). From these, 55% did not have access to a functioning LIS, with 56% of these not having access to a LIS for greater than 2 weeks. A decrease in specimen requests received during this period was reported by 74% of laboratories, with 32% experiencing a reduction that lasted in excess of one month. Over half of the laboratories (55%) experienced a reduction of > 30% in requests, indicating that clinicians stopped investigating patients (87% reduction in primary care), further escalating the disruption to healthcare.

CONCLUSION

The cyberattack burdened the HSE and laboratories at a time when healthcare staffs were coming to terms with the impact of the COVID-19 pandemic. Despite this, the survey confirms the agility of laboratory staff in meeting the demands placed on it during this time.

Development and evaluation of three automated media pooling and molecular diagnostic systems for the detection of SARS-CoV-2

Pooled testing combined with molecular diagnostics for the detection of SARS-CoV-2 is a promising method that can increase testing capacities and save costs. However, pooled testing is also associated with the risks of decreased test sensitivity and specificity. To perform reliable pooled testing, we developed and validated three automated media pooling and molecular diagnostic systems. These pooling systems (geneLEAD-PS, Panther-PS, and Biomek-PS) comprised existing automated molecular detection platforms, corresponding automated media pooling devices, and laboratory information management systems. Analytical sensitivity analysis and mock sample evaluation were performed, and the obtained data were used to determine the sizes of the pool for the validation study. In the validation study, a total of 2,448, 3,228, and 6,420 upper respiratory samples were used for geneLEAD-PS, Panther-PS, and Biomek-PS, respectively, and the diagnostic performances were compared with the reference RT‒PCR assay. A pool size of 6 for geneLEAD-PS and a pool size of 4 for Panther-PS and Biomek-PS were selected for the validation studies. All three systems showed high positive percent agreement values of ≥90.5% and negative percent agreement values of ≥99.8% for any specimen type. Pooled testing resulted in a 65%-71% reduction in cost per sample. The testing capacities of geneLEAD-PS, Panther-PS, and Biomek-PS were 144 samples in 3 hours, 384 samples in 5.5 hours, and 376 samples in 4 hours, respectively. The developed pooling systems showed robust diagnostic performances and will increase the testing capacities of molecular diagnostic tests while saving costs and may contribute to infection control of COVID-19.IMPORTANCEDuring the COVID-19 pandemic, there have been surges in demand for accurate molecular diagnostic testing and laboratory supply shortages. Pooled testing combined with highly sensitive molecular testing, which entails mixing multiple samples as a single sample, is a promising approach to increase testing capacities while reducing the use of consumables. However, pooled testing is associated with risks that compromise diagnostic performance, such as false negatives due to dilution of positive samples or false positives due to cross-contamination. To perform reliable pooled testing, three different pooling systems (an automated pooling device, an automated molecular detection platform, and a laboratory information management system) were developed to accurately interpret pooled testing results. These three systems were validated using multiple clinical samples and showed high concordance with individual testing. The developed pooling systems will contribute to increasing reliable molecular testing capacities while using fewer consumables and saving costs.

Increasing segmentation performance with synthetic agar plate images

Background

Agar plate analysis is vital for microbiological testing in industries like food, pharmaceuticals, and biotechnology. Manual inspection is slow, laborious, and error-prone, while existing automated systems struggle with the complexity of real-world agar plates. A shortage of diverse datasets hinders the development and evaluation of robust automated systems.

Methods

In this paper, two new annotated datasets and a novel methodology for synthetic agar plate generation are presented. The datasets comprise 854 images of cultivated agar plates and 1,588 images of empty agar plates, encompassing various agar plate types and microorganisms. These datasets are an extension of the publicly available BRUKERCOLONY dataset, collectively forming one of the largest publicly available annotated datasets for research. The methodology is based on an efficient image generation pipeline that also simulates cultivation-related phenomena such as haemolysis or chromogenic reactions.

Results

The augmentations significantly improved the Dice coefficient of trained U-Net models, increasing it from 0.671 to 0.721. Furthermore, training the U-Net model with a combination of real and 150% synthetic data demonstrated its efficacy, yielding a remarkable Dice coefficient of 0.729, a substantial improvement from the baseline of 0.518. UNet3+ exhibited the highest performance among the U-Net and Attention U-Net architectures, achieving a Dice coefficient of 0.767.

Conclusions

Our experiments showed the methodology's applicability to real-world scenarios, even with highly variable agar plates. Our paper contributes to automating agar plate analysis by presenting a new dataset and effective methodology, potentially enhancing fully automated microbiological testing.

Fully automated high-throughput immuno-µPlaque assay for live-attenuated tetravalent dengue vaccine development

Dengue fever has remained a continuing global medical threat that impacts half of the world's population. Developing a highly effective dengue vaccine, with live-attenuated tetravalent vaccines as leading candidates, remains essential in preventing this disease. For the development of live virus vaccines (LVVs), potency measurements play a vital role in quantifying the active components of vaccine drug substance as well as drug product during various stages of research, development, and post-licensure evaluations. Traditional plaque-based assays are one of the most common potency test methods, but they generally take up to weeks to complete. Less labor and time-intensive potency assays are thus called for to aid in the acceleration of vaccine development, especially for multivalent LVVs. Here, we introduce a fully automated, 96-well format µPlaque assay that has been optimized as a high-throughput tool to evaluate process and formulation development of a live-attenuated tetravalent dengue vaccine. To the best of our knowledge, this is the first report of a miniaturized viral plaque method for dengue with full automation via an integrated robotic system. Compared to the traditional manual plaque assay, this newly developed method substantially reduces testing time by approximately half and allows for the evaluation of over ten times more samples per run. The fully automated workflow, from cell culture to plaque counting, significantly minimizes analyst hands-on time and improves assay repeatability. The study presents a pioneering solution for the rapid measurement of LVV viral titers, offering promising prospects for advancing vaccine development through high-throughput analytics.

Conversion of a classical microbiology laboratory to a total automation laboratory enhanced by the application of lean principles

Laboratory automation in microbiology improves productivity and reduces sample turnaround times (TATs). However, its full potential can be unlocked through the optimization of workflows by adopting lean principles. This study aimed to explore the relative impact of laboratory automation and continuous improvement events (CIEs) on productivity and TATs. Laboratory automation took place in November 2020 and consisted of the introduction of WASPLab and VITEK MS systems. CIEs were run in May and September 2021. Before the conversion, the laboratory processed about ~492 samples on weekdays and had 10 full-time equivalent (FTE) staff for a productivity of 49 samples/FTE/day. In March 2021, after laboratory automation, the caseload went up to ~621 while the FTEs decreased to 8.5, accounting for productivity improvement to 73 samples/FTE/day. The hypothetical productivity went up to 110 samples/FTE/day following CIEs, meaning that the laboratory could at that point deal with a caseload increase to ~935 with unchanged FTEs. Laboratory conversion also led to an improvement in TATs for all sample types. For vaginal swabs and urine samples, median TATs decreased from 70.3 h [interquartile range (IQR): 63.5-93.1] and 73.7 h (IQR: 35.6-50.7) to 48.2 h (IQR: 44.8-67.7) and 40.0 h (IQR: 35.6-50.7), respectively. Automation alone was responsible for 37.2% and 75.8% of TAT reduction, respectively, while the remaining reduction of 62.8% and 24.2%, respectively, was achieved due to CIEs. The laboratory reached productivity and TAT goals predefined by the management after CIEs. In conclusion, automation substantially improved productivity and TATs, while the subsequent implementation of lean management further unlocked the potential of laboratory automation.IMPORTANCEIn this study, we combined total laboratory automation with lean management to show that appropriate laboratory work organization enhanced the benefit of the automation and substantially contributed to productivity improvements. Globally, the rapid availability of accurate results in the setting of a clinical microbiology laboratory is part of patient-centered approaches to treat infections and helps the implementation of antibiotic stewardship programs backed by the World Health Organization. Locally, from the point of view of laboratory management, it is important to find ways of maximizing the benefits of the use of technology, as total laboratory automation is an expensive investment.

Innovations in Diabetic Macular Edema Management: A Comprehensive Review of Automated Quantification and Anti-vascular Endothelial Growth Factor Intervention

Diabetic macular edema (DME) poses a significant threat to the vision and quality of life of individuals with diabetes. This comprehensive review explores recent advancements in DME management, focusing on integrating automated quantification techniques and anti-vascular endothelial growth factor (anti-VEGF) interventions. The review begins with an overview of DME, emphasizing its prevalence, impact on diabetic patients, and current challenges in management. It then delves into the potential of automated quantification, leveraging machine learning and artificial intelligence to improve early detection and monitoring. Concurrently, the role of anti-VEGF therapies in addressing the underlying vascular abnormalities in DME is scrutinized. The review synthesizes vital findings, highlighting the implications for the future of DME management. Promising outcomes from recent clinical trials and case studies are discussed, providing insights into the evolving landscape of personalized medicine approaches. The conclusion underscores the transformative potential of these innovations, calling for continued research, collaboration, and integration of these advancements into clinical practice. This review aims to serve as a roadmap for researchers, clinicians, and industry stakeholders, fostering a collective effort to enhance the precision and efficacy of DME management.

Can I benefit from laboratory automation? A decision aid for the successful introduction of laboratory automation

The large volumes of samples to be analysed every day would be impossible to manage without laboratory automation. As laboratory procedures have progressed, so have the tasks of laboratory personnel. With this feature article, we would like to provide (bio)chemical practitioners with little or no knowledge of laboratory automation with a guide to help them decide whether to implement laboratory automation and find a suitable system. Especially in small- and medium-sized laboratories, operating a laboratory system means having bioanalytical knowledge, but also being familiar with the technical aspects. However, time, budget and personnel limitations allow little opportunity for personnel to get into the depths of laboratory automation. This includes not only the operation, but also the decision to purchase an automation system. Hasty investments do not only result in slow or non-existent cost recovery, but also occupy valuable laboratory space. We have structured the article as a decision tree, so readers can selectively read chapters that apply to their individual situation. This flexible approach allows each reader to create a personal reading flow tailored to their specific needs. We tried to address a variety of perspectives on the topic, including people who are either supportive or sceptical of laboratory automation, personnel who want or need to automate specific processes, those who are unsure whether to automate and those who are interested in automation but do not know which areas to prioritize. We also help to make a decision whether to reactivate or discard already existing and unused laboratory equipment.

Development and evaluation of the automated multipurpose molecular testing system PCRpack for high-throughput SARS-CoV-2 testing

IMPORTANCE

Accurate and fast molecular testing is important for the diagnosis and control of COVID-19. During patient surges in the COVID-19 pandemic, laboratories were challenged by a higher demand for molecular testing under skilled staff shortages. We developed an automated multipurpose molecular testing system, named PCRpack, for the rapid, high-throughput testing of infectious pathogens, including SARS-CoV-2. The system is provided in an all-in-one package, including a liquid handling instrument, a laboratory information management system, and other materials needed for testing operation; is highly customizable; and is easily implemented. PCRpack showed robust liquid handling performance, high clinical diagnostic performance, a shorter turn-around time with minimal hands-on time, and a high testing capacity. These features contribute to the rapid implementation of the high-performance and high-throughput molecular testing environment at any phase of the pandemic caused by SARS-CoV-2 or future emerging pathogens.

Characterization of add-on testing before and after automation at a core laboratory

Objectives

Add-on testing refers to the process that occurs in clinical laboratories when clinicians request that additional tests be performed on a previously analysed specimen. This is a common but inefficient procedure, highly time-consuming, especially at core laboratories and could be optimised by automating these procedures. The aims of this study are: 1) To describe patterns of add-on testing at a core laboratory at a tertiary hospital, 2) To evaluate turnaround time (TAT) before and after automation of the pre-, post- and analytical phases.

Methods

Retrospective, observational study conducted at the biochemistry area of a core laboratory of all add-on orders received in two different months (pre-automation and post-automation).

Results

A total of 2464 add-on orders were analysed, representing around 5 % of total requests. Most orders were for either one (>50 %) or two (≈20 %) tests. Most orders were received during the week (from Monday to Friday), particularly during the morning shift (>50 %). More than 50 % of requests were made by the Emergency Department. The two most common add-on parameters were C-reactive protein and N-terminal pro-brain natriuretic peptide. After automation, the median TAT decreased by 42.3 % (from 52 to 22 min). The largest decreases in TAT were observed for routine samples (58.89 %) and fully automated analyses (56.86 %).

Conclusions

Automation of our core laboratory substantially reduced turnaround time for add-on testing, indicating an increase in efficiency. Automation eliminated several manual steps in the process, leading to a mean reduction of 15 work hours per day (more than 2 full-time equivalents).

Short-Term (6 Weeks) Experience of a Modular Workcell for Hemostasis Testing Including an Intelligent Data Manager at a Tertiary Care Hospital

OBJECTIVE

Modular workcells could be a better solution than total laboratory automation (TLA) in hemostasis laboratories. Here, we evaluated the impact of implementing a modular workcell (HemoCell) with an intelligent data management facility (HemoHub).

METHODS

We compared the turnaround times (TATs), numbers of rerun samples, and rerun times pre- and postimplementation of the HemoCell at Gil Medical Center. Prothrombin time (PT), activated partial thromboplastin time (aPTT), D-dimer, and fibrinogen were evaluated.

RESULTS

The TAT standard deviations (SDs) and maximum TAT values decreased after HemoCell implementation, although the mean TATs for PT, aPTT, and D-dimer were increased. Numbers of rerun samples were increased (18.1/day vs 44.7/day). However, rerun times were reduced, and SDs were decreased during the post-HemoCell period compared with pre-HemoCell. Additionally, technologists needed smaller working space and less labor.

CONCLUSION

The modular workcell could improve quality and efficiency by providing more consistent TATs and shorter rerun times in the hemostasis laboratory.

Cyberbiosecurity in high-containment laboratories

High-containment laboratories (HCLs) conduct critical research on infectious diseases, provide diagnostic services, and produce vaccines for the world's most dangerous pathogens, often called high-consequence pathogens (HCPs). The modernization of HCLs has led to an increasingly cyber-connected laboratory infrastructure. The unique cyberphysical elements of these laboratories and the critical data they generate pose cybersecurity concerns specific to these laboratories. Cyberbiosecurity, the discipline devoted to the study of cybersecurity risks in conjunction with biological risks, is a relatively new field for which few approaches have been developed to identify, assess, and mitigate cyber risks in biological research and diagnostic environments. This study provides a novel approach for cybersecurity risk assessment and identification of risk mitigation measures by applying an asset-impact analysis to the unique environment of HCLs. First, we identified the common cyber and cyberphysical systems in HCLs, summarizing the typical cyber-workflow. We then analyzed the potential adverse outcomes arising from a compromise of these cyber and cyberphysical systems, broadly categorizing potential consequences as relevant to scientific advancement, public health, worker safety, security, and the financial wellbeing of these laboratories. Finally, we discussed potential risk mitigation strategies, leaning heavily on the cybersecurity materials produced by the Center for Internet Security (CIS), including the CIS Controls®, that can serve as a guide for HCL operators to begin the process of implementing risk mitigation measures to reduce their cyberbiorisk and considering the integration of cyber risk management into existing biorisk management practices. This paper provides a discussion to raise awareness among laboratory decision-makers of these critical risks to safety and security within HCLs. Furthermore, this paper can serve as a guide for evaluating cyberbiorisks specific to a laboratory by identifying cyber-connected assets and the impacts associated with a compromise of those assets.

Laboratory Automation in Microbiology: Impact on Turnaround Time of Microbiological Samples in COVID Time

BACKGROUND

Laboratory Automation (LA) is an innovative technology that is currently available for microbiology laboratories. LA can be a game changer by revolutionizing laboratory workflows through efficiency improvement and is also effective in the organization and standardization of procedures, enabling staff requalification. It can provide an important return on investment (time spent redefining the workflow as well as direct costs of instrumentation) in the medium to long term.

METHODS

Here, we present our experience with the WASPLab^® system introduced in our lab during the COVID-19 pandemic. We evaluated the impact due to the system by comparing the TAT recorded on our samples before, during, and after LA introduction (from 2019 to 2021). We focused our attention on blood cultures (BCs) and biological fluid samples (BLs).

RESULTS

TAT recorded over time showed a significant decrease: from 97 h to 53.5 h (Δ43.5 h) for BCs and from 73 h to 58 h (Δ20 h) for BLs. Despite the introduction of the WASPLab^® system, we have not been able to reduce the number of technical personnel units dedicated to the microbiology lab, but WASPLab^® has allowed us to direct some of the staff resources toward other laboratory activities, including those required by the pandemic.

CONCLUSIONS

LA can significantly enhance laboratory performance and, due to the significant reduction in reporting time, can have an effective impact on clinical choices and therefore on patient outcomes. Therefore, the initial costs of LA adoption must be considered worthwhile.

Next-generation nanophotonic-enabled biosensors for intelligent diagnosis of SARS-CoV-2 variants

Constantly mutating SARS-CoV-2 is a global concern resulting in COVID-19 infectious waves from time to time in different regions, challenging present-day diagnostics and therapeutics. Early-stage point-of-care diagnostic (POC) biosensors are a crucial vector for the timely management of morbidity and mortalities caused due to COVID-19. The state-of-the-art SARS-CoV-2 biosensors depend upon developing a single platform for its diverse variants/biomarkers, enabling precise detection and monitoring. Nanophotonic-enabled biosensors have emerged as 'one platform' to diagnose COVID-19, addressing the concern of constant viral mutation. This review assesses the evolution of current and future variants of the SARS-CoV-2 and critically summarizes the current state of biosensor approaches for detecting SARS-CoV-2 variants/biomarkers employing nanophotonic-enabled diagnostics. It discusses the integration of modern-age technologies, including artificial intelligence, machine learning and 5G communication with nanophotonic biosensors for intelligent COVID-19 monitoring and management. It also highlights the challenges and potential opportunities for developing intelligent biosensors for diagnosing future SARS-CoV-2 variants. This review will guide future research and development on nano-enabled intelligent photonic-biosensor strategies for early-stage diagnosing of highly infectious diseases to prevent repeated outbreaks and save associated human mortalities.

Challenging gold standard hematology diagnostics through the introduction of whole genome sequencing and artificial intelligence

The diagnosis of hematological malignancies is rather complex and requires the application of a plethora of different assays, techniques and methodologies. Some of the methods, like cytomorphology, have been in use for decades, while other methods, such as next-generation sequencing or even whole genome sequencing (WGS), are relatively new. The application of the methods and the evaluation of the results require distinct skills and knowledge and place different demands on the practitioner. However, even with experienced hematologists, diagnostic ambiguity remains a regular occurrence and the comprehensive analysis of high-dimensional WGS data soon exceeds any human's capacity. Hence, in order to reduce inter-observer variability and to improve the timeliness and accuracy of diagnoses, machine learning based approaches have been developed to assist in the decision making process. Moreover, to achieve the goal of precision oncology, comprehensive genomic profiling is increasingly being incorporated into routine standard of care.

A semi-automated device rapidly determine circulating blood volume in healthy males and carbon monoxide uptake kinetics of arterial and venous blood

We examined whether a semi-automated carbon monoxide (CO) rebreathing method accurately detect changes in blood volume (BV) and total hemoglobin mass (tHb). Furthermore, we investigated whether a supine position with legs raised reduced systemic CO dilution time, potentially allowing a shorter rebreathing period. Nineteen young healthy males participated. BV and tHb was quantified by a 10-min CO-rebreathing period in a supine position with legs raised before and immediately after a 900 ml phlebotomy and before and after a 900 ml autologous blood reinfusion on the same day in 16 subjects. During the first CO-rebreathing, arterial and venous blood samples were drawn every 2 min during the procedure to determine systemic CO equilibrium in all subjects. Phlebotomy decreased (P < 0.001) tHb and BV by 166 ± 24 g and 931 ± 247 ml, respectively, while reinfusion increased (P < 0.001) tHb and BV by 143 ± 21 g and 862 ± 250 ml compared to before reinfusion. After reinfusion BV did not differ from baseline levels while tHb was decreased (P < 0.001) by 36 ± 21 g. Complete CO mixing was achieved within 6 min in venous and arterial blood, respectively, when compared to the 10-min sample. On an individual level, the relative accuracy after donation for tHb and BV was 102-169% and 55-165%, respectively. The applied CO-rebreathing procedure precisely detect acute BV changes with a clinically insignificant margin of error. The 10-min CO-procedure may be reduced to 6 min with no clinical effects on BV and tHb calculation. Notwithstanding, individual differences may be of concern and should be investigated further.

Diagnostic quality model (DQM): an integrated framework for the assessment of diagnostic quality when using AI/ML

BACKGROUND

Laboratory medicine has reached the era where promises of artificial intelligence and machine learning (AI/ML) seem palpable. Currently, the primary responsibility for risk-benefit assessment in clinical practice resides with the medical director. Unfortunately, there is no tool or concept that enables diagnostic quality assessment for the various potential AI/ML applications. Specifically, we noted that an operational definition of laboratory diagnostic quality - for the specific purpose of assessing AI/ML improvements - is currently missing.

METHODS

A session at the 3rd Strategic Conference of the European Federation of Laboratory Medicine in 2022 on "AI in the Laboratory of the Future" prompted an expert roundtable discussion. Here we present a conceptual diagnostic quality framework for the specific purpose of assessing AI/ML implementations.

RESULTS

The presented framework is termed diagnostic quality model (DQM) and distinguishes AI/ML improvements at the test, procedure, laboratory, or healthcare ecosystem level. The operational definition illustrates the nested relationship among these levels. The model can help to define relevant objectives for implementation and how levels come together to form coherent diagnostics. The affected levels are referred to as scope and we provide a rubric to quantify AI/ML improvements while complying with existing, mandated regulatory standards. We present 4 relevant clinical scenarios including multi-modal diagnostics and compare the model to existing quality management systems.

CONCLUSIONS

A diagnostic quality model is essential to navigate the complexities of clinical AI/ML implementations. The presented diagnostic quality framework can help to specify and communicate the key implications of AI/ML solutions in laboratory diagnostics.

High-Throughput and Automated Detection of HLA-B*27 Using the LabTurboTM AIO System

The adoption of an automated system can decrease the hands-on time requirements in a clinical laboratory setting. For the detection of HLA-B*27, implementing a high-throughput and fully automated system has several advantages over using manual methods. Therefore, this study aimed to evaluate automation efficiency for the detection of HLA-B*27. Peripheral blood samples were obtained from 50 participants, and DNA was isolated from these samples. A Pharmigene PG27 detection kit was used for the qualitative detection of HLA-B*27. The performances of the semi-automated and fully automated LabTurbo^TM AIO systems in the detection of HLA-B*27 were compared. The mean absorbance (optical density) values for the Maelstrom^TM 8 and LabTurbo^TM AIO systems were found to be 1.88 and 1.9, respectively. The housekeeping gene was amplified and quantified using a real-time PCR assay across all DNA extracts to check the quality of the extracted human DNA. The results were expressed as the cycle threshold (Ct) values for all DNA extracts from both platforms. The mean Ct values for the Roche Cobas z480 and LabTurbo^TM AIO systems were found to be 22.7 and 20.4, respectively. This study demonstrated that the semi-automated method and the LabTurbo^TM AIO system yield consistent results for the detection of HLA-B*27. However, compared to the semi-automated method, the LabTurbo^TM AIO system provides standardized procedures, avoids manual handling, and improves turnaround time.

Automated Approach to In Vitro Image-Guided Photothermal Therapy with Top-Down and Bottom-Up-Synthesized Graphene Quantum Dots

Graphene-based materials have been the subject of interest for photothermal therapy due to their high light-to-heat conversion efficiency. Based on recent studies, graphene quantum dots (GQDs) are expected to possess advantageous photothermal properties and facilitate fluorescence image-tracking in the visible and near-infrared (NIR), while surpassing other graphene-based materials in their biocompatibility. Several GQD structures including reduced graphene quantum dots (RGQDs) derived from reduced graphene oxide via top-down oxidation and hyaluronic acid graphene quantum dots (HGQDs) hydrothermally bottom-up synthesized from molecular hyaluronic acid were employed to test these capabilities in the present work. These GQDs possess substantial NIR absorption and fluorescence throughout the visible and NIR beneficial for in vivo imaging while being biocompatible at up to 1.7 mg/mL concentrations. In aqueous suspensions, RGQDs and HGQDs irradiated with a low power (0.9 W/cm2) 808 nm NIR laser facilitate a temperature increase up to 47.0 °C, which is sufficient for cancer tumor ablation. In vitro photothermal experiments sampling multiple conditions directly in the 96-well plate were performed using an automated simultaneous irradiation/measurement system developed on the basis of a 3D printer. In this study, HGQDs and RGQDs facilitated the heating of HeLa cancer cells up to 54.5 °C, leading to the drastic inhibition of cell viability from over 80% down to 22.9%. GQD's fluorescence in the visible and NIR traces their successful internalization into HeLa cells maximized at 20 h suggesting both extracellular and intracellular photothermal treatment capabilities. The combination of the photothermal and imaging modalities tested in vitro makes the GQDs developed in this work prospective agents for cancer theragnostics.

Development and clinical evaluation of an online automated quality control system for improving laboratory quality management

BACKGROUND

We developed an efficient online automated quality control (AUTO QC) system and tested its feasibility on automatic laboratory assembly lines.

METHODS

AUTO QC is based on developed quality control software (Smart QC) and designed adaptable consumables before. We applied the system to two assembly lines in our laboratory. Using third-party quality control samples, we evaluated the impact of the online AUTO QC system on out-of-control rate, biosecurity risk, turnaround time (TAT) and cost.

RESULTS

AUTO QC significantly decreased the occurrence rate of the Westgard quality control rules 1_3S/2_2S/R_4s and 1_2S, representing out-of-control and warning, respectively. The out-of-control rates were reduced by 58%, and the potential biosecurity risk of the samples decreased by 90%. The AUTO QC implementation also reduced the median TAT (by 7 min), the number of full-time employees and the cost of the quality control samples (by 45%).

CONCLUSIONS

The total laboratory AUTO QC system can improve the quality and stability of QC testing and reduce cost.

Performance of digital morphology analyzer CellaVision DC-1

OBJECTIVES

CellaVision DC-1 (DC-1, Sysmex, Kobe, Japan) is a newly launched digital morphology analyzer that was developed mainly for small to medium-volume laboratories. We evaluated the precision, qualitative performance, comparison of cell counts between DC-1 and manual counting, and turnaround time (TAT) of DC-1.

METHODS

Using five peripheral blood smear (PBS) slides spanning normal white blood cell (WBC) range, precision and qualitative performance of DC-1 were evaluated according to the Clinical and Laboratory Standards Institute (CLSI) EP15-A3, EP15-Ed3-IG1, and EP12-A2 guidelines. Cell counts of DC-1 and manual counting were compared according to the CLSI EP 09C-ED3 guidelines, and TAT of DC-1 was also compared with TAT of manual counting.

RESULTS

DC-1 showed excellent precision (%CV, 0.0-3.5%), high specificity (98.9-100.0%), and high negative predictive value (98.4-100.0%) in 18 cell classes (12 WBC classes and six non-WBC classes). However, DC-1 showed 0% of positive predictive value in seven cell classes (metamyelocytes, myelocytes, promyelocytes, blasts, plasma cells, nucleated red blood cells, and unidentified). The largest absolute mean differences (%) of DC-1 vs. manual counting was 2.74. Total TAT (min:s) was comparable between DC-1 (8:55) and manual counting (8:55).

CONCLUSIONS

This is the first study that comprehensively evaluated the performance of DC-1 including its TAT. DC-1 has a reliable performance that can be used in small to medium-volume laboratories for assisting PBS review. However, DC-1 may make unnecessary workload for cell verification in some cell classes.

Automation in the Thrombosis and Hemostasis Laboratory

Automation continues to advance into hemostasis and thrombosis laboratories. Integration of hemostasis testing into an existing chemistry track systems and adoption of a separate hemostasis track systems are important considerations. Unique issues must be addressed to maintain quality and efficiency when automation is introduced. Among other challenges, this chapter discusses centrifugation protocols, incorporation of specimen-check modules in the workflow, and inclusion of tests amenable to automation.

Magnetic Nanoparticle-Based Semi-automated Panning for High-Throughput Antibody Selection

Bio-panning is a common process involved in recombinant antibody selection against defined targets. The biopanning process aims to isolate specific antibodies against an antigen via affinity selection from a phage display library. In general, antigens are immobilized on solid surfaces such as polystyrene plastic, magnetic beads, and nitrocellulose. For high-throughput selection, semi-automated panning selection allows simultaneous panning against multiple target antigens adapting automated particle processing systems such as the KingFisher Flex. The system setup allows for minimal human intervention for pre- and post-panning steps such as antigen immobilization, phage rescue, and amplification. In addition, the platform is also adaptable to perform polyclonal and monoclonal ELISA for the evaluation process. This chapter will detail the protocols involved from the selection stage until the monoclonal ELISA evaluation with important notes attached at the end of this chapter for optimization and troubleshooting purposes.

Comparison of the APAS Independence Automated Plate Reader System with the Manual Standard of Care for Processing Urine Culture Specimens

Urine cultures are among the highest-volume tests in clinical microbiology laboratories and usually require considerable manual labor to perform. We evaluated the APAS Independence automated plate reader system and compared it to our manual standard of care (SOC) for processing urine cultures. The APAS device provides automated image interpretation of urine culture plate growth and sorts those images that require further evaluation. We examined 1,519 specimens over a 4-month period and compared the APAS growth interpretations to our SOC. We found that 72 of the 1,519 total specimens (4.74%) had growth discrepancies, where these specimens were interpreted differently by the APAS and the technologist, which required additional evaluation of plate images on the APAS system. Overall, there were 56 discrepancies in pathogen identification, which were present in 3.69% of the cultures. An additional pathogen was uncovered in a majority of these discrepancies; 12 (21.4%) identified an additional pathogen for the SOC, and 40 (71.4%) identified an additional pathogen for the APAS workflow. We found 214 (2.69%) antimicrobial susceptibility test (AST) discrepancies; 136 (1.71%) minor errors (mEs), 41 (0.52%) major errors (MEs), and 36 (0.45%) very major errors (VMEs). Many of the MEs and VMEs occurred in only a small subset of 13 organisms, suggesting that the specimen may have had different strains of the same pathogens with differing AST results. Given the significant labor required to perform urine cultures, the APAS Independence system has the potential to reduce manual labor while maintaining the identity and AST results of urinary pathogens. IMPORTANCE Urine cultures are among the highest-volume tests performed in clinical microbiology facilities and require considerable manual labor to perform. We compared the results of our manual SOC workflow with that of the APAS Independence system, which provides automated image interpretation and sorting of urine culture plates based on growth. We examined 1,519 urine cultures processed using both workflows and found that only 4.74% had growth pattern discrepancies and 3.69% pathogen identification discrepancies. There was substantial agreement in AST results between workflows, with only 2.69% having discrepancies. Only 1.71% of the ASTs had mEs, 0.52% had MEs, and 0.45% had VMEs, with most of the MEs and VMEs belonging to a small subset of organisms. The APAS system significantly decreased manual urine culture processing, while providing similar results to the SOC. As such, incorporating such automation into laboratory workflows has the potential to significantly improve efficiency.

Digital Morphology Analyzer Sysmex DI-60 vs. Manual Counting for White Blood Cell Differentials in Leukopenic Samples: A Comparative Assessment of Risk and Turnaround Time

Background

Digital morphology (DM) analyzers are increasingly being used for white blood cell (WBC) differentials. We assessed the laboratory efficiency of the Sysmex DI-60 system (DI-60; Sysmex, Kobe, Japan) in comparison with manual counting in leukopenic samples.

Methods

In total, 40 peripheral blood smear samples were divided into normal, mild leukopenia, moderate leukopenia, and severe leukopenia groups based on WBC count. In each group, the risk and turnaround time (TAT) were compared between DI-60 and manual counting. Risk was determined by failure mode and effect analysis using the risk priority number (RPN) score, and TAT was recorded for the analytical phase.

Results

Overall, DI-60 showed a five-fold lower risk (70 vs. 350 RPN) and longer TAT than manual counting. In severe leukopenic samples, DI-60 showed a shorter TAT/slide and a remarkably lower cell count/slide than manual counting. In all samples, the TAT/cell for DI-60 was substantially longer than that for manual counting (DI-60 vs. manual total, 1.8 vs. 1.0 sec; normal, 1.5 vs. 0.7 sec; mild leukopenia, 1.9 vs. 0.9 sec; moderate leukopenia, 1.8 vs. 1.0 sec; severe leukopenia, 28.8 vs. 19.0 sec).

Conclusions

This is the first comparative assessment of risk and TAT between DI-60 and manual counting in leukopenic samples. DI-60 decreases the laboratory risk and improves patient safety, but requires more time to count fewer cells, especially in severe leukopenic samples. DM analyzers should be applied selectively depending on the WBC count to optimize laboratory efficiency.

Identification of Anemia and Its Severity Level in a Peripheral Blood Smear Using 3-Tier Deep Neural Network

The automatic detection of blood cell elements for identifying morphological deformities is still a challenging research domain. It has a pivotal role in cognition and detecting the severity level of disease. Using a simple microscope, manual disease detection, and morphological disorders in blood cells is mostly time-consuming and erroneous. Due to the overlapped structure of RBCs, pathologists face challenges in differentiating between normal and abnormal cell shape and size precisely. Currently, convolutional neural network-based algorithms are effective tools for addressing this issue. Existing techniques fail to provide effective anemia detection, and severity level prediction due to RBCs’ dense and overlapped structure, non-availability of standard datasets related to blood diseases, and severity level detection techniques. This work proposed a three tier deep convolutional fused network (3-TierDCFNet) to extract optimum morphological features and identify anemic images to predict the severity of anemia. The proposed model comprises two modules: Module-I classifies the input image into two classes, i.e., Healthy and Anemic, while Module-II detects the anemia severity level and categorizes it into Mild or Chronic. After each tier’s training, a validation function is employed to reduce the inappropriate feature selection. To authenticate the proposed model for healthy, anemic RBC classification and anemia severity level detection, a state-of-the-art anemic and healthy RBC dataset was developed in collaboration with Shaukat Khanum Hospital and Research Center (SKMCH&RC), Pakistan. To evaluate the proposed model, the training, validation, and test accuracies were computed along with recall, F1-Score, and specificity. The global results reveal that the proposed model achieved 91.37%, 88.85%, and 86.06% training, validation, and test accuracies with 98.95%, 98.12%, and 98.12% recall F1-Score and specificity, respectively.

The Impact of Total Automaton on the Clinical Laboratory Workforce: A Case Study

Background

There has been a significant concern that total automation can decrease the need for laboratory personnel at all levels. The objective of this study was to investigate the impact of total laboratory automation on the clinical laboratory workforce.

Methods

A one-year data including the demographical features of laboratory workforce and technical productivity of laboratory tests were provided by two medical laboratory departments of similar profile and different equipment setup; one adopting a total automation system and the other utilizing discrete analysis system. The technical productivities of the two laboratories were compared and statistically tested.

Results

A similar technical productivity per single laboratory worker was noted in the hematology section in each of the two sites with no significant difference (average odd radio = 0.9, p = 0.79). However, with total automation, the number of tests performed per single worker has increased to an average of 1.4 and 3.7 times with total automation in the clinical chemistry and serology sections, respectively (p ≤ 0.001).

Conclusion

Total laboratory automation improves the productivity of the laboratory, leading to a decreased laboratory workforce. The laboratory workload has increased steadily therefore, the existing laboratory workforce, in the absence of automation, could not have been able to maintain the current volume of service. Adoption of automation reduces repetitive manual labor, thereby allowing the redefinition of the job roles of the laboratory workforce. TLA is ideal for laboratories that suffer from workforce shortages or managing high volume testing with less staff.

New Analytical Approach for the Alignment of Different HE4 Automated Immunometric Systems: An Italian Multicentric Study

Human epididymal secretory protein 4 (HE4) elevation has been studied as a crucial biomarker for malignant gynecological cancer, such us ovarian cancer (OC). However, there are conflicting reports regarding the optimal HE4 cut-off. Thus, the goal of this study was to develop an analytical approach to harmonize HE4 values obtained with different laboratory resources. To this regard, six highly qualified Italian laboratories, using different analytical platforms (Abbott Alinity I, Fujirebio Lumipulse G1200 and G600, Roche Cobas 601 and Abbott Architett), have joined this project. In the first step of our study, a common reference calibration curve (designed through progressive HE4 dilutions) was tested by all members attending the workshop. This first evaluation underlined the presence of analytical bias in different devices. Next, following bias correction, we started to analyze biomarkers values collected in a common database (1509 patients). A two-sided p-value < 0.05 was considered statistically significant. In post-menopausal women stratified between those with malignant gynecological diseases vs. non-malignant gynecological diseases and healthy women, dichotomous HE4 showed a significantly better accuracy than dichotomous Ca125 (AUC 0.81 vs. 0.74, p = 0.001 for age ≤ 60; AUC 0.78 vs. 0.72, p = 0.024 for age > 60). Still, in post-menopausal status, similar results were confirmed in patients with malignant gynecological diseases vs. patients with benign gynecological diseases, both under and over 60 years (AUC 0.79 vs. 0.73, p = 0.006; AUC 0.76 vs. 0.71, p = 0.036, respectively). Interestingly, in pre-menopausal status women over 40 years, HE4 showed a higher accuracy than Ca125 (AUC 0.73 vs. 0.66, p = 0.027), thus opening new perspective for the clinical management of fertile patients with malignant neoplasms, such as ovarian cancer. In summary, this model hinted at a new approach for identifying the optimal cut-off to align data detected with different HE4 diagnostic tools.

An Open-Source Modular Framework for Automated Pipetting and Imaging Applications

The number of samples in biological experiments is continuously increasing, but complex protocols and human error in many cases lead to suboptimal data quality and hence difficulties in reproducing scientific findings. Laboratory automation can alleviate many of these problems by precisely reproducing machine-readable protocols. These instruments generally require high up-front investments, and due to the lack of open application programming interfaces (APIs), they are notoriously difficult for scientists to customize and control outside of the vendor-supplied software. Here, automated, high-throughput experiments are demonstrated for interdisciplinary research in life science that can be replicated on a modest budget, using open tools to ensure reproducibility by combining the tools OpenFlexure, Opentrons, ImJoy, and UC2. This automated sample preparation and imaging pipeline can easily be replicated and established in many laboratories as well as in educational contexts through easy-to-understand algorithms and easy-to-build microscopes. Additionally, the creation of feedback loops, with later pipetting or imaging steps depending on the analysis of previously acquired images, enables the realization of fully autonomous "smart" microscopy experiments. All documents and source files are publicly available to prove the concept of smart lab automation using inexpensive, open tools. It is believed this democratizes access to the power and repeatability of automated experiments.

Total Laboratory Automation for Rapid Detection and Identification of Microorganisms and Their Antimicrobial Resistance Profiles

At a time when diagnostic bacteriological testing procedures have become more complex and their associated costs are steadily increasing, the expected benefits of Total laboratory automation (TLA) cannot just be a simple transposition of the traditional manual procedures used to process clinical specimens. In contrast, automation should drive a fundamental change in the laboratory workflow and prompt users to reconsider all the approaches currently used in the diagnostic work-up including the accurate identification of pathogens and the antimicrobial susceptibility testing methods. This review describes the impact of TLA in the laboratory efficiency improvement, as well as a new fully automated solution for AST by disk diffusion testing, and summarizes the evidence that implementing these methods can impact clinical outcomes.

Review of Scavenged Sampling for Sustainable Therapeutic Drug Monitoring: Do More With Less

PURPOSE

Innovative and sustainable sampling strategies for bioanalytical quantification of drugs and metabolites have gained considerable interest. Scavenging can be stratified as a sustainable sampling strategy using residual material because it aligns with the green principles of waste reduction and sampling optimization. Scavenged sampling includes all biological fluids' (eg, blood, liquor, and urine) leftover from standard clinical care. This review elaborates on the past and current landscape of sustainable sampling within therapeutic drug monitoring, with a focus on scavenged sampling.

METHODS

In February 2021, 4 databases were searched to assess the literature on the clinical use of innovative and sustainable sampling techniques without applying publication date restrictions. Studies reporting the clinical use of scavenged blood sampling and bridging studies of scavenged sampling and normal blood sampling were eligible for inclusion.

RESULTS

Overall, 19 eligible studies concerning scavenged sampling were identified from 1441 records. Scavenged sampling is mainly applied in the pediatric population, although other patient groups may benefit from this strategy. The infrastructure required for scavenged sampling encounters several challenges, including logistic hurdles, storage and handling conditions, and documentation errors. A workflow is proposed with identified opportunities that guide the implementation of scavenged sampling.

CONCLUSIONS

This review presents current evidence on the clinical use of scavenged sampling strategies. Scavenged sampling can be a suitable approach for drug quantification to improve dosage regimens, perform pharmacokinetic studies, and explore the value of therapeutic drug monitoring without additional sample collection.

Economic Evaluation of Total Laboratory Automation in the Clinical Laboratory of a Tertiary Care Hospital

Background

Total laboratory automation (TLA) is an innovation in laboratory technology; however, the high up-front costs restrict its widespread adoption. To examine whether the capital investment for TLA is worthwhile, we analyzed its clinical- and cost-effectiveness for the expected payback period.

Methods

Clinical chemistry tests and immunoassays performed in the clinical laboratory of a tertiary care hospital were divided into a post-TLA group, including 1,182,419 tests performed during December 2019, and a pre-TLA group, including 1,151,501 tests performed during December 2018. Laboratory information system data were used to measure clinical effectiveness, and depreciation data were used to calculate TLA costs.

Results

Laboratory performance improved after TLA adoption in all four key performance indicators mean turn-around time (TAT), representing the timeliness of result reporting, decreased by 6.1%; the 99th percentile of TAT, representing the outlier rate, decreased by 13.3%; the TAT CV, representing predictability, decreased by 70.0%; and weighted tube touch moment (wTTM), representing staff safety, improved by 77.6%. Based on these effectiveness results, economic evaluation was performed using two approaches. First, the incremental cost-effectiveness ratio and wTTM were used as the most cost-effective performance indicators. Second, the expected payback period was calculated. Considering only staff cost reduction, it was anticipated that 4.75 yrs would be needed to payback the initial investment.

Conclusions

TLA can significantly enhance laboratory performance, has a relatively quick payback period, and can reduce total hospital expenses in the long term. Therefore, the capital investment for TLA adoption is considered to be worthwhile.

Current State of Laboratory Automation in Clinical Microbiology Laboratory

BACKGROUND

Although it has been 30 years since the first automation systems were introduced in the microbiology laboratory, total laboratory automation (TLA) has only recently been recognized as a valuable component of the laboratory. A growing number of publications illustrate the potential impact of automation. TLA can improve standardization, increase laboratory efficiency, increase workplace safety, and reduce long-term costs.

CONTENT

This review provides a preview of the current state of automation in clinical microbiology and covers the main developments during the last years. We describe the available hardware systems (that range from single function devices to multifunction workstations) and the challenging alterations on workflow and organization of the laboratory that have to be implemented to optimize automation.

SUMMARY

Despite the many advantages in efficiency, productivity, and timeliness that automation offers, it is not without new and unique challenges. For every advantage that laboratory automation provides, there are similar challenges that a laboratory must face. Change management strategies should be used to lead to a successful implementation. TLA represents, moreover, a substantial initial investment. Nevertheless, if properly approached, there are a number of important benefits that can be achieved through implementation of automation in the clinical microbiology laboratory. Future developments in the field of automation will likely focus on image analysis and artificial intelligence improvements. Patient care, however, should remain the epicenter of all future directions and there will always be a need for clinical microbiology expertise to interpret the complex clinical and laboratory information.

Integrating Scalable Genome Sequencing Into Microbiology Laboratories for Routine Antimicrobial Resistance Surveillance

Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.

Total lab automation: sample stability of clinical chemistry parameters in an automated storage and retrieval module

OBJECTIVES

Automated storage and retrieval modules (SRM), as part of total lab automation (TLA) systems, offer tremendous practical and economic benefits. In contrast to manual storage systems, SRMs indicate continuous motion of samples and may leave samples prone to temperature fluctuations. This study investigates analyte stability in serum and heparin plasma within an automated storage module.

METHODS

The stability of 28 common biochemistry analytes was investigated using 57 freshly obtained routine serum samples and 42 lithium-heparin plasma samples. Following baseline measurement, samples were stored at 2-8 °C in the automated SRM of the Accelerator a3600 TLA and reanalyzed at fixed time points (2, 4, 8, 12, 24, 48 and 72 h) on the Abbott Architect c16000 chemistry analyzer. The concentration at each time point was expressed as %-difference to the baseline value and mean results were compared to the criteria for desirable bias derived from the biological variation database.

RESULTS

Nine of the analytes exceeded the bias criterion within 72 h after initial measurement in either serum samples, plasma samples or both. Lithium-heparin plasma samples showed increasing values for phosphor, potassium and lactate dehydrogenase (LDH), which were only considered stable for respectively 24, 12 and 4 h, glucose was considered stable for 8 h. Electrolyte concentrations and LDH activity significantly increased in serum samples beyond 48 h. Bicarbonate should not be performed as add-on test at all.

CONCLUSIONS

The presented data indicate that the conditions within an SRM have no clinical impact on sample stability and allow stable measurement of routine analytes within 72 h, comparable to manual storage facilities.

eLabFTW as an Open Science tool to improve the quality and translation of preclinical research

Reports of non-replicable research demand new methods of research data management. Electronic laboratory notebooks (ELNs) are suggested as tools to improve the documentation of research data and make them universally accessible. In a self-guided approach, we introduced the open-source ELN eLabFTW into our life-science lab group and, after using it for a while, think it is a useful tool to overcome hurdles in ELN introduction by providing a combination of properties making it suitable for small life-science labs, like ours. We set up our instance of eLabFTW, without any further programming needed. Our efforts to embrace open data approach by introducing an ELN fits well with other institutional organized ELN initiatives in academic research and our goals towards data quality management.

Automation in small labs

Objectives

The following report describes the development and implementation of a small-lab automation solution for small hospitals.

Methods

It uses a new generation of collaborative robots instead of the traditional laboratory automation lines with their input and output units and connected analyzers. After the Proof of Concept during fall 2018, both a centrifuge and several routine analyzers were integrated.

Results

The run-up phase ended after successful test operations in continuous mode in 2019. Routine operations were launched in October 2020 in a MVZ routine lab after a delay caused by the pandemic.

Conclusions

Apart from the direct cost savings for night duty or compensation for the lack of personnel, the mentioned solution delivers a significant upgrading of the laboratory technicians’ activities and an improvement in their working conditions.

Mass spectrometry and total laboratory automation: opportunities and drawbacks

The diffusion of laboratory automation, initiated nearly 50 years ago with consolidation of preanalytical, clinical chemistry and immunochemistry workstations, is now also gradually embracing mass spectrometry (MS). As for other diagnostic disciplines, the automation of MS carries many advantages, such as efficient personnel management (i.e. improving working atmosphere by decreasing manual activities, lowering health risks, simplifying staff training), better organization (i.e. reducing workloads, improving inventory handling, increasing analytical process standardization) and the possibility to reduce the number of platforms. The development and integration of different technologies into automated MS analyzers will also generate technical and practical advantages, such as prepackaged and ready-to-use reagents, automated dispensing, incubation and measurement, automated sample processing (e.g. system fit for many models of laboratory automation, bar code readers), multiplex testing, automatic data processing, also including quality control assessment, and automated validation/interpretation (e.g. autoverification). A new generation of preanalytical workstations, which can be directly connected to MS systems, will allow the automation of manual extraction and elimination of time-consuming activities, such as tube labeling and capping/decapping. The use of automated liquid-handling platform for pipetting samples, along with addition of internal standards, may then enable the optimization of some steps of extraction and protein precipitation, thus decreasing turnaround time and increasing throughput in MS testing. Therefore, this focused review is aimed at providing a brief update on the importance of consolidation and integration of MS platforms in laboratory automation.