RNA Drugs and RNA Targets for Small Molecules: Principles, Progress, and Challenges.

RNA-based therapies, including RNA molecules as drugs and RNA-targeted small molecules, offer unique opportunities to expand the range of therapeutic targets. Various forms of RNAs may be used to selectively act on proteins, transcripts, and genes that cannot be targeted by conventional small molecules or proteins. Although development of RNA drugs faces unparalleled challenges, many strategies have been developed to improve RNA metabolic stability and intracellular delivery. A number of RNA drugs have been approved for medical use, including aptamers (e.g., pegaptanib) that mechanistically act on protein target and small interfering RNAs (e.g., patisiran and givosiran) and antisense oligonucleotides (e.g., inotersen and golodirsen) that directly interfere with RNA targets. Furthermore, guide RNAs are essential components of novel gene editing modalities, and mRNA therapeutics are under development for protein replacement therapy or vaccination, including those against unprecedented severe acute respiratory syndrome coronavirus pandemic. Moreover, functional RNAs or RNA motifs are highly structured to form binding pockets or clefts that are accessible by small molecules. Many natural, semisynthetic, or synthetic antibiotics (e.g., aminoglycosides, tetracyclines, macrolides, oxazolidinones, and phenicols) can directly bind to ribosomal RNAs to achieve the inhibition of bacterial infections. Therefore, there is growing interest in developing RNA-targeted small-molecule drugs amenable to oral administration, and some (e.g., risdiplam and branaplam) have entered clinical trials. Here, we review the pharmacology of novel RNA drugs and RNA-targeted small-molecule medications, with a focus on recent progresses and strategies. Challenges in the development of novel druggable RNA entities and identification of viable RNA targets and selective small-molecule binders are discussed. SIGNIFICANCE STATEMENT: With the understanding of RNA functions and critical roles in diseases, as well as the development of RNA-related technologies, there is growing interest in developing novel RNA-based therapeutics. This comprehensive review presents pharmacology of both RNA drugs and RNA-targeted small-molecule medications, focusing on novel mechanisms of action, the most recent progress, and existing challenges.

Determination of acyclovir and its metabolite 9-carboxymethoxymethylguanide in human serum by ultra-high-performance liquid chromatography-tandem mass spectrometry.

A simple and rapid ultra-high-performance liquid chromatography coupled with mass spectrometry method was developed for acyclovir and its metabolite 9-carboxymethoxymethylguanine in human serum. After precipitation of serum samples with 0.1% formic acid in acetonitrile/methanol (40:60, v/v), components were separated on a Luna Omega C18 column (1.6 µm; 2.1 × 150 mm) at 40°C. Mobile phase A (2 mmol/L ammonium acetate, 0.1% formic acid in 5% acetonitrile, v/v/v) and mobile phase B (2 mmol/L ammonium acetate, 0.1% formic acid in 95% acetonitrile, v/v/v) were used for gradient elution. A linear calibration curve was obtained over the range of 0.05-50 mg/L, and the correlation coefficients were better than 0.999. The limit of quantitation was 0.05 mg/L for both analytes. The intra- and interday accuracy and precision at three concentration levels ranged between 1.6 and 13.3%, and recoveries were achieved with a range between 92.2 and 114.2%. This method was developed and validated for the therapeutic monitoring of acyclovir in patients.

Practical application of Westgard Sigma rules with run size in analytical biochemistry processes in clinical settings.

BACKGROUND: The performance of 18 routine chemical detection methods was evaluated by the sigma (σ) metric, and Westgard Sigma rules with run size were used to establish internal quality control (IQC) standards to reduce patient risks. MATERIALS AND METHODS: External quality assessment (EQA) and internal quality control data from 18 assays in a biochemical laboratory were collected from January to June 2020. The sigma values of each assay were calculated, based on the bias, total error allowable, and coefficient of variation, appropriate quality control rules were selected. According to the quality goal index, the main causes of poor performance were determined to guide quality improvement. RESULTS: At IQC material level 1, seven of the 18 assays achieved five sigma (excellent), and five assays (UA, Crea, AMY, TC and Na) showed world-class performance. At IQC material level 2, 14 of the 18 assays achieved 5 sigma (excellent), and thirteen assays (UA, ALT, CK, Crea, AMY, K, AST, ALP, Na, LDH, Mg, TC and GGT) showed world-class performance. The quality goal index (QGI) was calculated for items with analysis performance <5 sigma, and the main causes of poor performance were determined to guide quality improvement. CONCLUSIONS: Westgard sigma rules with run size are an effective tool for evaluating the performance of biochemical assays. These rules can be used to more simply and intuitively select the quality control strategy of related items and reduce the risk to patients.

Standardized production of a homogeneous latex enzyme source overcoming seasonality and microenvironmental variables.

Calotropis procera produces a milky sap containing proteolytic enzymes. At low concentrations, they induce milk-clotting (60 µg/ml) and to dehair hides (0.05 and 0.1%). A protocol for obtaining the enzymes is reported. The latex was mixed with distilled water and the mixture was cleaned through centrifugation. It was dialyzed with distilled water and centrifuged again to recover the soluble fraction [EP]. The dialyze is a key feature of the process. EP was characterized in terms of protein profile, chemical stability, among other criteria. Wild plants belonging to ten geographic regions and grown in different ecological conditions were used as latex source. Collections were carried out, spaced at three-month, according to the seasons at the site of the study. Proteolytic activity was measured as an internal marker and for determining stability of the samples. EP was also analyzed for metal content and microbiology. EP showed similar magnitude of proteolysis, chromatographic and electrophoretic profiles of proteins. Samples stored at 25 °C exhibited reduced solubility (11%) and proteolytic capacity (11%) after six months. Enzyme autolysis was negligible. Microbiological and metal analyses revealed standard quality of all the samples tested. EP induced milk clotting and hide dehairing after storage for up to six months.

Basal serum luteinising hormone cut-off, and its utility and cost-effectiveness for aiding the diagnosis of the onset of puberty in girls with early stages of breast development.

OBJECTIVE: To determine basal and gonadotrophin-releasing hormone analogue (GnRHa)-stimulated peak luteinising hormone (LH) cut-offs to diagnose onset of early or normal puberty in girls with each Tanner stage of breast (II and III). DESIGN, PATIENTS AND MEASUREMENTS: A retrospective study of 601 girls with breast onset before 8 years of age who underwent GnRHa test was conducted. Patients were categorized as CPP and premature thelarche. Each group was divided into two subgroups; Tanner II and III. Cost-effectiveness analysis was performed. RESULTS: In comparison with basal LH cut-off of 0.3 IU/L, basal LH cut-off of 0.2 IU/L had comparable specificity (Tanner II: 98.0% vs 94.8%, Tanner III: 98.8% vs 93.8%), but greater sensitivity (Tanner II: 28.3% vs 41.7%, Tanner III: 45.2% vs 59.3%). Specificity of basal LH cut-off of 0.2 IU/L was not inferior to that of the traditionally used peak LH of 5 IU/L. Using basal LH cut-off of 0.2 IU/L followed by GnRHa test in girls with negative basal LH was more cost-saving when compared with using the cut-off of 0.3 IU/L. Moreover, using basal LH cut-off of 0.2 IU/L followed by GnRHa test provided a cost reduction when compared with performing GnRHa test in all patients. CONCLUSIONS: Basal serum LH cut-off of 0.2 IU/L could be a simple and cost-saving tool for initial diagnosis of onset of early or normal puberty in girls with Tanner II and III before proceeding to GnRH testing.

Reference-mean-centered statistical quality control.

Background: Statistical quality control (SQC) procedures generally use rejection limits centered on the stable mean of the results obtained for a control material by the analyzing instrument. However, for instruments with significant bias, re-centering the limits on a different value could improve the control procedures from the viewpoint of patient safety. Methods: A statistical model was used to assess the effect of shifting the rejection limits of the control procedure relative to the instrument mean on the number of erroneous results reported as a result of an increase in the systematic error of the measurement procedure due to an out-of-control condition. The behaviors of control procedures of type 1ks (k = 2, 2.5, 3) were studied when applied to analytical processes with different capabilities (σ = 3, 4, 6). Results: For measuring instruments with bias, shifting the rejection limits in the direction opposite to the bias improves the ability of the quality control procedure to limit the risk posed to patients in a systematic out-of-control condition. The maximum benefit is obtained when the displacement is equal to the bias of the instrument, that is, when the rejection limits are centered on the reference mean of the control material. The strategy is sensitive to error in estimating the bias. Shifting the limits more than the instrument's bias disproportionately increases the risk to patients. This effect should be considered in SQC planning for systems running the same test on multiple instruments. Conclusions: Centering the control rule on the reference mean is a potentially useful strategy for SQC planning based on risk management for measuring instruments with significant and stable uncorrected bias. Low uncertainty in estimating bias is necessary for this approach not to be counterproductive.

The new IVD Regulation 2017/746: a case study at a large university hospital laboratory in Belgium demonstrates the need for clarification on the degrees of freedom laboratories have to use lab-developed tests to improve patient care.

Objectives: The new European In Vitro Diagnostic (IVD) Regulation 2017/746 (IVDR) restricts the use of lab-developed tests (LDT) after 26th May 2022. There are no data on the impact of the IVDR on laboratories in the European Union. Methods: Laboratory tests performed in UZ Leuven were divided in four groups: core laboratory, immunology, special chemistry, and molecular microbiology testing. Each test was classified as Conformité Européenne (CE)-IVD, modified/off-label CE-IVD, commercial Research Use Only (RUO) or LDT. Each matrix was considered a separate test. Results: We found that 97.6% of the more than 11.5 million results/year were generated with a CE-IVD method. Of the 922 different laboratory tests, however, only 41.8% were CE-IVD, 10.8% modified/off-label CE-IVD, 0.3% RUO, and 47.1% LDT. Off-label CE-IVD was mainly used to test alternative matrices not covered by the claim of the manufacturer (e.g., pleural or peritoneal fluid). LDTs were mainly used for special chemistry, flow cytometry, and molecular testing. Excluding flow cytometry, the main reasons for the use of 377 LDTs were lack of a CE-IVD method (71.9%), analytical requirements (14.3%), and the fact the LDT was in use before CE-IVD available (11.9%). Conclusions: While the large majority of results (97.6%) were generated with a CE-IVD method, only 41.8% of laboratory tests were CE-IVD. There is currently no alternative on the market for 71.5% of the 537 LDTs performed in our laboratory which do not fall within the scope of the current IVD directive (IVDD). Compliance with the IVDR will require a major investment of time and effort.

Are 2D fingerprints still valuable for drug discovery?

Recently, molecular fingerprints extracted from three-dimensional (3D) structures using advanced mathematics, such as algebraic topology, differential geometry, and graph theory have been paired with efficient machine learning, especially deep learning algorithms to outperform other methods in drug discovery applications and competitions. This raises the question of whether classical 2D fingerprints are still valuable in computer-aided drug discovery. This work considers 23 datasets associated with four typical problems, namely protein-ligand binding, toxicity, solubility and partition coefficient to assess the performance of eight 2D fingerprints. Advanced machine learning algorithms including random forest, gradient boosted decision tree, single-task deep neural network and multitask deep neural network are employed to construct efficient 2D-fingerprint based models. Additionally, appropriate consensus models are built to further enhance the performance of 2D-fingerprint-based methods. It is demonstrated that 2D-fingerprint-based models perform as well as the state-of-the-art 3D structure-based models for the predictions of toxicity, solubility, partition coefficient and protein-ligand binding affinity based on only ligand information. However, 3D structure-based models outperform 2D fingerprint-based methods in complex-based protein-ligand binding affinity predictions.

Improving the performance of the MM/PBSA and MM/GBSA methods in recognizing the native structure of the Bcl-2 family using the interaction entropy method.

In the research and development of new drugs, theoretical and computational studies play an increasingly important role in discriminating native and decoy structures by their binding free energies. Predicting the binding free energy using the molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) methods to identify the native structure as the lowest-energy conformation is more theoretically rigorous than most scoring functions, but the main challenge of this method is the calculation of the entropic contribution. In this study, we add the entropic contribution to the MM/PBSA and two MM/GBSA (GBHCT and GBOBC1) models using the interaction entropy (IE) method. We then systemically evaluate the performance of these methods in recognizing the native structures by predicting the binding affinities of 176 protein-ligand and protein-protein systems of the Bcl-2 family. By calculating a series of statistical metrics, sensitivity, specificity, accuracy, Matthews correlation coefficient, the G-mean, and the receiver operating characteristic (ROC) curve, we find that the ability to discern the native structure from a decoy ensemble is improved significantly by the modification of the binding free energy using the IE method in both protein-ligand and protein-protein systems. Furthermore, the maximum area under the ROC curve (AUC) was 0.97, which was obtained by the GBHCT model combined with the IE method, indicating that this method has the best performance. The largest improvement occurs in the PB method, with a change in the AUC of 0.32. The modification of the energy is more obvious for protein-protein interactions than for protein-ligand interactions. This study indicates the effectiveness of the IE method in successfully recognizing the native structure, which is critical in rational drug design.

The Automation Technique Lab-In-Syringe: A Practical Guide.

About eight years ago, a new automation approach and flow technique called "Lab-In-Syringe" was proposed. It was derived from previous flow techniques, all based on handling reagent and sample solutions in a flow manifold. To date Lab-In-Syringe has evidently gained the interest of researchers in many countries, with new modifications, operation modes, and technical improvements still popping up. It has proven to be a versatile tool for the automation of sample preparation, particularly, liquid-phase microextraction approaches. This article aims to assist newcomers to this technique in system planning and setup by overviewing the different options for configurations, limitations, and feasible operations. This includes syringe orientation, in-syringe stirring modes, in-syringe detection, additional inlets, and addable features. The authors give also a chronological overview of technical milestones and a critical explanation on the potentials and shortcomings of this technique, calculations of characteristics, and tips and tricks on method development. Moreover, a comprehensive overview of the different operation modes of Lab-In-Syringe automated sample pretreatment is given focusing on the technical aspects and challenges of the related operations. We further deal with possibilities on how to fabricate required or useful system components, in particular by 3D printing technology, with over 20 different elements exemplarily shown. Finally, a short discussion on shortcomings and required improvements is given.

Simple Fabrication of Solid-Phase Microextraction with Surface-Coated Aluminum Foil for Enhanced Detection of Analytes in Biological and Clinical Samples by Mass Spectrometry.

Rapid detection of analytes in biological and clinical samples is highly desirable, and significant progress has been made with direct mass spectrometric (MS) analysis. Rapid and sensitive detection, however, remains a major challenge in direct analysis of raw samples. In this study, we described a simple, rapid, and efficient method for enhanced detection of analytes in complex samples, using surface-coated aluminum (Al) foil that was simply made with conductive resin for physical adhesion of functional particles. The surface-coated Al foils were used as a solid-phase microextraction (SPME) tip for rapid sampling of target analytes from raw samples and then applied as an electrospray ionization (ESI) tip to couple MS for sensitive detection. Our results show that surface-coated Al foil is highly effective for enhanced detection of analytes in complex samples with excellent analytical performances, including sensitivity, reproducibility, and linear ranges. Overall, this development enabled an extremely simplified protocol to integrate SPME and ESI that is expected to have a significant impact on rapid screening of raw samples.

Using the Analytical Target Profile to Drive the Analytical Method Lifecycle.

Quality by design (ICH-Topic Q8) requires a prospective summary of the desired quality characteristics of a drug product. This is known as the Quality Target Product Profile (QTPP), which forms the basis for the design and development of the product. An analogous term has been established for analytical procedures called the Analytical Target Profile (ATP). The ATP, in a similar fashion to the QTPP, prospectively summarizes the requirements associated with a measurement on a quality attribute which needs to be met by an analytical procedure. Criteria defined in the ATP relate to the maximum uncertainty associated with the reportable result that is required to maintain acceptable confidence in the quality decision made from the result. The ATP is used to define and assess the fitness of an analytical procedure in the development phase and during all changes across the analytical lifecycle. One or more analytical procedures can meet the requirements of an ATP. The ATP can be applied to any quality attribute across any pharmaceutical modality where an analytical procedure is used to generate a reportable result, and this paper provides examples from three of these modalities: small molecules, oligonucleotides, and vaccines. Some key performance characteristics will be discussed for each ATP, namely specificity, accuracy, and precision, taking into account the expected range of the analyte. The combination of accuracy and precision into a combined uncertainty characteristic is also discussed as a more holistic approach. The use of the ATP concept will help focus attention on the properties of a method which impact quality decisions rather than method descriptions and may enable greater regulatory flexibility across the lifecycle using established conditions based on method performance criteria as proposed in the Step 2 version of ICHQ12. The revision of ICHQ2(R1) and development of the new ICHQ14 guideline (Analytical Procedure Development) will provide a golden opportunity to harmonize the definition of new QbD concepts such as the ATP.

Multi-site performance evaluation and Sigma metrics of 20 assays on the Atellica chemistry and immunoassay analyzers.

Background The Atellica Solution comprises chemistry (CH) and immunoassay (IM) analyzers. Recently, six early adopter clinical laboratories across Europe evaluated the analytical performance of 20 CH and IM assays. To measure analytical performance quality, Sigma metrics were calculated for individual-site and pooled-site results. Methods Precision, detection capability, linearity, and method comparison studies were performed according to Clinical Laboratory Standards Institute protocols. Global Sigma metrics across sites were calculated from pooled data at the medical decision level using total allowable error (TEa) goals from CLIA for CH assays, and TEa goals from RiliBÄK for IM assays; and, the equation: Sigma metrics=%TEa-%bias/%CV. A pooled %CV was calculated by combining the imprecision obtained from individual sites. Bias calculations were performed against the ADVIA Chemistry system or ADVIA Centaur system using Deming regression analysis (Passing-Bablok regression for electrolytes) on the pooled-site data. The 103 individual-site Sigma metric calculations used individual-site imprecision and pooled-bias. Results The limits of blank and detection results agreed with the manufacturer's claims. Most assays were linear across the assay range tested. Pooled Sigma metrics were good or better (>4 Sigma) for 18 of 20 assays; and, acceptable for urea nitrogen (3.1) and sodium (3.9), the latter values attributable to higher imprecision at one of five sites. Conclusions Sigma metrics for data generated across multiple real-world sites evaluating the Atellica Solution demonstrated good or better performance of greater than 4 Sigma for 18 of 20 assays tested. Overall, results verified the manufacturer's claims that methods were fit for use in clinical laboratories.

Elucidation of stability profiles of common chemistry analytes in serum stored at six graded temperatures.

Background Many reports address the stability of biochemical analytes in serum. However, studies covering a wide range of storage temperatures are unavailable. Using equipment enabling precise temperature control, we investigated the effect of six different storage temperatures on serum analytes. Methods Serum specimens from seven healthy volunteers were obtained and divided into multiple aliquots for storage at -30, -20, -10, 0, 4, and 25 °C. On days 1, 3, 7, 14, 28 and 56, the aliquots stored at each temperature were relocated to a deep freezer maintained at -80 °C. On day 60, all aliquots were measured collectively for 13 major chemistry analytes. Results (1) At 25 °C, alanine aminotransferase (ALT), creatine kinase (CK), aspartate aminotransferase (AST) and total bilirubin (TBil) were very unstable especially on day 7 and later. (2) At ≤4 °C, alkaline phosphatase (ALP), γ-glutamyltransferase (GGT), amylase (AMY), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglyceride (TG), TBil and complement component-4 (C4) were generally stable and were very stable at 25 °C until day 14. (3) Between -20 and 4 °C, especially at -10 °C, test results of ALT, AST and lactate dehydrogenase (LDH) showed prominent decreases, but their stability was greatly improved at -30 °C. (4) In contrast, the value of complement component-3 (C3) increased at ≥- 20 °C. (5) At -30 °C, test results of all analytes were generally very stable except for ALT and CK, which showed noticeable reductions in activity after 14 days. Conclusions This is the first study to assess the stability of serum analytes at six graded temperatures simultaneously. Each analyte has a unique stability pattern for a range of temperatures.

Quick temperature-sweep pure-shift NMR: the case of solvent effects in atorvastatin.

Pure-shift NMR experiments provide highly resolved spectra, which could be perfect for precise monitoring of chemical shift variations under different conditions, such as temperature or concentration. However, their sensitivity is relatively low and signal sampling is time-consuming, which leads to long experimental times, making such serial acquisition problematic. In this paper we present a new method of NMR spectroscopy which improves the speed and sensitivity of serial pseudo-two-dimensional pure-shift experiments. The example of variable-temperature study of atorvastatin reveals the potential of the method in verifying the theoretical predictions of solvent-dependent spectral effects.

Assessing the performance of the MM/PBSA and MM/GBSA methods. 10. Impacts of enhanced sampling and variable dielectric model on protein-protein Interactions.

Enhanced sampling has been extensively used to capture the conformational transitions in protein folding, but it attracts much less attention in the studies of protein-protein recognition. In this study, we evaluated the impact of enhanced sampling methods and solute dielectric constants on the overall accuracy of the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) approaches for the protein-protein binding free energy calculations. Here, two widely used enhanced sampling methods, including aMD and GaMD, and conventional molecular dynamics (cMD) simulations with two AMBER force fields (ff03 and ff14SB) were used to sample the conformations for 21 protein-protein complexes. The MM/PBSA and MM/GBSA calculation results illustrate that the standard MM/GBSA based on the cMD simulations yields the best Pearson correlation (rp = -0.523) between the predicted binding affinities and the experimental data, which is much higher than that given by MM/PBSA (rp = -0.212). Two enhanced sampling methods (aMD and GaMD) are indeed more efficient for conformational sampling, but they did not improve the binding affinity predictions for protein-protein systems, suggesting that the aMD or GaMD sampling (at least in short timescale simulations) may not be a good choice for the MM/PBSA and MM/GBSA predictions of protein-protein complexes. The solute dielectric constant of 1.0 is recommended to MM/GBSA, but a higher solute dielectric constant is recommended to MM/PBSA, especially for the systems with higher polarity on the protein-protein binding interfaces. Then, a preliminary assessment of the MM/GBSA calculations based on a variable dielectric generalized Born (VDGB) model was conducted. The results highlight the potential power of VDGB in the free energy predictions for protein-protein systems, but more thorough studies should be done in the future.

Interlaboratory comparison about feasibility of insoluble particulate matter test for injections with reduced test volume in light obscuration method.

Insoluble particulate matter test for injections in pharmacopoeia is mandatory for parenteral drug products. In this test using light obscuration, four measurements of at least 5-mL are required. Since therapeutic protein injections of low dosage volumes are getting more popular, reduction of test volumes is desired. In this collaborative study, the impact of lower measurement volume on the accuracy and precision of particle count was evaluated using 2, 5, 10, and 25-µm polystyrene count standards for the validity of test with reduced sample volumes. Good accuracy (3000 particles/mL ±â€¯10%) was obtained at all measurement volumes, and the inter-run variability (RSD) was the same levels between 5 and 1 mL. Although the inter-run variability increased at 0.2 mL, it was below 5%. These results indicated that light obscuration method can be used with 5 mL-0.2 mL, and that it is feasible for monitoring particles ≥2 µm.

Important issues in plant tissues analyses by HR-MAS NMR.

INTRODUCTION: High-resolution magic-angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy enables the analysis of the metabolic profile of plant and animal tissues under close to natural conditions, as well as of other heterogeneous natural or synthetic materials. Neither sample pretreatment is required after fragmentation nor powdering of the sample before insertion into the rotor. However, the efficiency of the method depends strongly on the sample preparation, rotor insertion procedure, and analysis conditions. OBJECTIVE: To identify some of the variables that affect the spectral data and to propose solutions that minimise their impact on the quality of the analyses and results. METHODS: Dried plant tissues were powdered, weighed, and homogenised in a 50 µL rotor with an optimised volume of deuterated solvent and sample in order to prevent material from escaping during spacer insertion, avoiding variations in magnetic susceptibility. Factors affecting the quality of HR-MAS NMR analysis such as particle size, sample and solvent amounts, solvent polarity, swelling time, rotor manipulation and pulse sequence setting were evaluated. RESULTS: A strong correlation was observed between the signal area and the particle size of the powdered sample. The spectral profile varied depending on the deuterated solvent used. An incubation period was necessary to achieve adequate swelling of the sample and to ensure good data reproducibility. Proper sealing of the rotor, number of cycles and τ time on cpmgpr1d pulse sequence were found to affect the signal areas. CONCLUSION: The study highlights the need for standardised sample preparation and instrumental setup protocols in order to achieve high reproducibility and obtain reliable data from HR-MAS NMR analyses.

Measurement uncertainty of γ-glutamyltransferase (GGT) in human serum by four approaches using different quality assessment data.

BACKGROUND: Measurement uncertainty (MU) characterizes the dispersion of the quantity values attributed to a measurand. Although this concept was introduced to medical laboratories some years ago, not all medical researchers are familiar with it. Therefore, the evaluation and expression of MU must be highlighted. In this paper, the evaluation of MU is described by using four different approaches from different quality assessment data. METHODS: In accordance with Guide to the Expression of Uncertainty of Measurement (GUM) principles, human serum γ-glutamyltransferase (GGT) level was defined as the measurand. Main sources of MU were analyzed; individual components of MU were evaluated, followed by calculation of standard uncertainty, the combined standard uncertainty and the expanded uncertainty. RESULTS: In method 1, the median of expanded uncertainty (k=2) of GGT in lower level (65±1 U/L) was 5 U/L (9%, 95% confidence interval) and in higher level (116±2 U/L) was 8% (95% confidence interval), respectively. The results of method 2 were lower than that of method 1. There were no significant differences between the two other methods compared with the method 1. CONCLUSIONS: Three out of the four different approaches based on different quality assessment data yielded similar results. Proficiency testing or external quality assessment data used for MU evaluation can be regarded as a supplementary method in clinical laboratory.

Results of the first external quality assessment scheme (EQA) for isolation and analysis of circulating tumour DNA (ctDNA).

BACKGROUND: Circulating tumour DNA (ctDNA) is considered to have a high potential for future management of malignancies. This pilot external quality assessment (EQA) scheme aimed to address issues of analytical quality in this new area of laboratory diagnostics. METHODS: The EQA scheme consisted of three 2-mL EDTA-plasma samples spiked with fragmented genomic DNA with a mutant allele frequency ranging from 0% to 10% dedicated to the analysis of nine known sequence variations in KRAS codon 12/13 and of BRAF V600E. Laboratories reported: (1) time elapsed for processing, (2) storage temperatures, (3) methods for extraction and quantification, (4) genotyping methodologies and (5) results. RESULTS: Specimens were sent to 42 laboratories from 10 European countries; 72.3% reported to isolate cell-free DNA (cfDNA) manually, 62.5% used the entire plasma volume for cfDNA isolation and 38.5% used >10% of cfDNA extracted for downstream genotyping. Of the methods used for quantification, PicoGreen demonstrated the lowest coefficient of variation (33.7%). For genotyping, 11 different methods were reported with the highest error rate observed for Sanger sequencing and the lowest for highly sensitive approaches like digital PCR. In total, 197 genotypes were determined with an overall error rate of 6.09%. CONCLUSIONS: This pilot EQA scheme illustrates the current variability in multiple phases of cfDNA processing and analysis of ctDNA resulting in an overall error rate of 6.09%. The areas with the greatest variance and clinical impact included specimen volume, cfDNA quantification method, and preference of genotyping platform. Regarding quality assurance, there is an urgent need for harmonisation of procedures and workflows.