Stochastic simulation software is developed and used to calculate and visualize the detection power of complex QC rule combinations, including traditional Westgard rules as well as statistical tests of multiple QC repeats, with arbitrary degrees of multiplexing and levels of control.
Accessible molecular diagnostics is fundamental to effective healthcare. While most current point-of-care devices detect only the presence of a molecular biomarker(s), biomarker quantification can be equally important for decision-making on disease treatment and containment. Here, we present a diagnostic platform that enables the equipment-free quantification of molecular biomarkers with the simplicity of a binary (yes/no) readout. This capability is achieved by integrating a stoichiometric quantitative approach with widely available and easy-to-use lateral flow dipsticks. To implement the approach, we engineer negative cooperativity into target–probe binding interactions for oligonucleotide targets as a model system. The resulting threshold-based semi-quantitative assay with lateral flow dipsticks quantifies targets in the low-nanomolar range and operates reliably in complex biological backgrounds. A key advantage of this platform is its potential adaptability to new and emerging targets: repurposing will require only reagent redesign, without the need for additional fabrication.
Baseline IQC practices for emergency immunoassays in the surveyed laboratories were inconsistent and lacked a standardized risk-based foundation, and it is recommended that clinical laboratories implement individualized RB-SQC protocols designed using the Westgard Sigma Rule with Run Length nomogram, and periodically reassess their appropriateness based on updated sigma metrics.
Guangjun Xiao, Juan Hu, Yanting Liu et al.· Frontiers in Medicine· 0 citations
Some of the recent work on dPCR-based RMPs are described and how this can be applied to improve nucleic acid analysis measurements on a global scale in EQA schemes, clinical laboratories and harmonization studies for infectious disease diagnostics are discussed.
S. Falak, D. O'Sullivan, Megan H. Cleveland et al.· 150th anniversary of the Met...· 0 citations
Accurate and comparable quantification of somatic mutations is essential for precision oncology, as clinical decision-making increasingly relies on the quantification of molecular biomarkers. Despite major technological advances, inter-laboratory variability and the lack of metrological traceability remain significant barriers to harmonization and confidence in mutation testing results. Reference Measurement Procedures (RMPs) represent a critical framework to address these challenges by anchoring molecular measurements to common quantitative standards. Here, we describe the development and validation of a candidate RMP for the detection and quantification of the clinically relevant NRAS p.Q61R mutation using digital PCR (dPCR). The assay was systematically optimized to maximize specificity and minimize cross-reactivity between wild-type and mutant alleles. Analytical characterization demonstrated excellent linearity across a broad range of variant allele frequencies (vAF), with a limit of detection of 0.1 %. Precision studies performed on commercially available circulating tumour DNA reference materials (RM) showed good repeatability and intermediate precision, while a full measurement uncertainty budget confirmed the robustness of the approach. Comparison with a commercial dPCR assay provided independent support for assay comparability and consistent vAF estimates across the investigated range. Preliminary inter-laboratory assessment supported transferability of the candidate RMP and comparability of the resulting measurements. Overall, this work establishes a metrologically characterized and transferable dPCR-based RMP for NRAS p.Q61R quantification. Its implementation can support the harmonization of molecular measurements, the value assignment of RM, and the alignment of routine and secondary methods, thereby strengthening the reliability of quantitative biomarker assessment in precision oncology.
Jessica Petiti, Sabrina Caria, L. Revel et al.· Methods· 0 citations