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WO2025031642A1 - Procédé pour déterminer les erreurs d'exécution d'une méthode d'analyse pour la quantité d'une pluralité d'analytes dans une pluralité d'échantillons biologiques - Google Patents

Procédé pour déterminer les erreurs d'exécution d'une méthode d'analyse pour la quantité d'une pluralité d'analytes dans une pluralité d'échantillons biologiques Download PDF

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Publication number
WO2025031642A1
WO2025031642A1 PCT/EP2024/066810 EP2024066810W WO2025031642A1 WO 2025031642 A1 WO2025031642 A1 WO 2025031642A1 EP 2024066810 W EP2024066810 W EP 2024066810W WO 2025031642 A1 WO2025031642 A1 WO 2025031642A1
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sample
samples
reaction container
test reagent
test
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John BROBERG
Lei CONZE
Gil HENRIQUES
Nicole PAUL
Pascal PUCHOLT
Kristjan PULLERITS
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Olink Proteomics AB
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Olink Proteomics AB
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B99/00—Subject matter not provided for in other groups of this subclass
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis

Definitions

  • the present disclosure relates to a method for determining run errors for an analysismethod for quantifying a plurality of analytes in a plurality of biological samples.
  • Dual-recognition immunoassays build on a concept developed by Ulf Landegren and co-workers and described i.a. in Fredriksson et al., Nature Biotechnology, vol. 20, 2002, pp. 473-477 and WQ01/61037.
  • Dual-recognition immunoassay methods include Proximity Extension Assay (PEA), commercially available from Olink Proteomics AB (Uppsala, Sweden).
  • PEA Proximity Extension Assay
  • WO 03/044231 WO 2004/094456, WO 2005/123963, WO 2006/137932, WO 2013/113699, WO 2021/191442, WO 2021/191448, WO 2021/191449, WO 2021/191450, and WO 2022/112300
  • Lundberg et al. Molecular & Cellular Proteomics 10:10.1074/mcp.M110.004978, 1-10, 2011
  • Wik et al. 2021, Mol Cell Proteomics 20, 100168, all incorporated herein by reference in their entirety.
  • PLA Proximity Ligation Assay
  • RCA Rolling Circle Amplification
  • Duolink® A PLA-based method for multiplex detection of proteins is described in WO 2021/113290.
  • PEA and PLA are dual-recognition assays, which rely on the principle of "proximity probing".
  • an analyte is detected by the binding of multiple (i.e. two or more, generally two or three) probes, which when brought into proximity by binding to the analyte (hence “proximity probes") allow a signal to be generated.
  • the proximity probes comprises a nucleic acid domain (or moiety) linked to the analyte-binding domain (or moiety) of the probe, and generation of the signal involves an interaction between the nucleic acid moieties and/or a further functional moiety which is carried by the other probe(s).
  • signal generation is dependent on an interaction between the probes (more particularly between the nucleic acid or other functional moieties/domains carried by them) and hence only occurs when the necessary probes have bound to the analyte, thereby lending improved specificity to the detection system.
  • nucleic acid moieties linked to the analyte-binding domains of a probe pair hybridise to one another when the probes are in close proximity (i.e. when bound to the same target molecule), and are then extended using a nucleic acid polymerase.
  • the extension product forms a reporter nucleic acid, detection of which demonstrates the presence of a particular analyte (the analyte bound by the relevant probe pair) in a sample of interest.
  • nucleic acid moieties linked to the analyte-binding domains of a probe pair come into proximity when the probes of the probe pair bind their target, and may be ligated together, or alternatively they may together template the ligation of separately added oligonucleotides, which are able to hybridise to the nucleic acid domains when they are in proximity.
  • the ligation product is then amplified, acting as a reporter nucleic acid.
  • Multiplex analyte detection using PEA or PLA may be achieved by including one or more unique barcode sequences in the nucleic acid moiety of each probe.
  • Oligonucleotides comprising a barcode sequence unique to a specific sample may further be added to the respective sample and incorporated into all reporter molecules generated from that sample.
  • a reporter nucleic acid molecule corresponding to a particular analyte, and optionally a particular sample, may then be identified by the barcode sequences it contains.
  • the methods of the present invention find particular utility in multiplex PEA and PLA methods.
  • Panels of proximity assays are commercially available from Olink Proteomics AB (Uppsala, Sweden) under the trademark Olink® Target, Olink® Focus, Olink® Explore, and Olink® Flex. These are panels of up to 92 assays (Olink® Target, Olink® Focus and Olink® Flex) or up to ⁇ 3,000 assays split over eight different panels (Olink® Explore).
  • a panel may further be divided into a number, typically four, of "abundance blocks" and the samples may be diluted based on their predicted abundance prior to being incubated with the assay probes of the respective abundance block.
  • Each panel generally includes assays for proteins that have known functions within certain biological or physiological areas, pathways or organs in the body, such as inflammation, organ-specific proteins, cardiovascular, neurology etc. It is also possible for a user to select a specific combination of protein assays that are of particular interest to create a tailor-made panel.
  • Proximity based assays produce a number of reporter molecules with a certain barcode set-up, which number correlates to the amount of protein with the corresponding barcode. This number can be quantified by either quantitative Polymerase Chain Reaction (qPCR) or sequencing, preferably Next Generation Sequencing (NGS).
  • the qPCR produces a Ct value that corresponds to the amount of protein in the sample and NGS produces an actual number, called “counts", of reporter molecules and the counts correlate with the amount of protein in the sample.
  • Olink uses an arbitrary relative quantification unit called NPX that may be calculated with software adapted for use with the above panels.
  • a measure of relative protein quantity, such as NPX can be calculated from counts as described in Wik et al., cited above.
  • test reagents also known as internal controls
  • standardized samples also known as external controls
  • the test reagents used for QC are an incubation test reagent and an amplification test reagent.
  • the incubation test reagent comprises PEA probes measuring a fixed concentration of nonhuman green fluorescent protein (GFP), added to each sample.
  • the amplification test reagent consists of a synthetic double-stranded DNA template and is used in QC to monitor the PCR steps in the protocol.
  • Standardized samples used for QC comprise a blank sample (buffer only) run in triplicate, and standard samples, run in duplicate.
  • a standard sample is pooled plasma samples run in duplicates on each plate. These are used as standardized sample to estimate inter and intra precision for each assay.
  • a blank sample (also known as negative controls) comprises buffer run as a normal sample. Blank samples are used to monitor any background noise generated when DNA-tags come in close proximity without prior binding to the appropriate protein. The blank sample set the background levels for each protein assay and are used to calculate the limit of detection (LOD).
  • LOD limit of detection
  • test reagent is a reagent used to identify substances contained within a test sample.
  • a test plate sample comprises pooled plasma originating from healthy blood donors. Standard samples are used in data normalization to compensate potential variation between runs and plates.
  • the QC assessment is performed at two levels; run QC and sample QC. At the run QC level each of the abundance blocks for each panel and sample plate should fulfil the following criteria: (i) mean absolute deviation (MAD) in test reagents may not exceed a certain threshold of relative protein quantity (such as 0.3 NPX) and (ii) deviation on the sample QC level is allowed for a maximum of one out of six samples. Further, in each panel, the median of at least 90% of the assays in test plate sample and blank samples must be in the accepted range from predefined values set during validation.
  • CV coefficient of variation
  • a quality control method for determining run errors for an analysis-method for quantifying a plurality of analytes in a plurality of biological samples comprises: providing a plurality of samples in a plurality of reaction containers of a plate, wherein each sample is identified as a biological sample or a standardized sample, wherein a first plurality samples in a first set of reaction containers are identified as biological samples and a second plurality of samples in a second set of reaction containers are identified as standardized samples, wherein the samples identified as biological samples are samples under investigation and wherein the samples identified as standardized samples are further identified as either a standard sample, or a blank sample.
  • the method further comprises adding, to each of the plurality of samples, predetermined amounts of at least one test reagent; and adding assay reagents to each of the plurality of samples, wherein the assay reagents are configured to generate nucleic acid reporter molecules in an amount correlated to the amounts of analyte or test reagent in the plurality of samples, wherein each nucleic acid reporter molecule pertains to an analyzed sample among the plurality of samples and comprises identification sequences, the identification sequences comprises a first identification sequence identifying the reaction container of the analyzed sample and a second identification sequence uniquely identifying one of: the analyte or a test reagent from the one or more test reagents.
  • the quality control method comprises obtaining using the identification sequences of the nucleic acid reporter molecules, for each reaction container, a set of counts, the set of counts comprising a count for the amount of analyte reporter molecules detected in the reaction container; and for each test reagent of the at least one test reagent detected in the reaction container, a count for the amount of the test reagent specific reporter molecules corresponding to the test reagent.
  • the quality control method further comprises determining, for all reaction containers comprising a sample identified as a standardized sample, a mean count of the set of counts of the test reagent specific reporter molecules corresponding to any of the one or more test reagents, and upon a number of reaction containers comprising a sample identified as standardized sample, in which the count forthe amount of analyte reporter molecules detected in the reaction container exceeds the mean count, exceeds a second threshold, determining a run error for the plate.
  • This embodiment involves calculating the mean (e.g., average, or median) count of the test reagent-specific reporter molecules for all reaction containers containing standardized samples.
  • This mean count represents the mean number of reporter molecules detected for each test reagent across all standardized samples.
  • each reaction container identified a standardized sample is examined to determine if the count of analyte reporter molecules exceeds the calculated mean count. Specifically, the method identifies the reaction containers where the count of analyte reporter molecules is higher than the mean count. The number of these reaction containers is then compared to a predefined second threshold. If the number of reaction containers with counts exceeding the mean count surpasses this second threshold, a run error is determined for the entire plate.
  • the plate is inserted into the device that carries out the analysis. Each sample in the reaction containers of the plate is identified as either a biological sample or a standardized sample based on the correct orientation of the plate in the device. However, human error may result in the plate being inserted incorrectly, such as being rotated 180 degrees.
  • An advantage of the QC method is its ability to detect such errors, ensuring the integrity and accuracy of the analysis by verifying that samples are correctly identified regardless of the orientation of the plate. This reduces the risk of inaccurate results due to misidentification and enhances the reliability of the overall analytical process.
  • a plate-level run error is detected, it suggests that the results from the entire plate may be unreliable, necessitating a re-run of the analysis for all samples on that plate.
  • the nucleic acid reporter molecules include both test reagent-specific reporter molecules and analyte reporter molecules. Each nucleic acid reporter molecule is equipped with identification sequences that enable precise identification and quantification.
  • the first identification sequence is used to identify the specific reaction container of the analyzed sample, ensuring that the data correlates accurately to the correct sample location.
  • the second identification sequence is used to uniquely identifying one of: the analyte or a test reagent from the one or more test reagents, ensuring that the data correlates accurately to the amount of analyte and test reagent(s) of the sample.
  • This system allows for the accurate detection and measurement of both test reagents and analytes in each sample, facilitating robust quality control and error detection throughout the analysis process.
  • known reference values can be used to verify the quality and accuracy of the analysis method.
  • the method further comprises determining for each reaction container comprising a sample identified as standardized sample, a combined count of the set of counts determined for the reaction container, wherein upon the combined count for the reaction container is below a first threshold, determining a run error for the reaction container.
  • known reference values can be used to verify the quality and accuracy of the analysis method.
  • a standardized sample's total count falls below a set threshold, it may be flagged as being a run-error. This flag indicates potential technical issues, resulting in insufficient data for reliable analysis.
  • This QC step ensures only samples with adequate content are considered for further analysis.
  • the threshold may be established based on the known reference values and specific implementation requirements.
  • a run error can occur at either the reaction container level or the plate level, each representing different scopes of issues in the quality control process.
  • a run error of a reaction container occurs when a specific reaction container (well) has issues. It indicates a problem with an individual sample or reagent addition in that particular container. This type of error flags that specific reaction container for re-evaluation or exclusion from analysis. When a large enough amount of reaction container has been flagged with a run error, this may lead to a run error being determined for the entire plate.
  • Run error on a plate level occurs when multiple reaction containers on a plate exhibit errors, indicating a broader issue affecting the entire plate. This can be due to systemic problems such as incorrect plate insertion, widespread reagent failure, or instrument malfunction.
  • the method further comprises determining for each reaction container comprising a sample identified as standardized sample, and for each test reagent among the one or more test reagent, whether a count for the amount of test reagent specific reporter molecules of the reaction container is below a test reagent specific threshold, wherein upon the count is below the test reagent specific threshold, determining a run error for the reaction container.
  • the amount of each test reagent, identified via the raw count of the reagent-specific reporter molecules, can be verified against known reference values. This ensures that the addition of the test reagent has been successfully accomplished. This QC step ensures that only samples with adequate content are considered for further analysis.
  • the method further comprises determining, for each reaction container comprising a sample identified as standard samples, and for each test reagent among the one or more test reagent, whether a fraction of the count for the amount of test reagent specific reporter molecules of the reaction container to the combined count of the reaction container is outside a test reagent specific range, wherein upon the fraction is outside the test reagent specific range, determining a run error for the reaction container.
  • the aim of identifying deviating plate controls may be to ensure the reliability and accuracy of the assay results.
  • the method helps to identify and correct underlying technical issues that could compromise data quality.
  • the QC checks may be improved, since the known reference values can be used to verify the quality and accuracy of the analysis method.
  • formal plate quality control as exemplified above is to identify samples, block-plates or assays that are severely affected by technical errors, such as reagent contaminations, operation mistakes, and instrument failures.
  • the method provides for obtaining more detailed information about the quality of the performed assay and the reasons for any poor performance.
  • the test reagents comprise incubation test reagents, extension test reagents, and amplification test reagents.
  • the test reagents comprise incubation control, extension control, and amplification control as known in the art and described e.g. in Wik et al., supra.
  • extension test reagent is to be interpreted as two paired oligonucleotides coupled to the same antibody molecule, thereby being in constant proximity.
  • the incubation test reagents comprise of one or more non-human antigens, such asphycoerythrin and green fluorescent protein, with matching proximity probes.
  • the extension test reagents is made by antibodies conjugated to a set of single stranded oligonucleotides capable of at least partial hybridization.
  • the amplification test reagents comprise synthetic double-stranded nucleic acid molecules.
  • the method further comprises determining the type of run error.
  • the method further comprises determining and actions to be taken in response to determining a run error for the plate and/or a run error for a reaction container.
  • the method further comprises an initial step of initiating, wherein the step of initiating the method comprises receiving a quality control warning from the analysis-method indicating that the method should be performed.
  • the above object is achieved by a computer program product comprising a non-transitory computer-readable storage medium having thereon a computer program comprising program instructions, the computer program being loadable into a processor and configured to cause the processor to perform the method according to the first aspect.
  • system comprising, one or more processors; and one or more non-transitory computer-readable media storing instructions executable by the one or more processors, wherein the instructions, when executed, cause the system to perform the method according to the first aspect.
  • Figure 1 shows schematically a flowchart of the method according to an embodiment of the present disclosure.
  • Figure 2 shows schematically a top view of the plate from which the method, according to an embodiment of the present disclosure, obtains measurements.
  • Figure 3 show schematically a data processing unit comprising a computer program product.
  • each run of the method also includes standardized samples.
  • the analysis results from standardized samples shall be as expected from the constitution of these samples and these results are used as described herein to assess, or control, the quality of the specific run of the analysis method.
  • Standardized samples as used herein are of two types, standard samples and blank samples. Standard samples are prepared to reflect a biological sample with a normal content of the analytes to be analysed by the analysis method. They are in general prepared by pooling biological samples of the same type as those being analyzed, from a number of healthy individuals. Blank samples do not contain any of the analytes to be tested for in the analysis method, and usually contain only buffer. Standardized samples are sometimes also referred to in the art as "external controls".
  • Test reagents are reagents that are specifically constructed to produce specific reporter nucleic acid molecules when added to the biological and standardized samples in the analysis method.
  • Test reagents as used in the present invention are known in the art and sometimes referred to as "internal controls".
  • the present invention relates to a method for determining whether an error has occurred in a certain run of the analysis method (a "run error"), based on the data patterns obtained by the analysis method from the standardized samples and the test reagents.
  • the present invention also allows for connecting specific data patterns to specific errors, thereby simplifying identification of error sources.
  • Fig. 1 shows a flowchart of analysis-method 10 and method 100 according to the first aspect of this disclosure.
  • Fig.l shows a method 100 for determining at least one run error for an analysis-method 10 for quantifying a plurality of analytes in a plurality of biological samples.
  • the analysis-method 10 comprises the step of adding S12 a plurality of biological samples in a first set of reaction containers (e.g. Al-All, ...,H1-H11 as shown in Fig.2) of a plate 200 and adding a plurality of standardized samples in a second set of reaction containers (e.g. A12-H12 as shown in Fig.2) of the plate 200.
  • a first set of reaction containers e.g. Al-All, ...,H1-H11 as shown in Fig.2
  • a second set of reaction containers e.g. A12-H12 as shown in Fig.2
  • the biological samples are samples under investigation and the standardized samples are of a type selected from at least a standard sample, and a blank sample.
  • a plurality of samples in a plurality of reaction containers of a plate wherein each sample is identified as a biological sample or a standardized sample, wherein a first plurality samples in a first set of reaction containers (Al-All, ...,H1-H11) are identified as biological samples and a second plurality of samples in a second set of reaction containers (A12-H12) are identified as standardized samples.
  • Al-All, ...,H1-H11 a first set of reaction containers
  • A12-H12 second plurality of samples in a second set of reaction containers
  • the analysis-method 10 further comprises the step of adding S16, to each biological sample and to each standardized sample, predetermined amounts of at least one test reagent.
  • Analysis-method 10 further comprises the step of adding S14 assay reagents to the biological samples and to the plurality of the standardized samples.
  • the assay reagent is configured to generate a nucleic acid reporter molecules in an amount correlated to the amount of analyte and test reagent in the biological sample and the standardized sample.
  • Each nucleic acid reporter molecule pertains to an analyzed sample among the plurality of samples and comprises identification sequences.
  • the identification sequences comprise a first identification sequence identifying the reaction container of the analyzed sample and a second identification sequence uniquely identifying one of: the analyte or a test reagent from the one or more test reagents.
  • the assay reagents are thus designed to generate nucleic acid reporter molecules in quantities that correspond to the amounts of analyte and test reagent present in each sample.
  • Each nucleic acid reporter molecule contains identification sequences which have two main purposes. The first identification sequence identifies the reaction container (well) that holds the analyzed sample, ensuring that the data collected is accurately associated with the correct sample location on the plate. The second identification sequence uniquely identifies either the analyte or a specific test reagent from among the multiple test reagents used. Such identification aids in determining the type and quantity of each substance within the sample. This process allows for accurate tracking and differentiation of samples and reagents, ensuring that results are correctly attributed to the appropriate sample and reagent.
  • the method By correlating the amount of nucleic acid reporter molecules to the amount of analyte and test reagent, the method provides reliable quantification of the substances present in the samples.
  • the identification sequences also enhance data integrity by preventing mix-ups between samples and reagents, which is especially important in high-throughput settings where many samples are processed simultaneously.
  • identification data of known amounts of test reagent is used for quality control purposes. As such, known reference values can be utilized to verify the quality and accuracy of the analysis method.
  • the analysis-method 10 comprising the step of detecting S18 the amount of reporter molecules carrying identification sequences such that obtaining a count value for each unique combination of the first and second identification sequences may be possible in a quality control method 100 described below.
  • a "unique combination” refers to the pairing of two specific identification sequences within each nucleic acid reporter molecule.
  • the first identification sequence identifies the specific reaction container from which the sample originates, ensuring that data can be accurately traced back to its source.
  • the second identification sequence uniquely identifies eitherthe analyte orthe specific test reagent present in the sample. Together, these sequences create a unique identifier for each data point, ensuring that the counts obtained can be precisely attributed to the correct sample and its corresponding amount of reagent or analyte.
  • a quality control warning may or may not be received. If a quality control warning is received, the quality control method 100 aim to determining the cause of said quality control warning.
  • the method 100 comprises the step of obtaining S110 using the identification sequences of the nucleic acid reporter molecules, for each reaction container, a set of counts, the set of counts comprising a count for the amount of analyte reporter molecules detected S18 in the reaction container; and for each test reagent of the at least one test reagent detected in the reaction container, a count for the amount of the test reagent specific reporter molecules corresponding to the test reagent.
  • each nucleic acid reporter molecule has identification sequences that indicate the specific reaction container and whether it corresponds to an analyte or a test reagent.
  • the system then counts (obtains) the nucleic acid reporter molecules, providing a set of counts that includes both the count of analyte reporter molecules and the count of test reagent-specific reporter molecules for each sample. These counts are used in the quality control method 100 as discussed below to ensure that the data is reliable and that the test reagents were properly added.
  • the method 100 than determining which of a set of criteria are fulfilled. The criteria are based on parameters, which correlate to certain issues.
  • the method 100 may comprise determining S118, for all reaction containers comprising a sample identified as a standardized sample, a mean count of the set of counts of the test reagent specific reporter molecules corresponding to any of the one or more test reagents, and upon a number of reaction containers comprising a sample identified as standardized sample, in which the count for the amount of analyte reporter molecules detected in the reaction container exceeds the mean count, exceeds a second threshold, determining a run error for the plate.
  • a protein assay identified as a negative control or empty sample is considered to have received an unexpectedly high number of counts if the amount of analyte reporter molecules detected in the reaction container exceeds the mean count. If enough such protein assays have such an unexpectedly amount of analyte reporter molecules (i.e., over the second threshold, which may for example be 1, 5, 7, 10, etc.), a run error for the plate is determined. For example, if the mean count of test reagent-specific reporter molecules across all standardized samples is 1000, and a reaction container identified as a standardized sample shows 1500 analyte reporter molecules, this exceeds the mean count. If the second threshold is set to 5 and there are 6 reaction containers where the analyte reporter molecules exceed 1000, this number exceeds the threshold. Consequently, a run error is determined for the plate.
  • the method may further comprise determining (S112) for each reaction container comprising a sample identified as standardized sample, a combined count of the set of counts determined for the reaction container, wherein upon the combined count for the reaction container is below a first threshold, determining a run error for the reaction container.
  • Example of the first threshold may be 2000, 4000, 5600, 10000, etc.
  • the method may further comprise determining S114 for each reaction container comprising a sample identified as standardized sample, and for each test reagent among the one or more test reagent, whether a count for the amount of test reagent specific reporter molecules of the reaction container is below a test reagent specific threshold, wherein upon the count is below the test reagent specific threshold, determining a run error for the reaction container For example, if the counts for any of the test reagents, e.g., incubation-, extension- and amplification test reagents, is less than 150, a run error for the reaction container may be is determined In another example, if the counts for any of the test reagents in container comprises standardized sample is greater than 150, and less than or equal to 500, 1000, and 500 for incubation-, extension- and amplification test reagent respectively, run error for the reaction container may be is determined
  • the counts for any of the test reagents in container comprises biological samples is greater than 150, and less than or equal to 500, 1000, and 500 for incubation-, extension- and amplification test reagent respectively, run error for the reaction container may be is determined.
  • the correlated issue causing the problem may be low test reagent levels.
  • the method may comprise determining S116, for each reaction container comprising a sample identified as standard samples, and for each test reagent among the one or more test reagent, whether a fraction of the count for the amount of test reagent specific reporter molecules of the reaction container to the combined count of the reaction container is outside a test reagent specific range, wherein upon the fraction is outside the test reagent specific range, determining a run error for the reaction container
  • the correlated issue causing the problem may be that there is a sample instead of a blank sample in the reaction container.
  • the quality control method 100 can include any of the steps S112- S118, either individually or in combination. For instance, in some cases, the quality control method 100 may consist of just one of the steps S112-S118.
  • the method may include two or more of these steps, such as step S118 followed by step S112 and step S116, or step S112 followed by step S116.
  • the method 100 may then comprise determining S160 at least one run error for one or more reaction containers and/or the plate as described above, depending on which of the QC checks (and how many) that have failed.
  • the method 100 further comprises the step of determining S170, on basis on QC checks that failed, the type of run error caused the quality control warning.
  • the method 100 further comprises determining S180 on basis on which QC checks that have failed or not failed, or, on basis on the type of the determined run error, which corresponding actions to be taken. For example, if an incorrect sample plate is used or a sample plate is not facing the right direction, then blank sample will not be at the expected positions and the expected positions for blank sample will be samples of other types.
  • the method 100 may further comprise the step of initiating S105, which precedes the other steps.
  • the step of initiating 105 is triggered when receiving the quality control warning from the analysis-method 10 indicating that the method 100 may be performed.
  • Fig. 2 depicts schematically a well plate 200 comprising 96 wells illustrated by a circle.
  • the plate has the dimensions of 8 samples in a column (A-H) and 12 samples in a row (1-12).
  • Fig. 3 depicts schematically a data processing unit comprising a computer program product for determining a position and an orientation.
  • Fig. 3 depicts a data processing unit 310 comprising a computer program product comprising a non-transitory computer-readable storage medium 312.
  • the non-transitory computer-readable storage medium 312 having thereon a computer program comprising program instructions.
  • the computer program is loadable into a data processing unit 310 and is configured to cause a processor 311 to carry out the method 100 for determining run errors for an analysis-method 10 for quantifying a plurality of analytes in a plurality of biological samples with the description of fig. 1.
  • the Quality Control is performed directly on Counts, on one block per 96 samples.
  • a "block” in this regard is an abundance block as described in Wik et al., supra.
  • the Plate QC are divided into three parts, Sample QC, Block QC and Assay QC.
  • Each sample and external control should have enough number of counts in a block for being proceeded with other steps in QC. Failure of a sample at this stage might indicate that index (i.e. identification sequence identifying reaction container) was not properly added into the sample.
  • Each sample and external control should have a minimum number of counts for any of the internal controls, otherwise they consider as missing the internal controls and fail.
  • the corresponded Plate and Negative controls should pass some QC criteria. This step is performed only on the Plate/Negative controls that pass Sample QC step and checks if the block has been affected by any technical errors. The failed block requires to be rerun.
  • Deviation of internal control's counts from the expected ranges in Plate Controls might be an indicator of different technical errors.
  • a plate control fails this QC step if the fraction of counts of all internal control to total counts in logarithmic scale, deviates positively or negatively from the reference values.
  • the reference ranges are block specific and kit lot related.
  • the data in a block passes QC if more than half of the plate controls in the corresponding block passes this QC step (ex: 3 out of 5 plate controls need to pass QC).
  • Negative Control fails this step if many assays get higher number of counts in comparison with the counts of all internal controls.
  • the data in a block passes QC if enough number of Negative Control pass this QC step (ex: 1 out of 2 Negative Controls)

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Abstract

Procédé de contrôle qualité (100) permettant de déterminer les erreurs d'exécution pour une méthode d'analyse (10) visant à quantifier une pluralité d'analytes dans une pluralité d'échantillons biologiques.
PCT/EP2024/066810 2023-08-07 2024-06-17 Procédé pour déterminer les erreurs d'exécution d'une méthode d'analyse pour la quantité d'une pluralité d'analytes dans une pluralité d'échantillons biologiques Pending WO2025031642A1 (fr)

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Citations (10)

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WO2001061037A1 (fr) 2000-02-18 2001-08-23 Ulf Landegren Procedes et trousses de detection de proximite
WO2003044231A1 (fr) 2001-11-23 2003-05-30 Simon Fredriksson Procede et kit pour le sondage de proximite au moyen de sondes de proximite polyvalentes
WO2004094456A2 (fr) 2003-04-18 2004-11-04 Becton, Dickinson And Company Amplification immunologique
WO2005123963A2 (fr) 2004-06-14 2005-12-29 The Board Of Trustees Of The Leland Stanford Junior University Procedes et compositions destines a la detection d'analytes au moyen de sondes de proximite
WO2006137932A2 (fr) 2004-11-03 2006-12-28 Leucadia Technologies, Inc. Detection homogene de substance a analyser
WO2013113699A2 (fr) 2012-01-30 2013-08-08 Olink Ab Dosage d'extension par sonde de proximité avec une adn polymérase hyperthermophile
WO2021113290A1 (fr) 2019-12-03 2021-06-10 Alamar Biosciences, Inc. Dosage immunologique-sandwich lié à un acide nucléique (nulisa)
WO2021191450A1 (fr) 2020-03-27 2021-09-30 Olink Proteomics Ab Commandes pour dosages de détection de proximité
WO2021191442A1 (fr) 2020-03-27 2021-09-30 Olink Proteomics Ab Procédé de détection d'analytes d'abondance variable
WO2022112300A1 (fr) 2020-11-25 2022-06-02 Olink Proteomics Ab Procédé de détection d'analyte utilisant des concatémères

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001061037A1 (fr) 2000-02-18 2001-08-23 Ulf Landegren Procedes et trousses de detection de proximite
WO2003044231A1 (fr) 2001-11-23 2003-05-30 Simon Fredriksson Procede et kit pour le sondage de proximite au moyen de sondes de proximite polyvalentes
WO2004094456A2 (fr) 2003-04-18 2004-11-04 Becton, Dickinson And Company Amplification immunologique
WO2005123963A2 (fr) 2004-06-14 2005-12-29 The Board Of Trustees Of The Leland Stanford Junior University Procedes et compositions destines a la detection d'analytes au moyen de sondes de proximite
WO2006137932A2 (fr) 2004-11-03 2006-12-28 Leucadia Technologies, Inc. Detection homogene de substance a analyser
WO2013113699A2 (fr) 2012-01-30 2013-08-08 Olink Ab Dosage d'extension par sonde de proximité avec une adn polymérase hyperthermophile
WO2021113290A1 (fr) 2019-12-03 2021-06-10 Alamar Biosciences, Inc. Dosage immunologique-sandwich lié à un acide nucléique (nulisa)
WO2021191450A1 (fr) 2020-03-27 2021-09-30 Olink Proteomics Ab Commandes pour dosages de détection de proximité
WO2021191442A1 (fr) 2020-03-27 2021-09-30 Olink Proteomics Ab Procédé de détection d'analytes d'abondance variable
WO2021191448A1 (fr) 2020-03-27 2021-09-30 Olink Proteomics Ab Procédé de détection d'analytes
WO2021191449A1 (fr) 2020-03-27 2021-09-30 Olink Proteomics Ab Procédé de détection d'analytes
WO2022112300A1 (fr) 2020-11-25 2022-06-02 Olink Proteomics Ab Procédé de détection d'analyte utilisant des concatémères

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ASSARSSON ET AL., PLOS 1, vol. 9, no. 4, 2014, pages e95192
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WIK ET AL., MOL CELL PROTEOMICS, vol. 20, 2021, pages 100168
WIK LOTTA ET AL: "Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis", vol. 20, 1 January 2021 (2021-01-01), US, pages 100168, XP093030109, ISSN: 1535-9476, Retrieved from the Internet <URL:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633680/pdf/main.pdf> DOI: 10.1016/j.mcpro.2021.100168 *

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