Multi-stage inspection method including multiple inspection methods, system for executing said method, and billing system

Abstract

The present disclosure provides a method that is for inspecting a plurality of biological samples obtained from respective subjects, that comprises a first step and a second step, and in which the number of inspections in the second step is reduced by narrowing down, in the first step, the subjects to be inspected in the second step. As a result, for example, it is possible to speed up and / or reduce cost through reduction of the inspection volume by reducing the number of times for which the second step, which is complicated or is high cost, is carried out.

Description

Multi-stage inspection method including multiple inspection methods, system for executing said method, and billing system

[0001] The present disclosure relates to a multi-stage testing method including multiple testing methods, a system for performing said method, and a billing system.

[0002] There is a medical need for predicting health status, disease status, drug response, or risk of developing a disease. A comprehensive understanding of the expression of various genes in a living organism will lead to more accurate predictions. With the advent of next-generation sequencers (NGS), biological transcriptome analysis has become possible at a research level, while ensuring overwhelming comprehensiveness, at a realistic cost. However, NGS analysis is still too expensive for clinical testing. In addition to NGS, there are many other testing techniques that require complicated procedures or are too expensive for clinical testing.

[0003] Patent Literature 1 discloses a system for selecting a cancer therapeutic drug equipped with next-generation sequencing and an automatic slide staining device. The system disclosed in Patent Literature 1 can extract a sample, subject it to next-generation sequencing, and subject it to immunohistochemical staining.

[0004] WO2017 / 132276A

[0005] The present invention provides a multi-stage testing method including multiple testing methods, and a billing system. Specifically, the present disclosure provides a method, a system for performing the method, and a billing system that enable speeding up and / or reducing costs of overall testing in testing multiple subjects.

[0006] According to the present invention, for example, the following inventions can be provided: (1) A method for testing a plurality of biological samples obtained respectively from a plurality of subjects, comprising a first step and a second step, the second step being carried out after the first step, the first step comprising: measuring the levels of s types of first biomarkers (s is a natural number of 1 or more) contained in each of the biological samples, and identifying the subject from whom the biological sample whose level of the first biomarker satisfies a first criterion is derived, the second step comprising: measuring the levels of t types of second biomarkers (t is a natural number of 2 or more, preferably a natural number greater than s) contained in each of the biological samples obtained from the subjects identified in the first step, and identifying the biological sample whose measured level satisfies a second criterion, wherein the number of biological samples analyzed in the first step is p, and the number of biological samples analyzed in the second step is q, (2) A method wherein the number of biological samples whose measured levels satisfy the second criterion is r, the number of biological samples whose measured levels satisfy the second criterion when all p biological samples are subjected to the second step without performing the first step is r', and r / q is greater than r' / p, and biological samples obtained from subjects from which biological samples whose levels measured in the first step do not satisfy the first criterion are derived are not analyzed in the second step, whereby p and q are natural numbers satisfying p > q. (2) The method described in (1) above, wherein the first step comprises measuring the presence or absence of s types of first biomarkers (s is a natural number of 1 or greater) contained in each of the biological samples, and identifying subjects from which biological samples whose presence or absence of the first biomarkers satisfies the first criterion are derived. (3) The method described in (1) or (2) above, wherein the level of the first biomarker is measured by a PCR method, and the level of the second biomarker is measured by a sequencing method. (4) The method described in (3) above, wherein the PCR method is digital PCR. (5) The method according to (3) or (4) above, wherein t is a natural number of 20 or more.(6) The method according to any one of (1) to (5) above, wherein in the second step, information relating to the association between the level of a second biomarker in each of biological samples obtained from a plurality of subjects that have been previously measured and the health status of each of the plurality of subjects is learned by machine learning, and a prediction model constructed so as to be able to predict the health status of the subject from which the biological sample was derived based on the level of the second biomarker in the biological sample includes a second criterion regarding the level of the second biomarker, and the prediction model evaluates whether the level of the second biomarker in the biological sample satisfies the second criterion. (7) The method according to any one of (1) to (6) above, further comprising one or more cycles of correcting the first criterion, wherein the first criterion correction cycle comprises: correlating the level of the first biomarker with the level of the second biomarker for each subject; learning the correlated levels of the first biomarker and the second biomarker by machine learning to construct a prediction model capable of predicting the level of the second biomarker from the level of the first biomarker; wherein the number of biological samples whose measured levels satisfy the second criterion is r (r is a natural number less than or equal to q); and correcting the first criterion based on the prediction model so that r becomes larger without increasing q (i.e., q is kept constant or preferably decreased).(8) A system for testing a plurality of biological samples obtained from a plurality of subjects, the system comprising one or more processors, a memory, and an output device, wherein one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs causing the memory to record levels of s types of first biomarkers (s is a natural number equal to or greater than 1) contained in each of the biological samples obtained from the subjects (number of individuals p) and a first criterion, causing a processor to calculate whether the levels of the first biomarkers recorded in the memory meet the first criterion, causing the processor to identify subjects (number of individuals q) from which biological samples whose levels of the first biomarkers meet the first criterion are derived, and outputting the result to the output device (first step); the levels of t types of second biomarkers (t is a natural number greater than or equal to 1) contained in each of the biological samples obtained from the subjects (number of individuals q) output to the output device, and the second criterion, and having a processor calculate whether the levels of the second biomarkers recorded in the memory meet the second criterion, and having the processor identify the subjects (number of individuals r) from which the biological samples whose levels of the second biomarker meet the second criterion are derived, and output the result to the output device (second step), wherein p, q, and r are all natural numbers, p>q>r, and the number of biological samples whose measured levels meet the second criterion when all p biological samples are subjected to the second step is r', and r / q is greater than r' / p. (9) The system according to (8) above, wherein the time required for the program to execute the first and second steps is shorter than the time required for executing a control program, and the control program includes instructions to record in a memory the levels of t types of second biomarkers (t is a natural number equal to or greater than 1) contained in each biological sample obtained from a subject (number of individuals p) and a second criterion, to cause a processor to calculate whether the levels of the second biomarkers recorded in the memory meet the second criterion, and to cause the processor to identify the subject (number of individuals r) from which the biological sample whose level of the second biomarker meets the second criterion is derived, and to output the result to an output device.(10) The system according to (8) or (9), wherein the program further includes instructions for executing one or more cycles of correction of the first criterion, wherein the first criterion correction cycle includes: correlating the level of the first biomarker with the level of the second biomarker for each subject; learning the correlated levels of the first biomarker and the second biomarker by machine learning to construct a prediction model capable of predicting the level of the second biomarker from the level of the first biomarker; wherein the number of biological samples whose measured levels satisfy the second criterion is r (r is a natural number less than or equal to q); and correcting the first criterion based on the prediction model so that r becomes larger without increasing q (i.e., q remains constant or preferably decreases).

[0007] 1 shows a scheme of inspection in the multi-stage inspection method of the present disclosure. 2 shows a schematic diagram of the inspection system of the present disclosure.

[0008] <Definition of Terms> As used herein, a "subject" may be a mammal, including, for example, rodents such as rats and mice, non-rodent mammals such as horses, goats, cows, pigs, sheep, dogs, and cats, and humans and non-human primates. Multiple subjects may be of different species, but are preferably of the same species, for example, humans.

[0009] As used herein, "biological sample" refers to a sample (e.g., tissue, cell, extracellular fluid, and body fluid) obtained from a subject. Body fluids include blood, urine, ascites, pleural effusion, saliva, nasal mucus, and secretions (e.g., endocrine and exocrine fluids, such as digestive fluids such as pancreatic juice, sweat, and tears). As used herein, a "blood sample" refers to blood (e.g., peripheral blood) or a blood-derived sample (e.g., serum and plasma) obtained from a subject. The sample to be measured in the first step described below is referred to as the "first biological sample," and the sample to be measured in the second step is referred to as the "second biological sample." The first biological sample and the second biological sample may be the same or of the same type, or different (i.e., different but the same type), or different types.

[0010] As used herein, a "biomarker" is a factor that is detected in a biological sample or whose level increases or decreases depending on a subject's health condition, risk of developing a disease, responsiveness to a drug, and / or disease state. The presence or amount of a biomarker can be used as an indicator to predict a subject's health condition, risk of developing a disease, responsiveness to a drug, and / or disease state. Examples of biomarkers include, but are not limited to, the presence or absence of nucleic acids such as DNA and RNA (mRNA and microRNA), epigenetic modifications of the genome, the sequence and amount of the nucleic acid, the type and amount of exosomes, the type and amount of proteins, the presence and amount of post-translational modifications of specific proteins (including the presence and amount of glycosylation, phosphorylation, and other modifications), and the type and amount of metabolites.

[0011] As used herein, "comprising" includes "consisting of," and the singular includes the plural unless expressly stated otherwise.

[0012] <Method of the Present Disclosure> According to the present disclosure, a multi-step testing method including a plurality of testing methods is provided. The testing method may be an in vivo testing method or an in vitro testing method, and is preferably an in vitro testing method. In one embodiment, the testing method of the present invention does not involve medical procedures (particularly diagnostic procedures or surgical procedures). The testing method of the present invention is industrially applicable. The testing method of the present invention may be a method for obtaining preliminary information for estimating or predicting a subject's health state, risk of developing a disease, responsiveness to a drug, and / or disease state.

[0013] A multi-stage testing method includes a first step and a second step, where the second step is performed after the first step, and the first step and the second step are different. Alternatively, the multi-stage testing method includes a first-stage testing method including the first step and a second-stage testing method including the second step, where the second step is performed after the first-stage testing method, and the first-stage testing method and the second-stage testing method are different. According to the present disclosure, a first-stage testing method including the first step is different from a second-stage testing method including the second step. The steps may be performed independently, but they may include data acquisition or data analysis to obtain clinically significant estimated or predicted results, and do not necessarily need to provide clinically significant estimated or predicted results. In contrast, a testing method independently provides results of technical or clinical significance. The things that the first-stage testing method and the second-stage testing method are attempting to estimate or predict may be the same, and are preferably the same.

[0014] Preferably, the multi-step method includes a preliminary method including a first step and a testing method including a second step. The preliminary method including the first step only needs to include data acquisition or data analysis to obtain clinically significant estimated or predicted results, and does not necessarily provide clinically significant estimated or predicted results. In contrast, the testing method independently provides results of technical or clinical significance. The preliminary method including the first step is a method for narrowing down the subjects to be subjected to the second step and is therefore considered a preliminary method. However, the preliminary method including the first step may itself provide clinically significant estimated or predicted results. If the subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state can be predicted without subjecting the subject to the second step, the second step is unnecessary. If prediction is not possible, it is also possible to subject the biological sample to the second step.

[0015] In certain aspects, the first testing method and the second testing method predict a subject's health state, risk of developing a disease, responsiveness to a drug, and / or disease state. In certain aspects, the first testing method and the second testing method predict a subject's health state, risk of developing a disease, and / or disease state. In certain aspects, in the first step, the preliminary method including the first step, and the first testing method, if it is predicted that the second biomarker will likely satisfy the second criterion in the second testing method, a second biological sample is provided to the second testing method. In certain aspects, in the first step, the preliminary method including the first step, and the first testing method, the second biological sample is not provided to the second testing method only if it is predicted that the second biomarker will not satisfy the second criterion in the second testing method.

[0016] In one aspect, the biological sample in the first step, the preliminary method including the first step, and the first testing method including the first step, and the biological sample in the second testing method including the second step are the same or of the same type. In one aspect, the biological sample in the first step, the preliminary method including the first step, and the first testing method including the first step, and the biological sample in the second testing method including the second step are different or of different types.

[0017] When the biological sample in the first step, the preliminary method including the first step, the first testing method including the first step, and the biological sample in the second testing method including the second step are the same or of the same type, they can be obtained from the subject in a single operation.

[0018] When the biological sample (first biological sample) in the first step, the preliminary method including the first step, or the first testing method including the first step is different from the biological sample (second biological sample) in the second testing method including the second step, or is of a different type, the first biological sample may be collected at the same time as the second biological sample, or may be collected at a different time.

[0019] When the first and second biological samples are collected contemporaneously, a single package containing the first and second biological samples can be provided, and the package can be appropriately transported from the subject to the testing site. Here, "contemporaneous" does not necessarily mean exactly the same time, but means close enough that the first and second biological samples can be collected and transported in a single package. According to the present disclosure, a biological sample collection kit is provided, including a first container for introducing the first biological sample and a second container for introducing the second biological sample. The biological sample collection kit is used to carry out the method of the present disclosure. The first and second biological samples collected using the biological sample collection kit are analyzed by the first and second steps, respectively. The first and second containers can be visually distinguished from each other by color and / or shape. When the first biological sample and the second biological sample are collected at different times, the second biological sample can be collected from a subject in the first step, a preliminary method including the first step, or a testing method including the first step, when the subject is desired to be analyzed by the second step.

[0020] In certain embodiments, the first step, the preliminary method including the first step, and the first testing method can calculate the probability (individual probability) that a subject will meet the second criterion in the second testing method. The calculation can be performed by statistical analysis or machine learning (including deep learning) analysis. Furthermore, in certain embodiments, the first step, the preliminary method including the first step, and the first testing method can calculate the probability (average of all subjects) that a group including all subjects subjected to the first step will meet the second criterion in the second testing method. In certain embodiments, the first step, the preliminary method including the first step, and the first testing method can obtain the average of all subjects and the individual probability. In certain embodiments, the first step, the preliminary method including the first step, and the first testing method can calculate how high the individual probability is compared to the average of all subjects.

[0021] The multi-stage testing method may further include additional testing methods. Each testing method may include determining the presence or absence of a biomarker in a biological sample obtained from a subject, predicting the subject's health status based on the amount of the biomarker, or comparing the amount of the biomarker to a reference value. The reference value is typically associated with the subject's health status. For example, the presence or absence of a biomarker is associated with the subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease status. In certain embodiments, each testing method may provide information for predicting the subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease status.

[0022] In some aspects, the presence of a biomarker correlates with a subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state. In these aspects, the absence of a biomarker correlates with a subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state. Detection of such qualitative biomarkers includes, but is not limited to, DNA sequences (e.g., DNA translocations, fusions, insertions / deletions (indels)), DNA polymorphisms such as DNA single nucleotide polymorphisms (SNIPs) and amplified fragment length polymorphisms (AFLPs)), immunochromatography, and PCR (particularly nucleic acid amplification other than quantitative PCR).

[0023] In some embodiments, the amount of a biomarker is associated with a subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state. In this embodiment, the amount of the biomarker varies in subjects with a particular disease state or risk of developing a disease. Such quantitative detection of biomarkers includes quantification methods using next-generation sequencing (NGS), digital PCR, mass spectrometry, quantitative PCR, and biochemical testing. Quantitative analysis may involve quantification of mRNA and microRNA. Quantitative analysis may involve quantification of proteins and other components. For example, in some embodiments, a greater amount of the biomarker than a reference value indicates that the presence of the biomarker is associated with a subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state. In some embodiments, a lesser amount of the biomarker than a reference value indicates that the presence of the biomarker is associated with a subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state. Thus, in certain embodiments, a subject's health status, risk of developing a disease, responsiveness to a drug, and / or disease state can be predicted based on the amount of a biomarker.

[0024] Next-generation sequencing (NGS) is a sequencing technique that increases the throughput of a single sequencing process by performing sequencing reactions in parallel. Some NGS methods can perform millions to billions of sequencing reactions simultaneously. NGS typically requires the preparation of a nucleic acid library for the sequencing reaction. The library includes ligation of nucleic acid fragments with adapters for the sequencing reaction, barcode sequences unique to the nucleic acid, and / or index sequences unique to the sample. Nucleic acids can be amplified (e.g., by bridge PCR or emulsion PCR). The amplification products can then be denatured into single strands, followed by DNA synthesis in the presence of dNTPs, including fluorescently labeled dNTPs with terminator caps, pyrosequencing, or ligation of fluorescently labeled single-stranded nucleic acids to decode the fragment sequences.

[0025] Digital PCR is a technique in which a template nucleic acid is dispensed into multiple wells (or droplets) so that each well (or droplet) does not contain more than one molecule, the nucleic acid is amplified by polymerase chain reaction (PCR), and the number of wells or droplets containing the amplified nucleic acid is counted, thereby estimating the concentration or number of molecules of the template present in the sample.

[0026] Quantitative PCR is also known as quantitative real-time PCR. Quantitative PCR uses a reporter dye that emits light with an intensity corresponding to the amount of amplified product obtained by the PCR amplification reaction. Reporter dyes include double-stranded DNA-binding dyes, primer-binding dyes, and dye-labeled oligonucleotides, which are called probes. Probes (particularly double-end-labeled probes) that bind to specific regions of the template between the primers are also preferably used. Double-end-labeled probes have a fluorescent dye (e.g., 6-FAM) at one end and a dark quencher (e.g., BHQ1 or QQ) at the other. As the amplified product increases, they bind to the amplified product, and then, due to the exonuclease activity of the DNA polymerase, one of the labels (particularly the reporter dye) dissociates from the quencher, emitting fluorescence.

[0027] When multiple biomarkers are present, the presence and / or amount of each biomarker can be scored by weighting each biomarker. Such scoring methods include, but are not limited to, weighting and integrating the Z-scores of the expression levels of each biomarker. A Z-score is a value obtained by subtracting the mean value from the corresponding value of a data group and dividing the result by the standard deviation. Weighting can be achieved, but is not limited to, by multiplying the Z-score by a factor corresponding to the weight and then adding the Z-scores multiplied by the factor. Weighting allows increases or decreases in important biomarkers to be more strongly reflected in the score, thereby making the comparison between the standard value and the score more reasonable.

[0028] In a multi-stage testing method, whether or not to perform a second-stage testing method is determined depending on the results of the first step, the preliminary method including the first step, and the first-stage testing method. In one embodiment, the second testing method is performed based solely on the results of the first step, the preliminary method including the first step, and the first-stage testing method (particularly, whether the level of the first biomarker meets the first criterion). In one embodiment, after the first step, the preliminary method including the first step, and the first-stage testing method are performed, no feedback or other communication is made to the subject or user before the second-stage testing method is performed.

[0029] In a multi-stage testing method, multiple subjects are subjects, all of whom are subjected to the first step, a preliminary method including the first step, and the first-stage testing method; some subjects are subjected to the second-stage testing method, while other subjects are not. The first step, the preliminary method including the first step, and the first-stage testing method are performed to narrow down the subjects to whom the second-stage testing method is applied. However, if the first-stage testing method clearly indicates that the second-stage testing is unnecessary (for example, if it is determined that the results are sufficient to understand the condition to be evaluated), not performing the second-stage testing method can have the effect of reducing the cost and effort required for the entire testing. If the second-stage testing method requires a large amount of calculation power, limiting the subjects subjected to the second-stage testing method can be effective, as it allows for rapid calculations or allows for calculations to be performed on a larger number of subjects.

[0030] The plurality of subjects can be 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, or 10 or more. The plurality of subjects can also be, but is not limited to, 10,000 or less, 9,000 or less, 8,000 or less, 7,000 or less, 6,000 or less, 5,000 or less, 4,000 or less, 3,000 or less, 2,000 or less, 1,000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 200 or less, 100 or less, 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less. The plurality of subjects may be, for example, but not limited to, 2 to 10,000, 3 to 9,000, 4 to 8,000, 5 to 7,000, 6 to 6,000, 7 to 5,000, 8 to 4,000, 9 to 3,000, 10 to 2,000, 11 to 1,000, 12 to 900, 13 to 800, 14 to 700, 15 to 600, 16 to 500, 17 to 400, 18 to 300, 19 to 200, 20 to 100, 30 to 90, 40 to 80, or 50 to 70. The plurality of subjects may include, for example, a number of people measured over a certain period of time (e.g., a span of one day, one week, one month, three months, six months, or one year). The plurality of subjects may also include, for example, a number of people measurable in a single run of a large-scale test. For example, the plurality of subjects may include a number of people measurable in a single run of NGS. The plurality of subjects may also include, for example, a number of people for which results can be provided by a single data processing.

[0031] The first criterion is a criterion for selecting a biological sample to be subjected to the second step. If the measured value of the first biomarker in the first biological sample satisfies the first criterion, a second biological sample obtained from the subject from which the first biological sample was derived is subjected to the second step. Furthermore, if the measured value of the first biomarker satisfies the first criterion, the second step is not, or may not be, performed.

[0032] In a preferred embodiment, the first step is a qualitative analysis step and the second step is a quantitative analysis step, and in a preferred embodiment, both the first step and the second step are quantitative analysis steps.

[0033] In certain aspects of the present disclosure, the first step may include measuring the levels of s types (s is a natural number of 1 or greater) of first biomarkers contained in each of the biological samples. In certain aspects of the present disclosure, the first step may include identifying a subject from whom the biological samples were derived, in which the measured values ​​(levels) of the first biomarkers in the biological samples obtained by the measurement satisfy a first criterion. In certain aspects, the first step may include measuring the levels of s types (s is a natural number of 1 or greater) of first biomarkers contained in each of the biological samples, and identifying a subject from whom the biological samples were derived, in which the levels of the first biomarkers satisfy the first criterion.

[0034] Although s is not particularly limited, it can be, for example, a natural number of 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, or 10 or more. Furthermore, although s is not particularly limited, it can be, for example, a natural number of 1,000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 2000 or less, 100 or less, 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less. Furthermore, s can be, but is not limited to, for example, 1 to 10, 1 to 100, 2 to 10, 2 to 100, 3 to 10, 3 to 100, 4 to 10, 4 to 100, 5 to 10, 5 to 100, 1 to 1,000, 2 to 900, 3 to 800, 4 to 700, 5 to 600, 6 to 500, 7 to 400, 8 to 300, 9 to 200, 10 to 100, 20 to 90, 30 to 80, 40 to 70, or 50 to 60.

[0035] In certain aspects, the second step comprises measuring the levels of t types of second biomarkers (where t is a natural number greater than or equal to 2, and preferably a natural number greater than s) contained in each of the biological samples obtained from the subjects identified in the first step. In certain aspects, the second step may comprise identifying subjects from whom the biological samples were derived, the measured values ​​(levels) of the second biomarkers in the biological samples obtained by the measurements satisfying a second criterion. In certain aspects, the second step comprises measuring the levels of t types of second biomarkers (where t is a natural number greater than or equal to 2, and preferably a natural number greater than s) contained in each of the biological samples obtained from the subjects identified in the first step, and identifying biological samples whose measured levels satisfy the second criterion.

[0036] t is not particularly limited, and may be, for example, a natural number of 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more, or 1,000 or more. Furthermore, t is not particularly limited, and may be, for example, a natural number of 1,000,000 or less, 100,000 or less, 10,000 or less, 1,000 or less, 900 or less, 800 or less, 700 or less, 600 or less, 500 or less, 400 or less, 300 or less, 2000 or less, 100 or less, 90 or less, 80 or less, 70 or less, 60 or less, 50 or less, 40 or less, 30 or less, 20 or less, or 10 or less. Furthermore, t may be, but is not limited to, 1 to 1,000,000, 1 to 100,000, 1 to 10,000, 1 to 1,000, 2 to 900, 3 to 800, 4 to 700, 5 to 600, 6 to 500, 7 to 400, 8 to 300, 9 to 200, 10 to 100, 20 to 90, 30 to 80, 40 to 70, or 50 to 60. The second step may be omics analysis (proteome analysis, transcriptome analysis, exome analysis, epigenome analysis, microRNA omics analysis, etc.). In this case, there may be no specific upper or lower limit on the number of markers.

[0037] In one aspect, t is a natural number greater than s, and t can be a natural number that is 2 or more times, 3 or more times, 4 or more times, 5 or more times, 6 or more times, 7 or more times, 8 or more times, 9 or more times, 10 or more times, 20 or more times, 30 or more times, 40 or more times, 50 or more times, 60 or more times, 70 or more times, 80 or more times, 90 or more times, 100 or more times, 200 or more times, 300 or more times, 400 or more times, 500 or more times, 600 or more times, 700 or more times, 800 or more times, 900 or more times, or 1000 or more times greater than s.

[0038] In the method of the present disclosure, the number of biological samples analyzed in the first step is p, and the number of biological samples analyzed in the second step is q (where p and q are natural numbers satisfying p>q).

[0039] In one aspect, the number of biological samples whose measured levels satisfy the second criterion is r, the number of biological samples whose measured levels satisfy the second criterion when all p biological samples are subjected to the second step without performing the first step is r', r / q is greater than r' / p, and biological samples obtained from subjects from whom biological samples whose measured levels in the first step do not satisfy the first criterion are derived are not analyzed in the second step, whereby p and q are natural numbers satisfying p>q.

[0040] In one aspect, the first step includes measuring the presence or absence of s types of first biomarkers (where s is a natural number equal to or greater than 1) contained in each of the biological samples, and identifying subjects from which biological samples in which the presence or absence of the first biomarkers satisfies a first criterion are derived.

[0041] In a preferred embodiment, the first step is a qualitative or quantitative analysis, and the second step is a quantitative analysis. In a preferred embodiment, the first step comprises qualitative or quantitative analysis of an amplified product of a first biomarker by PCR (e.g., a nucleic acid array (e.g., a qualitative or quantitative analysis by DNA array, a qualitative analysis by PCR, a quantitative analysis by real-time PCR (RT-PCR), or a quantitative analysis by digital PCR)), and the second step is a quantitative analysis. In this embodiment, the second step preferably comprises quantitative analysis by sequencing of a second biomarker or mass spectrometry of the second biomarker. In this embodiment, the first step is, for example, For example, the first step may include detecting the presence or absence of an amplification product of a first biomarker and determining whether the presence or absence of the amplification product of the first biomarker satisfies a first criterion. In this aspect, the first step may include, for example, detecting the presence or absence of an amplification product of the first biomarker and determining whether the amount of the amplification product of the first biomarker satisfies a first criterion. Furthermore, in this aspect, quantitative analysis by sequencing can typically be achieved by linking a unique barcode to each nucleic acid molecule and estimating the type of decoded barcode as the number of nucleic acid molecules.

[0042] As the number of second biomarkers increases, the burden or cost of qualitative analysis (e.g., sequencing and mass spectrometry) increases. Therefore, in order to reduce the number of biological samples (q) to be subjected to the second step, it is effective to select and discard the subjects in the first step. The number of second biomarkers (t) can be, for example, 20 or more, 30 or more, 40 or more, or 50 or more. The definition of t is as described above.

[0043] In one aspect, in the second step, the association information between the level of a second biomarker in each of biological samples obtained from a plurality of subjects and the health status of each of the plurality of subjects is learned by machine learning, and a prediction model constructed to be able to predict the health status of the subject from which the biological sample was derived based on the level of the second biomarker in the biological sample includes a second criterion related to the level of the second biomarker, and the prediction model evaluates whether the level of the second biomarker in the biological sample satisfies the second criterion. In one aspect, the second step or the second testing method infers or predicts the health status, risk of developing a disease, responsiveness to a drug, and / or disease state of the subject from which the biological sample was derived based on whether the level of the second biomarker in the biological sample satisfies the second criterion. For example, if the level of the second biomarker in the biological sample satisfies (or does not satisfy) the second criterion, it can be inferred or predicted that the subject from which the biological sample was derived is healthy, at risk of developing a disease (specific disease), and / or has a disease (specific disease). For example, if the level of the second biomarker in the biological sample does not meet (or does meet) a second criterion, it can be inferred or predicted that the subject from which the biological sample was derived is not healthy, is not at risk of developing a disease (specific disease), and / or does not have a disease (specific disease).

[0044] In certain aspects, the method of the present disclosure may further include one or more first criterion correction cycles. The first criterion correction cycle includes: correlating the level of a first biomarker with the level of a second biomarker for each subject; learning the correlated levels of the first biomarker and the second biomarker by machine learning to construct a prediction model capable of predicting the level of the second biomarker from the level of the first biomarker; where the number of biological samples whose measured levels meet the second criterion is r (r is a natural number less than or equal to q); and correcting the first criterion based on the prediction model so that r increases without increasing q (i.e., while q remains constant or preferably decreases). This makes it possible to more effectively reduce the number of tests (q) or more effectively increase r / q in the second testing method including the second step (particularly compared to r / q when the correction cycle is not included) in the first step, the preliminary method including the first step, and the first testing method.

[0045] In this way, according to the method of the present disclosure, by performing the first step, a preliminary method including the first step, or the first testing method including the first step before the second step or the second testing method including the second step, it is possible to reduce the number (q) of biological samples to be subjected to the second step.

[0046] The present disclosure provides a system 100 for testing multiple biological samples obtained from multiple subjects. The system 100 includes one or more processors 105, a memory 104, and an output device. One or more programs are stored in the memory 104 and configured to be executed by the one or more processors 105.

[0047] The one or more programs are configured to, for example, execute the methods of the present disclosure.

[0048] In a preferred aspect of the present disclosure, the one or more programs: (preferably, ID information for identifying the subjects) record in a memory the levels of s types of first biomarkers (s is a natural number equal to or greater than 1) contained in each biological sample obtained from the subjects (number of individuals p) and a first criterion; cause a processor to calculate whether the levels of the first biomarkers recorded in the memory meet the first criterion; (preferably, based on the ID information) cause the processor to identify the subjects (number of individuals q) from which the biological samples whose levels of the first biomarkers meet the first criterion are derived, and output the result to an output device (first step); (a) storing in a memory (preferably ID information for identifying the subjects) the levels of t types of second biomarkers (where t is a natural number equal to or greater than 1) contained in each of the biological samples obtained from the subjects (number of individuals q) output to the output device, and a second criterion; (b) causing a processor to calculate whether the levels of the second biomarkers recorded in the memory meet the second criterion; and (c) causing the processor to identify the subjects (number of individuals r) from which the biological samples whose levels of the second biomarkers meet the second criterion are derived (preferably based on the ID information), and output the results to the output device (a second step).

[0049] The ID information may be any information that identifies the subject, and may be, for example, the subject's real name, or may be text information (which may include, for example, numbers, symbols, uppercase letters, and lowercase letters).

[0050] In a preferred embodiment, p, q, and r are each natural numbers, p>q>r, the number of biological samples whose measured levels satisfy the second criterion when all p biological samples are subjected to the second step is r', and r / q is greater than r' / p.

[0051] In the above, the output device 101 may be, for example, a display, a printer, or a speaker. The output device 101 may be included in the system 100 of the present disclosure, but may not be included in the system of the present disclosure. For example, the output device 101 may be a terminal such as a smartphone or a tablet, and the processor may be configured to send commands to the terminal to display (output) an object on the screen of the terminal. Commands may be sent from the system 100 to the terminal via a communication interface 107. The communication interface 107 may transmit and receive radio waves such as Wi-Fi or Bluetooth. The communication interface 107 may have a transceiver for a universal serial bus (USB) or a local area network (LAN), and may send commands to the terminal via a local area network or the Internet to display information on the screen of the terminal.

[0052] The system 100 of the present disclosure may further include an input device 102 and / or a cursor control device 103. The input device 102 may be, for example, a keyboard or a microphone. The cursor control device 103 may be, for example, a mouse.

[0053] In the system 100 of the present disclosure, the processor 105, memory 104, input device 102, cursor control device 103, and output device 101 may be operatively coupled via a bus 108. The system 100 of the present disclosure may further include a communication interface 107, which may also be operatively coupled to other components of the system 100 of the present disclosure via the bus 108. The communication interface 107 may also be communicatively connected to a local network via a wired connection. The local network may be communicatively connected to a user's terminal via the Internet.

[0054] In one aspect, the system of the present disclosure is configured such that the time required for the program executing the first and second steps is shorter than the time required for executing a control program, wherein the control program includes instructions for recording in a memory the levels of t types of second biomarkers (t is a natural number greater than or equal to 1) contained in each biological sample obtained from a subject (number of individuals p) and a second criterion, causing a processor to calculate whether the levels of the second biomarkers recorded in the memory meet the second criterion, and causing the processor to identify the subjects (number of individuals r) from which the biological samples whose levels of the second biomarkers meet the second criterion were derived, and outputting the result to an output device. When the number of second biomarkers increases or the amount of calculation required to determine whether the second criterion is met is enormous, it is particularly beneficial that the time required for the program executing the first and second steps is shorter than the time required for executing the control program.

[0055] In one aspect, the program further includes instructions for executing one or more first criterion correction cycles, wherein the first criterion correction cycle includes: correlating the level of a first biomarker with the level of a second biomarker for each subject; learning the correlated levels of the first biomarker and the second biomarker by machine learning to construct a prediction model capable of predicting the level of the second biomarker from the level of the first biomarker; wherein the number of biological samples whose measured levels satisfy the second criterion is r (r is a natural number less than or equal to q); and correcting the first criterion based on the prediction model so that r increases without increasing q (i.e., while q remains constant or preferably decreases). This makes it possible to more effectively reduce the number of tests (q) or more effectively increase r / q in the second testing method including the second step (particularly compared to r / q in a case where the correction cycle is not included) in the first step, the preliminary method including the first step, and the first testing method.

[0056] In one aspect, the program can calculate, in the first step, the likelihood (individual likelihood) of a subject meeting the second criterion in the second step based on the level of the first biomarker. The calculation can be performed by statistical analysis or analysis using a trained model through machine learning (including deep learning). In one aspect, the program can calculate, in the first step, the likelihood (average of all subjects) of a group including all subjects subjected to the first step meeting the second criterion in the second testing method. In one aspect, the program obtains, in the first step, the average of all subjects and the individual likelihood. In one aspect, the program can calculate how high the individual likelihood is compared to the average of all subjects in the first step, the preliminary method including the first step, and the first testing method. In one preferred subject, in the first step, the program displays to the user or transmits to the user's terminal information recommending that the second testing method be performed.

[0057] In a preferred embodiment, the information recommending the implementation of the second test method can recommend the implementation of the second test method to the user with a strength corresponding to the individual possibility. The program can indicate to the user the degree of necessity to implement the second test method with a strength corresponding to the individual possibility, for example, by showing the user the individual possibility, the degree of deviation of the individual possibility from the average of all subjects, and a scored individual possibility.

[0058] In a preferred embodiment, the program may include a trained model obtained by machine learning using training data including information on whether the subject satisfies the second criterion in the second step and information on the level of the first biomarker. The program including the trained model can calculate the likelihood (individual likelihood) that the subject will satisfy the second criterion in the second step based on the level of the first biomarker. The program can, for example, indicate to the user the degree of necessity for performing the second testing method with a level of indication corresponding to the individual likelihood calculated by the trained model.

[0059] The information recommending the implementation of the second inspection method is preferably displayed on a display, but more preferably printed on paper and sent to the user.

[0060] As described above, the system of the present disclosure is useful in implementing the method of the present disclosure.

[0061] <Charging System> To realize the multi-stage inspection method of the present disclosure, a charging system according to the characteristics of the inspection method is required. For example, in a multi-stage inspection method, there is an object (object A) to which only the first step is applied, and there is also an object (object B) to which both the first step and the second step are applied. It is necessary to address the issue of whether objects A and B should be charged the same fee or whether they should be charged different fees.

[0062] In one embodiment, the billing program provides an electronic payment method for receiving a flat fee for the first and second steps from all users. The advantage of having both subjects A and B pay the same fee is that, for example, if the second step is very expensive and q is extremely small relative to p, charging everyone a flat fee can reduce the burden on subject B, who will undergo the second step. This billing method is similar to insurance. That is, many subjects can complete the test with only the first step, but if some subjects are unfortunate enough to need the second step, they can undergo the second step without the additional burden of the second step. For example, if q is 1 / 5 or less, 1 / 10 or less, more preferably 1 / 50 or less, 1 / 100 or less, even more preferably 1 / 500 or less, or 1 / 1000 or less of p, by having everyone pay subject B's cost equally, the burden on subject B can be greatly reduced with a limited increase in each user's burden. The smaller q / p, the more limited the increase in each user's burden. In some embodiments, the list price of the first step may be 1 / 5 or less, 1 / 10 or less, 1 / 50 or less, 1 / 100 or less, 1 / 500 or less, or 1 / 1000 or less of the list price of the second step.

[0063] In one embodiment, the billing program provides an electronic payment method for receiving a flat fee for the first step and the second step from all users. In this embodiment, if a subject decides not to undergo the second step in the first step, the preliminary method including the first step, and the first testing method, the billing program issues a discount coupon to the user's account for the next multi-step testing method. This billing method benefits subject A, for example, when subject A would suffer a significant financial disadvantage if he or she did not undergo the second step.

[0064] In one aspect, the billing program does not require the user to pay for the first step, the preliminary method including the first step, and the first testing method. In this aspect, the billing program provides the user with an electronic payment method for payment regarding the use of the second step by the subject. This billing method may be useful for increasing the number of users of the first step, the preliminary method including the first step, and the first testing method, thereby increasing the potential users of the second step. For example, this billing method is useful when it is difficult to opt out of the second step in the first step, the preliminary method including the first step, and the first testing method, or when the option of opting out of the second step is difficult to choose.

[0065] If a user of the second step has also used the first step, a preliminary method including the first step, and the first testing method, the fee for using the second testing method may be reduced. This may increase the number of users who enjoy a set of steps including the first and second steps. In one embodiment, the billing program may offer a discount or issue a discount coupon to the account of a user who has paid for the first step, the preliminary method including the first step, and the first testing method, offering a reduction in the fee for using the second testing method. A discount on the fee for using the second testing method may be beneficial when the testing in the second step can be simplified using the results of the first step, for example, when the biomarkers in the first and second steps overlap. Furthermore, this may encourage users who only undergo one of the steps in a set including the first and second steps to use the set of steps including the first and second steps. The discounted fee for use of the second inspection method may be equal to or less than the fee for the first step, the preliminary method including the first step, and the first inspection method.

[0066] If a user of the second step uses the first step, a preliminary method including the first step, and the first test method, the program may calculate the individual possibility in the first step and change (e.g., reduce or increase) the fee for using the second test method depending on the level of the individual possibility. In a preferred embodiment, the fee for using the second test method can be reduced when the individual possibility is higher. Users with a high individual possibility may be less motivated to use the second test method. However, reducing the fee when the individual possibility is high can encourage users who know that the individual possibility is high to use the second test method. In a preferred embodiment, the fee for using the second test method can be reduced when the individual possibility is lower. Users who know that the individual possibility is low may be less motivated to use the second test method. However, reducing the fee when the individual possibility is high can encourage users who know that the individual possibility is low to use the second test method. In one embodiment, the fee for using the second test method can be reduced as the individual possibility deviates from the average of all subjects. This can encourage the user to perform the second inspection method in either of the above cases.

[0067] The above is merely an example, but the billing program of the present disclosure may function as an insurance to reduce excessive burdens on users and maximize revenue from implementing the method of the present disclosure.

[0068] In one embodiment, the billing program provides electronic payment means for payment from all users to users of the first step, the preliminary method including the first step, and the first testing method, and the billing program also provides electronic payment means for payment to users of the second step.

[0069] In a preferred embodiment, the one or more programs may further cause the one or more processors to execute a billing program. The billing program provides the user with an electronic payment method. The electronic payment method may include one payment method or multiple selectable payment methods. The payment method may be, for example, electronic payment such as deferred payment or credit card payment. The payment method may also be payment from the balance of electronic money charged to the user's account.

Claims

1. A method for testing a plurality of biological samples obtained respectively from a plurality of subjects, comprising a first step and a second step, the second step being carried out after the first step, the first step comprising: measuring the levels of s types of first biomarkers (s is a natural number equal to or greater than 1) contained in each of the biological samples, and identifying a subject from which the biological sample having a level of the first biomarker that satisfies a first criterion is derived; and the second step comprising: measuring the levels of t types of second biomarkers (t is a natural number equal to or greater than 2, preferably a natural number greater than s) contained in each of the biological samples obtained from the subjects identified in the first step, and identifying a biological sample whose measured level satisfies a second criterion, wherein the number of biological samples analyzed in the first step is p, and the number of biological samples analyzed in the second step is q, The method of the present invention, wherein the number of biological samples whose measured levels satisfy the second criterion is r, the number of biological samples whose measured levels satisfy the second criterion when all p biological samples are subjected to the second step without performing the first step is r', and r / q is greater than r' / p, and wherein biological samples obtained from subjects from which biological samples whose measured levels in the first step do not satisfy the first criterion are derived are not analyzed in the second step, whereby p and q are natural numbers satisfying p>q.

2. A method according to claim 1, wherein a first step includes measuring the presence or absence of s types (s is a natural number equal to or greater than 1) of first biomarkers contained in each of the biological samples, and identifying a subject from which a biological sample whose presence or absence of the first biomarker satisfies a first criterion is derived.

3. The method according to claim 1 or 2, wherein the level of the first biomarker is measured by a DNA array or PCR method, and the level of the second biomarker is measured by a sequencing method.

4. The method according to claim 3, wherein the PCR method is a digital PCR method.

5. The method according to claim 3 or 4, wherein t is a natural number equal to or greater than 20.

6. A method according to any one of claims 1 to 5, wherein in the second step, association information between the level of a second biomarker in each of biological samples obtained from a plurality of subjects that has been previously measured and the health status of each of the plurality of subjects is learned by machine learning, and a prediction model constructed so as to be able to predict the health status of the subject from which the biological sample is derived from the level of the second biomarker in the biological sample includes a second criterion regarding the level of the second biomarker, and whether or not the level of the second biomarker in the biological sample satisfies the second criterion is evaluated by the prediction model.

7. The method according to any one of claims 1 to 6, further comprising one or more cycles of correction of the first criterion, the first criterion correction cycle comprising: correlating the level of the first biomarker with the level of the second biomarker for each subject; learning the correlated levels of the first and second biomarkers by machine learning to construct a predictive model capable of predicting the level of the second biomarker from the level of the first biomarker; wherein the number of biological samples whose measured levels satisfy the second criterion is r {r is a natural number less than or equal to q}; and correcting the first criterion based on the predictive model so that r becomes larger without increasing q (i.e., q is constant or preferably decreased).

8. A system for testing a plurality of biological samples obtained from a plurality of subjects, the system having one or more processors, a memory, and an output device, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs recording in the memory the levels of s types of first biomarkers (s is a natural number equal to or greater than 1) contained in each biological sample obtained from the subjects (number of individuals p) and a first criterion, causing a processor to calculate whether the levels of the first biomarkers recorded in the memory meet the first criterion, causing the processor to identify subjects (number of individuals q) from which biological samples whose levels of the first biomarker meet the first criterion are derived, and outputting the results to an output device (first step); a processor for calculating whether the levels of the second biomarkers recorded in the memory meet the second criterion, and the processor for identifying subjects (number of individuals r) from which biological samples whose levels of the second biomarkers meet the second criterion are derived, and outputting the results to the output device (second step); wherein p, q, and r are all natural numbers, p>q>r, r' is the number of biological samples whose measured levels meet the second criterion when all p biological samples are subjected to the second step, and r / q is greater than r' / p.

9. A system as described in claim 8, wherein the time required for the program executing the first and second steps is shorter than the time required for executing a control program, and the control program includes instructions for recording in a memory the levels of t types of second biomarkers (t is a natural number equal to or greater than 1) contained in each biological sample obtained from a subject (number of individuals p) and a second criterion, forcing a processor to calculate whether the levels of the second biomarkers recorded in the memory meet the second criterion, and for causing the processor to identify the subject (number of individuals r) from which the biological sample whose level of the second biomarker meets the second criterion is derived, and outputting the result to an output device.

10. The system of claim 8 or 9, wherein the program further includes instructions for performing one or more cycles of first criterion correction, the first criterion correction cycle including: correlating the levels of the first biomarker and the levels of the second biomarker for each subject; learning the correlated levels of the first and second biomarkers by machine learning to construct a predictive model capable of predicting the level of the second biomarker from the level of the first biomarker; wherein the number of biological samples whose measured levels satisfy the second criterion is r {r is a natural number less than or equal to q}; and correcting the first criterion based on the predictive model such that r becomes larger without increasing q (i.e., q remains constant or is preferably decreased).

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