Analytical systems and methods

Abstract

An assay system and method are provided. The system includes an assay zone including a binding ligand immobilized therein, the binding ligand selected from the group consisting of a binding ligand that binds free prostate specific antigen (fPSA), a binding ligand that binds intact prostate specific antigen (iPSA), a binding ligand that binds total prostate specific antigen (tPSA), and a binding ligand that binds human kallikrein 2 (hK2); at least one detector that detects the presence of an analyte in a sample from the assay zone, the analyte selected from the group consisting of tPSA, fPSA, iPSA, and hK2; and a processor programmed to: scale a plurality of variables by different coefficient values to produce scaled variables, the plurality of variables including age and at least two variables selected from the group consisting of fPSA, iPSA, and tPSA having values included in information received from the detector; sum the values of the scaled variables to produce a probability of a prostate cancer related event for the person; and output an indication of the probability of the prostate cancer related event.

Description

[0001] This patent application is a divisional application of the invention patent application with an international filing date of March 5, 2013, national application number 201380021939.X, and an invention title of "Method and Apparatus for Predicting Prostate Cancer Risk and Prostate Gland Volume". Technical Field

[0002] This invention relates to analytical systems and methods. More specifically, this invention relates to analytical systems and methods, solid-phase analysis systems, methods for predicting the risk of prostate cancer in subjects, and methods for determining whether a prostate biopsy is worthwhile. Background Technology

[0003] Most men with elevated blood levels of total prostate-specific antigen (PSA) (the most common trigger in US male biopsies) do not have prostate cancer. Therefore, it is estimated that nearly 750,000 unnecessary prostate biopsies are performed annually in the US. There is considerable evidence that measuring PSA isoforms separately, rather than combining them in a single measurement of total PSA, can help predict the presence of prostate cancer. These data include studies demonstrating the prediction of cancer using free PSA, BPSA, or -2proPSA. In practice, free PSA is often measured alone, with urologists obtaining results based on total PSA and the ratio of free PSA to total PSA; an estimated 10 million free PSA measurements are performed annually. There is also evidence that hK2 (the molecule that converts PSA from its undiluted form to its active form) provides information about prostate risk. However, none of these indicators themselves constitute a good predictor of prostate biopsy results.

[0004] Several attempts have been made to develop predictive models for prostate cancer, most notably the "Prostate Cancer Prevention Trial Risk Calculator," "Sunnybrook," and the European Randomized Screening Trial for Prostate Cancer (ERSPC) Risk Calculator. The problem with these models is that they all require, to varying degrees, extensive clinical examinations; that is, patients need to consult a urologist. For example, the ERSPC Risk Calculator requires data on prostate volume, which is obtained by inserting an ultrasound probe into the rectum. Therefore, new methods and devices for predicting prostate cancer risk and / or prostate gland volume would be beneficial. Summary of the Invention

[0005] Methods and apparatus for predicting prostate cancer risk and / or prostate gland volume are provided. More specifically, the present invention relates to methods and apparatus for providing models and using the models to predict prostate cancer risk and / or predict prostate gland volume. In some embodiments, methods and apparatus for predicting prostate cancer risk and / or prostate gland volume are provided, using at least in part information from a set of kallikrein indicators. In some cases, the subject matter of this application relates to a number of different uses of related methods, alternative solutions to specific problems, and / or systems and devices.

[0006] One object of the present invention is to provide a method for predicting the risk of prostate cancer in men by using a logistic regression model to obtain the probability of events.

[0007] In one set of embodiments, a computer is provided for determining the probability of prostate cancer-related events. The computer includes an input interface configured to receive information on a plurality of blood indicators, wherein the information on the plurality of blood indicators includes free prostate-specific antigen (fPSA) values ​​and total PSA (tPSA) values. The computer also includes at least one processor programmed to evaluate a logistic regression model, at least in part, based on the received information, thereby determining the probability of prostate cancer-related events in a person. The evaluation of the logistic regression model includes: determining cubic spline terms of tPSA, wherein determining cubic spline terms of tPSA comprises determining cubic spline terms of tPSA based on a first cubic spline having a first internal node between 2 and 5 and a second internal node between 5 and 8; determining cubic spline terms of fPSA, wherein determining cubic spline terms of fPSA comprises determining cubic spline terms of fPSA based on a second cubic spline having a third internal node between 0.25 and 1 and a fourth internal node between 1.0 and 2.0; determining a first value of tPSA based at least in part on the received tPSA value and the determined cubic spline terms of tPSA; determining a second value of fPSA based at least in part on the received fPSA value and the determined cubic spline terms of fPSA; and determining the probability of prostate cancer-related events based at least in part on the first and second values. The computer also includes an output interface configured to output an indication of the probability of prostate cancer-related events.

[0008] In one set of embodiments, a system for determining the probability of prostate cancer-related events is provided. The system includes a detector configured to measure values ​​of a plurality of blood indicators, wherein the plurality of blood indicators include free prostate-specific antigen (fPSA), total PSA (tPSA), and intact PSA (iPSA). The system also includes at least one processor in electronic communication with the detector. The at least one processor is programmed to evaluate a logistic regression model based at least in part on the measurements of fPSA, tPSA, and iPSA to determine the probability of a person having a high-grade prostate cancer-related event. The evaluation of the logistic regression model includes: determining cubic spline terms of tPSA, wherein determining cubic spline terms of tPSA comprises determining cubic spline terms of tPSA based on a first cubic spline having a first internal node between 4 and 5 and a second internal node between 6 and 8; determining cubic spline terms of fPSA, wherein determining cubic spline terms of fPSA comprises determining cubic spline terms of fPSA based on a second cubic spline having a third internal node between 0.25 and 1 and a fourth internal node between 1.0 and 2.0; determining a first value of tPSA based at least in part on the received tPSA value and the determined cubic spline terms of tPSA; determining a second value of fPSA based at least in part on the received fPSA value and the determined cubic spline terms of fPSA; determining the probability of prostate cancer-related events based at least in part on the first and second values; and outputting an indication of the probability of prostate cancer-related events.

[0009] In one set of embodiments, a method is provided for determining the probability of prostate cancer-related events. The method includes receiving information on a plurality of blood indicators via an input interface, wherein the information on the plurality of blood indicators includes free prostate-specific antigen (fPSA) values ​​and total PSA (tPSA) values. The method further includes using at least one processor to evaluate a logistic regression model, at least in part, based on the received information, to determine the probability of prostate cancer-related events in a person. The evaluation of the logistic regression model includes determining cubic spline terms of tPSA, wherein determining cubic spline terms of tPSA comprises determining cubic spline terms of tPSA based on a first cubic spline having a first internal node between 2 and 5 and a second internal node between 5 and 8; determining cubic spline terms of fPSA, wherein determining cubic spline terms of fPSA comprises determining cubic spline terms of fPSA based on a second cubic spline having a third internal node between 0.25 and 1 and a fourth internal node between 1.0 and 2.0; determining a first value of tPSA based at least in part on the received tPSA value and the determined cubic spline terms of tPSA; determining a second value of fPSA based at least in part on the received fPSA value and the determined cubic spline terms of fPSA; and determining the probability of prostate cancer-related events based at least in part on the first and second values. The method also includes outputting an indication of the probability of prostate cancer-related events.

[0010] In one set of embodiments, a computer-readable storage medium encoded with a plurality of instructions, when executed by a computer, performs a method for determining the probability of prostate cancer-related events. The method includes receiving information on a plurality of blood indicators, including free prostate-specific antigen (fPSA) values ​​and total PSA (tPSA) values, and evaluating a logistic regression model, at least in part, based on the received information, to determine the probability of prostate cancer-related events in a person. The evaluation of the logistic regression model includes: determining cubic spline terms of tPSA, wherein determining cubic spline terms of tPSA comprises determining cubic spline terms of tPSA based on a first cubic spline having a first internal node between 2 and 5 and a second internal node between 5 and 8; determining cubic spline terms of fPSA, wherein determining cubic spline terms of fPSA comprises determining cubic spline terms of fPSA based on a second cubic spline having a third internal node between 0.25 and 1 and a fourth internal node between 1.0 and 2.0; determining a first value of tPSA based at least in part on the received tPSA value and the determined cubic spline terms of tPSA; determining a second value of fPSA based at least in part on the received fPSA value and the determined cubic spline terms of fPSA; and determining the probability of prostate cancer-related events based at least in part on the first and second values. The method also includes outputting an indication of the probability of prostate cancer-related events.

[0011] In one set of embodiments, a computer is provided for determining the probability of prostate cancer-related events. The computer includes an input interface configured to receive information on a plurality of blood indicators, including free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The computer also includes at least one processor programmed to evaluate a logistic regression model, at least in part, based on the received information, to determine the probability of prostate cancer-related events in a person. Evaluating the logistic regression model includes determining the probability of prostate cancer-related events based at least in part on tPSA values, iPSA values, hK2 values, and the ratio of fPSA values ​​to tPSA values. The computer also includes an output interface configured to output an indication of the probability of prostate cancer-related events.

[0012] In one set of embodiments, a method for determining the probability of prostate cancer-related events is provided. The method includes: receiving information from a plurality of blood indicators via an input interface, wherein the information from the plurality of blood indicators includes free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values; evaluating a logistic regression model using at least one processor, at least in part based on the received information, to determine the probability of prostate cancer-related events in a person. Evaluating the logistic regression model includes determining the probability of prostate cancer-related events based at least in part on tPSA values, iPSA values, hK2 values, and the ratio of fPSA values ​​to tPSA values; and outputting an indication of the probability of prostate cancer-related events.

[0013] In one set of embodiments, a computer-readable storage medium encoded with a plurality of instructions, when executed by a computer, performs a method for determining the probability of a prostate cancer-related event. The method includes receiving information from a plurality of blood indicators via an input interface, wherein the information from the plurality of blood indicators includes free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values; evaluating a logistic regression model using at least one processor based at least in part on the received information to determine the probability of a prostate cancer-related event in a person. Evaluating the logistic regression model includes determining the probability of a prostate cancer-related event based at least in part on tPSA values, iPSA values, hK2 values, and the ratio of fPSA values ​​to tPSA values; and outputting an indication of the probability of a prostate cancer-related event.

[0014] In one set of embodiments, a computer is provided for determining the probability of prostate cancer-related events. The computer includes an input interface configured to receive information on a plurality of blood indicators, including free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The computer also includes at least one processor programmed to evaluate a logistic regression model at least in part based on the received information to determine the probability of a prostate cancer-related event in a person. Evaluating the logistic regression model includes: determining a nonlinear term for tPSA by multiplying the tPSA value by a first exponent; determining a nonlinear term for fPSA by multiplying the fPSA value by a second exponent; and determining the probability of a prostate cancer-related event at least in part based on the tPSA value, fPSA value, iPSA value, hK2 value, the nonlinear term for tPSA, and the nonlinear term for fPSA. The computer also includes an output interface configured to output an indication of the probability of a prostate cancer-related event.

[0015] In one set of embodiments, a method for determining the probability of a prostate cancer-related event is provided. The method includes receiving information from a plurality of blood indicators via an input interface, wherein the information from the plurality of blood indicators includes free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The method further includes evaluating a logistic regression model to determine the probability of a prostate cancer-related event in a person using at least one processor, based at least in part on the received information. Evaluating the logistic regression model includes determining a nonlinear term for tPSA by multiplying the tPSA value by a first exponent, determining a nonlinear term for fPSA by multiplying the fPSA value by a second exponent, and determining the probability of a prostate cancer-related event based at least in part on the tPSA value, fPSA value, iPSA value, hK2 value, the nonlinear term for tPSA, and the nonlinear term for fPSA. The method also includes outputting an indication of the probability of a prostate cancer-related event.

[0016] In one set of embodiments, a computer-readable storage medium encoded with a plurality of instructions, when executed by a computer, performs a method for determining the probability of a prostate cancer-related event. The method includes receiving information on a plurality of blood indicators, wherein the information on the plurality of blood indicators includes free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The method further includes evaluating a logistic regression model to determine the probability of a prostate cancer-related event in a person, based at least in part on the received information. Evaluating the logistic regression model includes determining a nonlinear term for tPSA by multiplying the tPSA value by a first exponent, determining a nonlinear term for fPSA by multiplying the fPSA value by a second exponent, and determining the probability of a prostate cancer-related event based at least in part on the tPSA value, fPSA value, iPSA value, hK2 value, the nonlinear term for tPSA, and the nonlinear term for fPSA. The method further includes outputting an indication of the probability of a prostate cancer-related event.

[0017] In one set of embodiments, a computer is provided for determining the probability of a prostate cancer-related event. The computer includes an input interface configured to receive information on a plurality of blood indicators, including free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The computer also includes at least one processor programmed to evaluate a logistic regression model based at least in part on the received information to determine the probability of a prostate cancer-related event in a person. Evaluating the logistic regression model includes: determining linear spline terms for tPSA, determining linear spline terms for fPSA, determining a first value of tPSA based at least in part on the received tPSA value and the determined linear spline terms of tPSA, determining a second value of fPSA based at least in part on the received fPSA value and the determined linear spline terms of fPSA, and determining the probability of a prostate cancer-related event based at least in part on the first and second values. The computer also includes an output interface configured to output an indication of the probability of a prostate cancer-related event.

[0018] In one set of embodiments, a method for determining the probability of a prostate cancer-related event is provided. The method includes receiving information from a plurality of blood indicators via an input interface, wherein the information from the plurality of blood indicators includes free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The method further includes evaluating a logistic regression model using at least one processor, at least partially based on the received information, to determine the probability of a prostate cancer-related event in a person. Evaluating the logistic regression model includes: determining linear spline terms for tPSA, determining linear spline terms for fPSA, determining a first value of tPSA at least partially based on the received tPSA value and the determined linear spline terms of tPSA, determining a second value of fPSA at least partially based on the received fPSA value and the determined linear spline terms of fPSA, and determining the probability of a prostate cancer-related event at least partially based on the first and second values. The method further includes outputting an indication of the probability of a prostate cancer-related event.

[0019] In one set of embodiments, a computer-readable storage medium is encoded with a plurality of instructions that, when executed by a computer, perform a method for determining the probability of a prostate cancer-related event. The method includes receiving information on a plurality of blood indicators, wherein the information on the plurality of blood indicators includes free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and human kallikrein 2 (kK2) values. The method also includes evaluating a logistic regression model to determine the probability of a prostate cancer-related event in a person, based at least in part on the received information. Evaluating the logistic regression model includes determining linear spline terms for tPSA, determining linear spline terms for fPSA, determining a first value of tPSA based at least in part on the received tPSA value and the determined linear spline terms of tPSA, determining a second value of fPSA based at least in part on the received fPSA value and the determined linear spline terms of fPSA, and determining the probability of a prostate cancer-related event based at least in part on the first and second values. The method also includes outputting an indication of the probability of a prostate cancer-related event.

[0020] In one set of embodiments, a system for determining the risk of high-grade cancer is provided. The system includes an input interface configured to receive information from a plurality of blood indicators, including free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, intact PSA (iPSA) values, and hK2 values. The system also includes at least one processor programmed to input the received values ​​into a logistic regression model, wherein at least the tPSA value and the fPSA value are input into the logistic regression model using linear and nonlinear terms, and to evaluate the logistic regression model to determine the risk of high-grade cancer.

[0021] In one set of embodiments, a system for determining the probability of prostate cancer-related events in a person is provided. The system includes a microfluidic sample analyzer comprising a housing and an opening in the housing configured to receive a cartridge having at least one microfluidic channel, wherein the housing includes components configured to interface with mating components on the cartridge to detect the cartridge within the housing. The system also includes a pressure control system located within the housing, configured to pressurize the at least one microfluidic channel in the cartridge, thereby allowing a sample to pass through the at least one microfluidic channel. The system further includes an optical system located within the housing, comprising at least one light source and at least one detector spaced apart from the light source, wherein the light source is configured to allow light to pass through the cartridge when the cartridge is inserted into the sample analyzer, and wherein the detector is located opposite the light source to detect the amount of light passing through the cartridge. The system includes a user interface associated with a housing for inputting at least a person's age and a processor that communicates electronically with a microfluidic sample analyzer. The processor is programmed to evaluate a logistic regression model, at least in part, based on information received from the at least one detector, to determine the probability of a person experiencing prostate cancer-related events. The evaluation of the logistic regression model includes scaling each of a plurality of variables by different coefficient values ​​to produce calibrated variables, and summing the values ​​of the calibrated variables to produce the probability of a person experiencing prostate cancer-related events. The plurality of variables includes age and at least two variables included in the information received from the detector and selected from the group consisting of fPSA, iPSA, and tPSA.

[0022] In one set of embodiments, a method for determining the probability of prostate cancer-related events in a person is provided. The method relates to providing a microfluidic sample analyzer including a housing with an opening configured to receive a cartridge having at least one microfluidic channel, wherein the housing includes components configured to connect with mating components on the cartridge to detect the cartridge within the housing, and a pressure control system located within the housing, the pressure control system being configured to pressurize the at least one microfluidic channel in the cartridge, thereby allowing a sample to pass through the at least one microfluidic channel. The microfluidic sample analyzer also includes an optical system located within the housing, the optical system including at least one light source and at least one detector spaced apart from the light source, wherein the light source is configured to allow light to pass through the cartridge when the cartridge is inserted into the sample analyzer, and wherein the detector is located opposite the light source to detect the amount of light passing through the cartridge, and a user interface associated with the housing for at least inputting the person's age. The method involves using a microfluidic sample analyzer to determine information on multiple blood parameters, including free prostate-specific antigen (fPSA) values, total PSA (tPSA) values, and intact PSA (iPSA) values, and using at least one processor to evaluate a logistic regression model at least partially based on this information to determine the probability of a person having prostate cancer-related events. The evaluation of the logistic regression model includes calibrating each of the multiple variables by different coefficient values ​​to produce calibrated variables, and summing the values ​​of the calibrated variables to produce the probability of a person having prostate cancer-related events. The multiple variables include age and at least two variables included in and selected from a group consisting of fPSA, iPSA, and tPSA, as received from the detector.

[0023] In one set of embodiments, a system is provided. The system includes an apparatus comprising a first analytical region containing a first binding ligand and a second analytical region containing a second binding ligand, wherein the first binding ligand is adapted to bind to at least one of free prostate-specific antigen (fPSA), intact prostate-specific antigen (iPSA), and total PSA (tPSA), and wherein the second binding ligand is adapted to bind to at least another of fPSA, iPSA, and tPSA. The system includes a detector and a processor associated with the first and second analytical regions, the processor being programmed to evaluate a logistic regression model, at least in part, based on information received from the detector, to determine the probability of a prostate cancer-related event in a person, wherein evaluating the logistic regression model includes scaling each of a plurality of variables by different coefficient values ​​to produce scaled variables, and summing the values ​​of the scaled variables to produce the probability of a prostate cancer-related event in a person, wherein the plurality of variables includes age and at least two variables included in the information received from the detector and selected from the group comprising fPSA, iPSA, and tPSA.

[0024] In one set of embodiments, a method is provided. The method includes introducing a sample into a device including a first analytical region containing a first binding ligand and a second analytical region containing a second binding ligand, wherein the first binding ligand is adapted to bind to at least one of free prostate-specific antigen (fPSA), intact prostate-specific antigen (iPSA), and total PSA (tPSA), and wherein the second binding ligand is adapted to bind to at least another of fPSA, iPSA, and tPSA. The method involves binding any one of fPSA, iPSA, and / or tPSA of a sample to a first and a second analytical region with a first binding ligand and / or a second binding ligand, determining the characteristics of fPSA, iPSA, and / or tPSA using one or more detectors associated with the first and second analytical regions, inputting the characteristics of fPSA, iPSA, and / or tPSA into a processor, the processor being programmed to evaluate a logistic regression model at least in part based on information received from the at least one detector to determine the probability of a prostate cancer-related event in a person, wherein evaluating the logistic regression model includes scaling each of a plurality of variables by different coefficient values ​​to produce calibrated variables, and summing the values ​​of the calibrated variables to produce the probability of a prostate cancer-related event in a person, wherein the plurality of variables includes age and at least two variables included in and selected from the group including fPSA, iPSA, and tPSA from the information received from the detector, and determining the probability of a prostate cancer-related event.

[0025] In one set of embodiments, a device is provided. The device includes a microfluidic system comprising: a first microfluidic channel including at least one inlet and one outlet; a first reagent stored in the first microfluidic channel; a seal covering the inlet of the first microfluidic channel and a seal covering the outlet of the first microfluidic channel, such that the first reagent is stored in the first microfluidic channel; and a second microfluidic channel including at least one inlet and one outlet. The device further includes a first analytical region, a second analytical region, and a third analytical region, each of which includes one of an anti-iPSA specific capture antibody, an anti-fPSA specific capture antibody, and an anti-tPSA specific capture antibody, wherein one or more of the first, second, and third analytical regions are in fluid communication with the second microfluidic channel. The device also includes a fluid connector connectable to a microfluidic system, wherein the fluid connector includes a fluid path having a fluid path inlet and a fluid path outlet, wherein, upon connection, the fluid path inlet connects to the outlet of a first microfluidic channel to provide fluid communication between the fluid path and the first microfluidic channel, and the fluid path outlet connects to the inlet of a second microfluidic channel to provide fluid communication between the fluid path and the second microfluidic channel, wherein the first and second microfluidic channels are not fluidly communication with each other when not connected by the fluid connector. The device also includes a metal colloid source conjugated with an antibody bound to anti-PSA.

[0026] In one set of embodiments, a method is provided to obtain the probability of an event using a logistic regression model for predicting the risk of prostate cancer in men. The method includes the following steps:

[0027] a) Provide a logistic regression model obtained through multivariate logistic regression using data from a large number of men, including prostate cancer status data for each man and prior data, including age; and blood parameters from these men's blood samples, total prostate-specific antigen (tPSA), free PSA (fPSA), intact PSA (iPSA), and optionally human kallikrein 2 (hK2) values, wherein the logistic regression model is generated using the following formula:

[0028]

[0029] Where π is the probability of the event, β i For variable x i The logistic regression model is obtained by taking the coefficients of j variables, including age, tPSA, fPSA, iPSA, and optional hK2.

[0030] b) Provide the male's age (in years);

[0031] c) Determine the blood indicators in the blood samples of the males respectively.

[0032] i)tPSA,

[0033] ii)fPSA,

[0034] iii) iPSA,

[0035] iv) Optional hK2;

[0036] d) Using the age provided in step b) and the blood parameters determined in step c), the probability of the event for the male is obtained using the logistic regression model as follows:

[0037] i) Define the formula used: as well as

[0038] ii) with The probability of obtaining the form is obtained.

[0039] The method is characterized in that, in the logistic regression model, if tPSA ≥ 15 ng / ml, preferably tPSA ≥ 20 ng / ml, and most preferably tPSA ≥ 25 ng / ml, then the cancer risk is based solely on tPSA.

[0040] Another object of the present invention is to provide a method for predicting prostate gland volume using a linear regression model.

[0041] Embodiments of the present invention provide a method for predicting prostate gland volume using a linear regression model, wherein the method includes the following steps:

[0042] a) Provide a linear regression model, which is obtained by linear regression using data from a large number of men, said data including the following data for each of the large number of men.

[0043] i) Data regarding prostate gland volume, and

[0044] ii) Prior data regarding prostate gland volume, including age; and determined values ​​of the following blood parameters in the male's blood sample: total prostate-specific antigen (tPSA), free PSA (fPSA), intact PSA (iPSA), and optionally human kallikrein 2 (hK2), wherein the linear regression model is generated using the following formula:

[0045] Where V is the volume of the prostate gland, β i For variable x iThe linear regression model is obtained by taking the coefficients of j variables (including age, tPSA, fPSA, iPSA, and optional hK2) respectively.

[0046] b) Provide the male's age (in years);

[0047] c) Determine the blood indicators in the blood samples of the males: tPSA, fPSA, iPSA, and optionally hK2;

[0048] d) Using the age provided in step b) and the blood parameters determined in step c), the linear regression model is used to obtain the predicted prostate volume of the male.

[0049] The method is characterized in that, in the linear regression model, if tPSA ≥ 15 ng / ml, preferably tPSA ≥ 20 ng / ml, and most preferably tPSA ≥ 25 ng / ml, then the cancer risk is based solely on tPSA.

[0050] An analytical system is provided according to an embodiment of the present invention. The system includes: an analytical region comprising one or more binding ligands immobilized therein in a solid phase portion, wherein the one or more binding ligands are selected from the group consisting of binding ligands binding free prostate-specific antigen (fPSA), binding ligands binding intact prostate-specific antigen (iPSA), binding ligands binding total prostate-specific antigen (tPSA), and binding ligands binding human kallikrein 2hK2; and at least one detector configured to detect the presence of an analyte in a sample from the analytical region, wherein the analyte is selected from the group consisting of... The system comprises the group consisting of tPSA, fPSA, iPSA, and hK2; and a processor programmed to: calibrate each of a plurality of variables by different coefficient values ​​to produce calibrated variables, wherein the plurality of variables includes age and at least two variables having values ​​included in information received from the at least one detector, wherein the at least two variables are selected from the group consisting of fPSA, iPSA, and tPSA; sum the values ​​of the calibrated variables to produce the probability of a person’s prostate cancer-related events; and output an indication of the probability of the prostate cancer-related events.

[0051] An embodiment of the present invention provides a method. The method includes: detecting the presence of an analyte in a sample from an analytical region of an analytical system by at least one detector, the analytical region including one or more binding ligands immobilized therein, wherein the one or more binding ligands are selected from the group consisting of binding ligands binding total prostate-specific antigen tPSA, binding ligands binding free prostate-specific antigen fPSA, binding ligands binding intact prostate-specific antigen iPSA, and binding ligands binding human kallikrein 2hK2, wherein the analyte is selected from the group consisting of tPSA, fPSA, iPSA, and hK2; calibrating each of a plurality of variables by at least one computer processor with different coefficient values ​​to generate calibrated variables, wherein the plurality of variables includes age and at least two variables included in information received from the at least one detector, wherein the at least two variables are selected from the group consisting of fPSA, iPSA, and tPSA; summing the values ​​of the calibrated variables by the at least one computer processor to generate a probability of prostate cancer-related events; and outputting an indication of the probability of prostate cancer-related events.

[0052] An analytical system is provided according to an embodiment of the present invention. The system includes: at least one detector configured to detect the presence of an analyte in a sample from an analytical region, the analytical region including one or more binding ligands immobilized therein on a solid phase portion, wherein the one or more binding ligands are selected from the group consisting of binding ligands binding total prostate-specific antigen (tPSA), binding ligands binding free prostate-specific antigen (fPSA), binding ligands binding intact prostate-specific antigen (iPSA), and binding ligands binding human kallikrein 2hK2, wherein the analyte is selected from the group consisting of tPSA, fPSA, iPSA, and hK2. A group; and a non-volatile computer-readable storage medium encoded with a plurality of instructions, which, when executed by a computer processor, perform a method, wherein the method includes: scaling each of a plurality of variables by different coefficient values ​​to produce a scaled variable, wherein the plurality of variables includes age and at least two variables included in information received from the at least one detector, wherein the at least two variables are selected from the group including fPSA, iPSA, and tPSA; summing the values ​​of the scaled variable to produce a probability of a prostate cancer-related event; and outputting an indication of the probability of the prostate cancer-related event.

[0053] According to embodiments of the present invention, a solid-phase analysis system is provided. The system includes: a chip comprising a substantially rigid substrate having two or more liquid-containing barrier regions, each liquid-containing barrier region having one or more analytical regions, wherein each analytical region includes one or more binding ligands fixed to a portion of the substrate therein, wherein the two or more liquid-containing barrier regions are not fluidly connected, wherein the binding ligands bind one or more kallikrein proteins; and a detector configured to measure values ​​of a plurality of kallikrein proteins.

[0054] An embodiment of the present invention provides a method for predicting the risk of prostate cancer in a subject. The method includes: subjecting a fluid sample from the subject to multiplexing analysis, the multiplexing analysis being configured to determine the levels of at least the following kallikrein enzymes: tPSA, fPSA, iPSA, and hK2; and assessing the risk of prostate cancer based on the results of the multiplexing analysis.

[0055] An embodiment of the present invention provides a method for determining whether a prostate biopsy is worthwhile. The method includes: obtaining a blood sample from a subject; subjecting serum or plasma from the blood sample to multiplexing, the multiplexing being configured to determine the levels of at least the following kallikrein enzymes: tPSA, fPSA, iPSA, and hK2; and using a predictive algorithm, based on the levels of the kallikrein enzymes, to determine the statistical probability that the biopsy will be positive for prostate cancer. Attached Figure Description

[0056] Non-limiting embodiments of the present invention will be described by way of example with reference to the accompanying drawings, which are schematic and not intended to be drawn to scale. In the drawings:

[0057] Figure 1 A flowchart illustrating a method for determining the probability of a positive cancer biopsy according to some embodiments of the present invention is shown.

[0058] Figure 2 A flowchart illustrating a method for conditionally selecting a logistic regression model according to some embodiments of the present invention;

[0059] Figure 3 A schematic diagram of a computer system in which some embodiments of the present invention may be implemented is shown;

[0060] Figure 4 This invention illustrates exemplary network environments in which some embodiments of the invention may be used;

[0061] Figure 5 This is a block diagram illustrating a microfluidic system and various components that can be used as part of a sample analyzer according to some embodiments of the present invention, the sample analyzer being used to determine one or more blood parameters;

[0062] Figure 6 This is a perspective view of a sample analyzer and cartridge that can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0063] Figure 7 This is a perspective view of a cartridge including a fluid connector, which can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0064] Figure 8 This is an exploded assembly view of a fluid connector that can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0065] Figure 9 This is an exploded view of an assembled cartridge that can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0066] Figure 10 This is a schematic diagram of a cartridge including a fluid connector that can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0067] Figure 11A This is a schematic diagram of a cartridge that can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0068] Figures 11B-11F This is a schematic diagram of a cartridge formed of multiple components, according to a set of embodiments, which can be used to determine one or more blood parameters;

[0069] Figure 12 This is a schematic diagram of a portion of a sample analyzer that can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0070] Figure 13 This is a block diagram illustrating a control system of a sample analyzer associated with a variety of different components, which can be used to determine one or more blood parameters according to some embodiments of the present invention;

[0071] Figure 14 This is a schematic diagram illustrating a microfluidic system of a cartridge that can be used to determine one or more blood parameters according to some embodiments of the present invention; and

[0072] Figure 15 This is a graph showing the determination of one or more blood indicators as a function of optical density measurement versus time, according to some embodiments of the present invention. Detailed Implementation

[0073] As discussed above, many conventional techniques for predicting the probability of prostate cancer and / or prostate gland volume are at least partially based on a clinical examination of the patient (e.g., digital rectal examination or DRE). Some embodiments described herein relate to methods and apparatus for determining the predicted probability of prostate cancer and / or prostate gland volume based at least partially on a set of blood parameters without clinical examination. As discussed in further detail below, the predicted probability of prostate cancer and / or prostate gland volume provided by a biopsy is a reliable measure that can be used to aid in making judgments related to prostate biopsy.

[0074] Some embodiments relate to a computer system including at least one processor programmed to assess the risk of prostate cancer, wherein the risk is determined at least in part based on values ​​of a plurality of blood indicators. In some embodiments, the computer system may be implemented as an integrated system having one or more detectors (e.g., on an analyzer and / or chip / cassette) that determine the values ​​of the one or more blood indicators described herein. In other embodiments, the computer system may include a computer located remotely from the one or more detectors and may receive the values ​​of the one or more blood indicators described herein via a user interface manually entered and / or via a network interface communicatively coupled to a network (e.g., the Internet). At least one processor in the computer system may be programmed to apply the received input data to one or more models after a biopsy to assess the risk of prostate cancer, as discussed in more detail below.

[0075] The models used in some embodiments of the present invention facilitate the integration of information from multiple input factors. For example, input factors may be PSA, the ratio of free PSA to total PSA, and / or digital rectal examination (DRE) status. Continuing with this example, a first patient may have a PSA of 3 ng / ml, a free PSA to total PSA ratio of 15%, and a negative DRE; a second patient may have a PSA of 9.5 ng / ml, a free PSA to total PSA ratio of 50%, and a negative DRE; and a third patient may have a PSA of 1.5 ng / ml, a free PSA to total PSA ratio of 29%, and a positive DRE. For the first patient, given the moderate PSA and negative DRE, a urologist may wonder whether a low (however, not extremely low) free PSA to total PSA ratio is sufficient to warrant a biopsy. For the second patient, a high PSA value generally warrants immediate biopsy, but an extremely high free PSA to total PSA ratio strongly suggests that the PSA elevation is not benign. For the third patient, a positive DRE is generally a very worrying sign, but given the low PSA and normal free PSA to total PSA ratio, it is insufficient to warrant a biopsy. As understood above, when these factors are presented to the physician in isolation, it can be difficult to determine when a biopsy is necessary. Furthermore, as the number of input factors increases, determining whether to perform a biopsy based on numerical information from different input factors becomes even more complex.

[0076] Patients and clinicians differ in their preferences regarding the choice of biopsy, depending on how they evaluate early cancer screening in light of the risks, harms, and inconveniences compared to a biopsy. It is often impractical to combine these preferences using strict judgment rules (e.g., performing a biopsy if PSA > 4 ng / ml or the ratio of free PSA to total PSA < 15%) or risk scores (e.g., a prostate health index (PHI) score of 29). For example, if a man is reluctant to undergo medical procedures, it may be difficult to determine how high a PSA and / or PHI score would be "high enough" to warrant a biopsy.

[0077] According to some embodiments, at least one processor is programmed to process multiple input data using one or more statistical models to guide the judgment regarding prostate biopsies, rather than using strict judgment rules. The input data to the statistical models may include, but is not limited to, blood parameters, patient characteristics (e.g., age), and other suitable information to determine the probability of a positive prostate cancer biopsy. This probability represents an interpretable scale that can be used to guide the biopsy judgment, taking into account patient and clinician preferences.

[0078] Figure 1A flowchart illustrating some embodiments of the present invention is provided. In action 110, one or more blood indicator values ​​are received by at least one processor for processing using one or more techniques described herein. As described in more detail below, the blood indicator values ​​(multiple blood indicator values) can be received in any suitable manner, including, but not limited to, from a network-connected interface (which receives the values ​​from a device located remotely from the processor) or directly from one or more detectors that measure the blood indicator values ​​(e.g., in an implementation where the processor is integrated with a measuring device including one or more detectors) via a local input interface (e.g., a keyboard, touchscreen, microphone, or other input device).

[0079] In response to receiving blood marker values, the method proceeds to action 120, whereby at least one logistic regression model is evaluated to determine the probability of a positive prostate cancer biopsy, wherein the probability is at least partially based on the received blood marker values. As described in further detail below, information other than the received blood marker values ​​(e.g., age, cancer grade, etc.) may optionally be used as factors in determining the specific model to be used and / or as input factors for evaluating the selected model.

[0080] After determining the probability of a positive cancer biopsy, the method proceeds to action 130, whereby the probability is output to a user (e.g., a physician, patient) to guide the decision-making process regarding whether a biopsy is necessary. The probability can be output in any suitable manner. For example, in some embodiments, the probability can be output by displaying a numerical value representing the probability on a device's display screen. In other embodiments, one or more lights or other visual indicators on the device can be used to output the probability. In other embodiments, the probability can be provided using audio output, haptic output, or some combination of audio output, haptic output, and visual output. In some embodiments, outputting the probability includes sending information to a network-connected device to inform the user about the determined probability. For example, the probability can be determined by one or more processors located remotely, and in response to determining the probability remotely, one or more networks can be used to send the probability indication to an electronic device of a user (e.g., a physician). The electronic device providing output to the user according to the techniques described herein can be any suitable device, including, but not limited to, laptop computers, desktop computers or tablet computers, smartphones, pagers, personal digital assistants, and electronic displays.

[0081] As discussed above, some embodiments aim to provide a method for obtaining event odds using a logistic regression model that predicts prostate cancer risk and / or prostate gland volume in men. In some embodiments, the method involves including information based on one or more kallikrein indicators (i.e., total prostate-specific antigen (tPSA), free PSA (fPSA), intact PSA (iPSA), and human kallikrein 2 (hK2)). Any suitable logistic regression model can be used, and the techniques described herein are not limited thereto. In some embodiments, the event odds are determined according to equation (I), reproduced as follows:

[0082]

[0083] The logit (L) is determined using any one of several logistic regression models. Non-limiting examples of nine different types of logistic regression models that can be used according to the techniques described herein include:

[0084] 1. Simple model (tPSA only)

[0085] L=β0+β1(Age)+β2(tPSA)

[0086] 2. Use the four-term analysis model of free / total ratio.

[0087] In this model, the ratio of free PSA to total PSA is substituted into the free PSA term.

[0088]

[0089] 3. A four-term analytical model using log(tPSA) and the free / total ratio.

[0090] In this model, the logarithm of tPSA is substituted into the tPSA term to illustrate the effect of this predictor's increase.

[0091]

[0092] 4. Polynomial Model

[0093] This model includes other nonlinear terms for tPSA and fPSA. In the example equations provided below, the square of tPSA is used to emphasize the direct relationship between this term and the risk of prostate cancer, and the square root of the free PSA / total PSA term is used to reflect the inverse correlation between this term and the risk. However, it should be understood that some embodiments may also include higher-order (e.g., cubic) polynomial terms.

[0094]

[0095] 5. Linear splines for all four analyses

[0096] In this model, a linear spline with a single node at the median is added. This spline can be determined using the following equation:

[0097] If x < node, then Sp1(x) = x

[0098] If x ≥ node, then Sp1(x) = node

[0099] If x < node, then Sp2(x) = 0

[0100] If x ≥ node, then Sp2(x) = x - node

[0101] The model is represented as follows:

[0102] L=β0+β1(Age)+β2(tPSA)+β3(fPSA)+β4(iPSA)+β5(hK2)+β6(sp1[tPSA])

[0103] +β7(sp2[tPSA])+β8(sp1[fPSA])+β9(sp2[fPSA])+β 10 (sp1[iPSA])+β 11 (sp2[iPSA])

[0104] +β 12 (sp1[hK2])+β 13 (sp2[hK2])

[0105] 6. Linear splines of tPSA and fPSA

[0106] In this model, only linear splines of tPSA and fPSA are included to reduce the number of variables and simplify the model.

[0107] L=β0+β1(Age)+β2(tPSA)+β3(fPSA)+β4(iPSA)+β5(hK2)+β6(sp1[tPSA])

[0108] +β7(sp2[tPSA])+β8(sp1[fPSA])+β9(sp2[fPSA])

[0109] 7. Cubic splines for all four types of analysis

[0110] This model includes cubic splines for each term. The example provided below describes a cubic spline with four nodes. However, it should be understood that cubic splines with any suitable number of nodes can be used alternatively, including, but not limited to, five, six, seven, and eight nodes. The spline can be determined using the following equation:

[0111]

[0112]

[0113] In this embodiment, nodes 1 and 4 are external nodes of the cubic spline, and nodes 2 and 3 are internal nodes of the cubic spline. In some embodiments, the internal nodes of tPSA are specified to be in the range of about 2 to about 5 and about 5 to about 8; the internal nodes of fPSA are specified to be in the range of about 0.25 to about 1 and about 1.0 to about 2.0; the internal nodes of iPSA are specified to be in the range of about 0.2 to about 0.5 and about 0.4 to about 0.8; and the internal nodes of hK2 are specified to be in the range of about 0.02 to about 0.04 and about 0.04 to about 0.08. For example, in one embodiment, the internal nodes of tPSA use values ​​of 3.89 and 5.54, the internal nodes of fPSA use values ​​of 0.81 and 1.19, the internal nodes of iPSA use values ​​of 0.3 and 0.51, and the internal nodes of kK2 use values ​​of 0.036 and 0.056.

[0114] In some embodiments, one or more internal nodes of the tPSA may independently fall within the range of about 3 to about 5, about 3 to about 6, about 2.5 to about 6, about 2.5 to about 6.5, about 5 to about 8, about 5.5 to about 8, about 5 to about 9, about 5 to about 10, about 1 to about 5, about 1 to about 4, and about 1 to about 3. Other ranges are also possible.

[0115] In some embodiments, one or more internal nodes of the fPSA may independently range from about 0.1 to about 1.0, from about 0.1 to about 1.2, from about 0.3 to about 0.8, from about 0.4 to about 0.9, from about 0.5 to about 1.2, from about 0.7 to about 1.4, from about 0.7 to about 0.9, from about 1.1 to about 1.6, from about 1.1 to about 1.2, and from about 1.1 to about 2. Other ranges are also possible.

[0116] In some embodiments, one or more internal nodes of the iPSA may independently range from about 0.05 to about 0.5, from about 0.1 to about 0.5, from about 0.2 to about 0.5, from about 0.1 to about 0.8, from about 0.2 to about 0.8, from about 0.4 to about 0.8, from about 0.4 to about 1.0, from about 0.3 to about 0.6, from about 0.5 to about 1.0, and from about 0.6 to about 0.8. Other ranges are also possible.

[0117] In some embodiments, one or more internal nodes of hK2 may independently range from about 0.01 to about 0.03, from about 0.01 to about 0.04, from about 0.01 to about 0.05, from about 0.02 to about 0.05, from about 0.02 to about 0.06, from about 0.03 to about 0.05, from about 0.4 to about 0.07, from about 0.04 to about 1.0, from about 0.5 to about 1.0, and from about 0.6 to about 1.0. Other ranges are also possible.

[0118] As discussed above, cubic splines incorporating any suitable number of internal nodes (e.g., three, four, five, or six internal nodes) can be used, and for illustrative purposes rather than limiting, only examples of cubic splines including two internal nodes are provided. In embodiments including more than two internal nodes, the nodes may be placed within one or more of the ranges described above, or within some other suitable range. For example, in some embodiments, nodes may be specified such that the length of the spline segments between each pair of adjacent nodes is substantially equal.

[0119] This model can be represented as:

[0120] L=β0+β1(Age)+β2(tPSA)+β3(fPSA)+β4(iPSA)+β5(hK2)+β6(sp1[tPSA])

[0121] +β7(sp2[tPSA])+β8(sp1[fPSA])+β9(sp2[fPSA])+β 10 (sp1[iPSA])+β 11 (sp2[iPSA])

[0122] +β 12 (sp1[hK2])+β 13 (sp2[hK2])

[0123] 8. Cubic splines of tPSA and fPSA

[0124] In this model, only cubic splines of tPSA and fPSA are included to reduce the number of variables and simplify the model.

[0125] In some embodiments, for cubic spline models of all four analyses, one or more of the ranges described above are used to specify the internal nodes of tPSA and fPSA. For example, the internal nodes of tPSA may be specified in the range between about 2 and about 5 and between about 5 and about 8, and the internal nodes of fPSA may be specified in the range between about 0.5 and about 1 and between about 1.0 and about 1.5. For example, in one embodiment, the internal nodes of tPSA use values ​​of 3.89 and 5.54 and the internal nodes of fPSA use values ​​of 0.81 and 1.19. However, it should be understood that other values ​​and / or ranges may be used alternatively. Additionally, it should be understood that, as discussed above regarding cubic spline models of all four analyses, in some embodiments, any number of nodes (e.g., not four nodes) may be used alternatively.

[0126] This model can be represented as:

[0127] L=β0+β1(Age)+β2(tPSA)+β3(fPSA)+β4(iPSA)+β5(hK2)+β6(sp1[tPSA])

[0128] +β7(sp2[tPSA])+β8(sp1[fPSA])+β9(sp2[fPSA])

[0129] 9. Age-stratified cubic splines for tPSA and fPSA

[0130] In this model, the dataset is divided into two parts to apply cubic splines, producing different coefficients (β) for patients whose age is less than or greater than / equal to a specific age (e.g., age 65). Therefore, in this model, both groups of patients use the same expression (with different coefficient values). Examples of the different coefficients that can be used in this model are provided in Table 1 below.

[0131] This model can be represented as:

[0132] If age <65:

[0133] L=β0+β1(Age)+β2(tPSA)+β3(fPSA)+β4(iPSA)+β5(hK2)+β6(sp1[tPSA])

[0134] +β7(sp2[tPSA])+β8(sp1[fPSA])+β9(sp2[fPSA])

[0135] If age ≥ 65:

[0136] L=β0+β1(Age)+β2(tPSA)+β3(fPSA)+β4(iPSA)+β5(hK2)+β6(sp1[tPSA])

[0137] +β7(sp2[tPSA])+β8(sp1[fPSA])+β9(sp2[fPSA])

[0138] The logistic regression models described above all include multiple input factors, including age and blood parameters such as total PSA (tPSA), free PSA (fPSA), intact PSA (iPSA), and human kallikrein 2 (hK2). In some cases, the blood parameter value is the concentration of the blood parameter in the patient sample. In some of the logistic regression models described above, linear or cubic splines are used to determine the nonlinear terms. It should be understood that higher-order splines can be used alternatively, as the techniques described herein are not limited in this respect.

[0139] For the logistic regression models described above, each term is multiplied by its corresponding coefficient value (β). This coefficient can be determined in any suitable manner. For example, the models can be applied to datasets including patient information, serological analysis results, and biopsy results. Using the techniques described herein, the best fit of each model to the information in the cancer prediction dataset can be determined, and the coefficients corresponding to the best fit can be used. Examples of the coefficients determined for each of the above models are shown in Table 1 below. For these models, age in years is input and the analysis results are measured in ng / mL.

[0140]

[0141] Table 1: Instance coefficients (β) for each of the nine linear regression models described above. The coefficients were determined based on the best fit of each model to a dataset including information from 1420 individuals.

[0142] It should be understood that the specific coefficients used in implementing the techniques described herein may differ from those listed in Table 1, as the values ​​in Table 1 are provided for illustrative purposes only. Furthermore, in some embodiments, different coefficients may be used for different patient groups and / or to determine the odds of different outcomes. For example, different coefficients may be used for patients in different age ranges, as described above regarding age-stratified cubic spline models. Different coefficients may also be used to determine the odds of a positive biopsy for different grades of cancer. For example, for one or more models, embodiments for determining the odds of a positive biopsy for high-grade cancer (e.g., Gleason score ≥ 7) may use different coefficients than embodiments for determining the odds of a positive biopsy for low-grade cancer. Additionally, different coefficients may be used at least in part based on whether one or more blood marker values ​​are determined based on serum or plasma.

[0143] In some embodiments, a first logistic regression model may be used when the value of one or more indicators exceeds a certain threshold, and a second logistic regression model may be used when the value is below the threshold. Figure 2 An example of a method based on a threshold-selective logistic regression model according to some embodiments of the present invention is illustrated. In action 210, the value of the blood indicator total PSA (tPSA) is received. Although Figure 2 The exemplary method uses tPSA as a blood indicator value to determine which logistic regression model to use, but it should be understood that any other blood indicator value, combination of blood indicator values, or any other suitable information may be used alternatively. Therefore, in some embodiments, at least one processor may be programmed to implement multiple models and select from multiple models at least in part based on one or more input values.

[0144] After receiving the tPSA value, the method proceeds to action 212, where a logistic regression model is selected at least in part based on the received tPSA value. For example, in one implementation, when the tPSA value is ≥15 ng / ml, preferably ≥20 ng / ml, and most preferably ≥25 ng / ml, the logistic regression model may be based solely on tPSA (e.g., the “simple model (tPSA alone)” model described above may be used). For this implementation, when the tPSA value is less than a certain threshold (e.g., less than 15 ng / ml), one or more other logistic regression models may be selected.

[0145] continue Figure 2 The method proceeds to step 214 after a model has been selected, where it is determined whether the selected model is a complete model (e.g., including all four kallikrein indicators) or a partial model (excluding all indicators in the kallikrein group). If the selected model is not a complete model, the method proceeds to step 216, where the cancer probability is determined solely based on the received tPSA value, as described above. If the selected model is a complete model, the method proceeds to step 218, where the cancer probability is determined using multiple blood indicators based on the selected model. Regardless of the specific model selected, after determining the cancer probability, the method proceeds to step 220, where the above steps are combined... Figure 1 The discussion focuses on outputting the probability of cancer.

[0146] In some embodiments of the invention, the events that yielded the stated probability proved prostate cancer at the site of a prostate biopsy performed on an asymptomatic male or a male with lower urinary tract symptoms.

[0147] In some embodiments of the invention, events that yielded the stated probability demonstrated high-grade prostate cancer (i.e., a Gleason score of 7 or higher) at the site of a prostate biopsy performed on asymptomatic men or men with lower urinary tract symptoms. Typically, the progression or status of prostate cancer is defined as (i) a Gleason score of 7 or higher, (ii) a Gleason grade of 4+3 or higher, or (iii) a Gleason score of 8 or higher.

[0148] In many preferred embodiments, the data for numerous men includes one or more biopsy data selected from a group that includes: the reason for the biopsy, the year of the biopsy, the number of biopsy cores, the number of positive cores, the percentage of positive cores in each core, and any possible combination thereof.

[0149] As discussed above, in many preferred embodiments, the blood index is included in a logistic regression model employing at most two nonlinear terms for at least one blood index. In some embodiments, the blood index is included in a logistic regression model employing at most three nonlinear terms for at least one blood index. In some embodiments, the blood index is included in a logistic regression model employing at most four nonlinear terms for at least one blood index. In some embodiments, the blood index is included in a logistic regression model employing at most five nonlinear terms for at least one blood index.

[0150] In some embodiments, when the expected event incidence rate in the target group of men representing the event probability to be obtained differs from the event incidence rates of the numerous men already used to obtain the logistic regression model, the logistic regression model can be recalibrated according to equation (II) by defining:

[0151]

[0152] Where p is the event occurrence rate in the data of the numerous men, and P is the expected event occurrence rate in the target group, as defined by equation (III):

[0153]

[0154] Where π is the original probability of the model, and is defined according to equation (IV):

[0155] Win rate 再校准 = Win rate × k (IV), and

[0156] The recalibration probability is obtained according to formula (V):

[0157]

[0158] Where, π 再校准 It is the probability of this event.

[0159] Some embodiments aim to provide a method and apparatus for predicting prostate gland volume using a linear regression model, wherein the method includes the action a) providing a linear regression model obtained by applying linear regression to data from a plurality of men, for each of the plurality of men, the data comprising: (i) data regarding prostate gland volume, and (ii) the preceding data relating to prostate gland volume, including age; and determined values ​​of blood indicators (including tPSA, fPSA, iPSA, and optionally hK2) based on blood samples from the men. The linear regression model may be generated using formula (VI):

[0160]

[0161] Where V is the volume of the prostate gland, β i It is variable x i The linear regression model is obtained by taking the coefficients for j variables (including age, tPSA, fPSA, iPSA, and optionally hK2). The method further includes: action b) providing the male's age in years; c) determining the blood indicators tPSA, fPSA, iPSA, and optionally hK2 based on a blood sample from the male; and d) using the age provided in step b) and the blood indicators determined in step c) to apply the linear regression model to obtain a predicted prostate volume for the male. In some embodiments, in the statistical model, the cancer risk is based on tPSA alone if tPSA ≥ 15 ng / ml, preferably tPSA ≥ 20 ng / ml, and most preferably tPSA ≥ 25 ng / ml.

[0162] It should be understood that embodiments of the present invention used to determine prostate gland volume may use any suitable logistic regression model, including but not limited to the model described above used to determine the probability of prostate cancer after a biopsy.

[0163] In some embodiments, the data (ii) for providing a logistic regression model or a linear regression model in step a) and the determined values ​​of the male's blood indicators include human kallikrein 2.

[0164] In many preferred embodiments of the method of the present invention for predicting prostate gland volume, a prostate gland volume is provided, as defined by transrectal ultrasound.

[0165] In many preferred embodiments of the method of the invention, data for each of the numerous men providing a logistic regression model or a linear regression model also includes the results of a digital rectal examination (DRE), and thus the DRE is performed on the men, and the probabilities are obtained using the results obtained when employing a logistic regression model or a linear regression model, respectively. In the case of the presence or absence of a second value for the estimated volume (i.e., small = 0, medium = 1, and large = 2), the results of the DRE are preferably represented as binary values, i.e., normal = 0, and nodule present = 1.

[0166] In some preferred embodiments of the method of the present invention, in order to obtain the model, the data of numerous men includes only the data of men with elevated tPSA levels (defined as median age or higher), and thus only the event probability or prostate volume prediction value of said men with elevated tPSA levels is obtained.

[0167] In a preferred embodiment of the method of the invention, the determination values ​​of blood indicators for each of the numerous men in the model, and thus those blood indicators determined for obtaining probabilities or predicted prostate gland volume values, are determined based on blood samples (preferably anticoagulant) of fresh or frozen serum or plasma. All samples preferably belong to the same category, i.e., serum or plasma, and are either fresh or frozen.

[0168] In some preferred embodiments of the method of the present invention, a logistic regression model or a linear regression model is provided using data from a large number of men aged 40 to 75; and thus, event probability or prostate volume prediction values ​​are obtained for men aged 40 to 75.

[0169] In some preferred embodiments of the method of the present invention, a logistic regression model or a linear regression model is provided, which uses data from a large number of men whose blood tPSA is ≥ one-third, one-quarter, one-fifth, or one-tenth of their maximum age, and thus obtains the event probability or prostate volume prediction values ​​for men whose blood tPSA is ≥ one-third, one-quarter, one-fifth, or one-tenth of their maximum age, respectively. For example, for a 60-year-old man, the corresponding total PSA values ​​could be: 1.5 ng / ml for ≥ one-third of his maximum age; 1.9 ng / ml for ≥ one-quarter of his maximum age; 2.1 ng / ml for ≥ one-fifth of his maximum age; and 3 ng / ml for ≥ one-tenth of his maximum age.

[0170] Exemplary computer systems

[0171] Figure 3Exemplary embodiments of a computer system 300 capable of implementing some or all of the technologies and / or user interactions described herein are illustrated. The computer system 300 may include one or more processors 310 and one or more computer-readable permanent storage media (e.g., memory 320 and one or more non-volatile storage media 330). The one or more processors 310 may control the writing of data to and reading of data from memory 320 and non-volatile storage devices 330 in any suitable manner, as the aspects of the invention described herein are not limited in this respect.

[0172] To perform any of the functions described herein, one or more processors 310 may execute one or more instructions (e.g., program modules) stored in one or more computer-readable storage media (e.g., memory 320), which may serve as a non-transitory computer-readable storage medium storing the instructions executed by processor 310. Typically, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. Embodiments may also be implemented in a distributed computing environment, where tasks are performed by remote processing devices linked via a communication network. In a distributed computing environment, program modules may reside in local and remote computer storage media, including memory storage devices.

[0173] Computer 300 can operate in a network environment using a logical connection to one or more remote computers. The one or more remote computers may include personal computers, servers, routers, network PCs, peer devices, or other public network nodes, and typically include many or all of the components described above with respect to computer 300. The logical connection between computer 300 and the one or more remote computers may include, but is not limited to, local area networks (LANs) and wide area networks (WANs), but may also include other networks. These networks may be based on any suitable technology and operate according to any suitable protocol, and may include wireless networks, wired networks, or fiber optic networks. These network environments are common in offices, corporate WANs, intranets, and the Internet.

[0174] When used in a LAN network environment, computer 300 can be connected to the LAN via a network interface or adapter. When used in a WAN network environment, computer 300 typically includes a modem or other components that establish communication over a WAN (e.g., the Internet). In a network environment, program modules or portions thereof may be stored in remote storage devices.

[0175] The various input data described herein for assessing prostate cancer risk and / or determining prostate gland volume may be received by computer 300 via a network (e.g., LAN, WAN, or other network) from one or more remote computers or devices storing data associated with the input data. One or more remote computers / devices may analyze the remotely stored data and then send the analysis results as input data to computer 300. Alternatively, the remotely stored data may be sent to computer 300 as is, without any remote analysis. Additionally, the input data may be directly received by a user of computer 300 using any of a plurality of input interfaces (e.g., input interface 340) that may be incorporated as a component of computer 300.

[0176] The various output data described herein (including output data on prostate cancer risk probability and / or prostate gland volume) may be provided visually to an output device (e.g., a monitor) directly connected to computer 300, or the output data may be provided to a remotely located output device connected to computer 300 via one or more wired or wireless networks, as embodiments of the invention are not limited in this respect. In addition to visual presentation, the output data described herein may be provided additionally or alternatively. For example, the computer 300 or remote computer to which the output data is provided may include one or more output interfaces, including but not limited to speakers and vibration output interfaces, for providing output indication.

[0177] It should be understood that although computer 300 is in Figure 3 While exemplified as a single device, in some embodiments, computer 300 may include multiple devices communicatively coupled to perform some or all of the functions described herein, and computer 300 is merely one exemplary embodiment of a computer usable according to embodiments of the invention. For example, in some embodiments, computer 300 may be integrated into... Figure 5 The system shown and / or electronically communicating with the system.

[0178] As described above, in some embodiments, computer 300 may be included in a networked environment, wherein information regarding one or more blood indicators used to determine the probability of prostate cancer and / or prostate gland volume is sent from an external source to computer 300 for analysis using one or more techniques described herein. Figure 4 An exemplary network environment 400 according to some embodiments of the present invention is illustrated. In network environment 400, computer 300 is connected to detector 420 via network 410. As discussed above, network 410 can be any suitable type of wired or wireless network, and may include one or more local area networks (LANs) or wide area networks (WANs), such as the Internet.

[0179] Detector 420 can be configured to determine the values ​​of one or more blood indicators used to determine the probability of prostate cancer and / or prostate gland volume according to one or more techniques described herein. While detector 420 in Figure 4 The detector 420 is illustrated as a single detector, but it should be understood that detector 420 can be implemented with multiple detectors, each configured to determine one or more blood indicator values ​​used according to one or more techniques described herein. Other examples of detectors and detection systems are provided in more detail below (e.g., Figure 12 ).

[0180] In some embodiments, information corresponding to the values ​​of blood indicators determined by detector 420 may be stored, and these values ​​may then be sent to computer 300. In these embodiments, the information corresponding to these values ​​may be stored locally in local storage 420 communicatively coupled to detector 420 and / or in central storage 440 connected to a network. Therefore, when computer 300 receives values ​​corresponding to blood indicators according to one or more of the techniques described herein, it should be understood that at least some values ​​may be received directly from detector 420 or from one or more storage devices (e.g., local storage 430, central storage 440) where these values ​​are stored, as the embodiments are not limited to where these values ​​are received from.

[0181] Other systems and components

[0182] As described herein, in some embodiments, the system may include a processor or computer programmed to evaluate a logistic regression model in electronic communication with the analyzer for determining the odds of prostate cancer-related events (e.g., prostate cancer risk and / or prostate gland volume). The analyzer may be adapted and configured to determine one or more blood indicator features for input into the logistic regression model. In some embodiments, the analyzer is a microfluidic sample analyzer; for example, the analyzer may be adapted and configured to determine samples processed in a microfluidic device / cassette. However, it should be understood that other types of analyzers (e.g., analyzers for microwell ELISA-type analysis) may also be used, and the systems described herein are not limited in this respect.

[0183] In one set of embodiments, examples of such a system include a microfluidic sample analyzer comprising a housing, an opening in the housing configured to receive a cartridge having at least one microfluidic channel, wherein the housing includes components configured to connect with mating components on the cartridge to detect the cartridge within the housing. The analyzer may also include a pressure control system located within the housing, configured to pressurize at least one microfluidic channel in the cartridge, thereby allowing a sample to pass through the at least one microfluidic channel. An optical system located within the housing includes at least one light source and at least one detector spaced apart from the light source, wherein the light source is configured to allow light to pass through the cartridge when the cartridge is inserted into the sample analyzer, and wherein the detector is located opposite the light source to detect the amount of light passing through the cartridge. The system may also include a user interface associated with the housing for at least inputting the age and / or other information of a person input into a linear regression model.

[0184] In some embodiments, the processor (or is adapted) to communicate electronically with a microfluidic sample analyzer. In some cases, the processor is located within the analyzer's housing. However, in other embodiments, the processor is not included within the analyzer's housing but is accessible by electronic components as described herein. The processor is programmed to evaluate a logistic regression model, at least in part, based on information received from at least one detector, to determine the probability of a prostate cancer event in a person. The evaluation of the logistic regression model involves scaling each of a plurality of variables by different coefficient values ​​to produce scaled variables and summing the values ​​of the scaled variables to produce the probability of a prostate cancer-related event in a person. The plurality of variables includes age and at least two variables included in the information received from the detector and selected from the group consisting of fPSA, iPSA, and tPSA.

[0185] Methods for determining the probability of prostate cancer-related events in a person may include, for example, providing a microfluidic sample analyzer. The microfluidic sample analyzer may include a housing, an opening in the housing configured to receive a cartridge having at least one microfluidic channel, wherein the housing includes components configured to connect with mating components on the cartridge to detect the cartridge within the housing. The analyzer may also include a pressure control system located within the housing, the pressure control system being configured to pressurize at least one microfluidic channel in the cartridge, thereby allowing a sample to pass through at least one microfluidic channel. An optical system located within the housing includes at least one light source and at least one detector spaced apart from the light source, wherein the light source is configured to allow light to pass through the cartridge when the cartridge is inserted into the sample analyzer, and wherein the detector is located opposite the light source to detect the amount of light passing through the cartridge. The analyzer may also include a user interface associated with the housing for inputting at least the person's age. The method may involve using the microfluidic sample analyzer to determine information on multiple blood parameters, wherein the information on the multiple blood parameters includes fPSA values, iPSA values, tPSA values, and optionally hK2 values. The method may also involve using at least one processor to evaluate a logistic regression model at least in part based on the information to determine the probability of a person’s prostate cancer-related events, wherein evaluating the logistic regression model includes scaling each of a plurality of variables by different coefficient values ​​to produce scaled variables and summing the values ​​of the scaled variables to produce the probability of a person’s prostate cancer-related events, wherein the plurality of variables includes age and at least two variables included in the information received from the detector and selected from the group including fPSA, iPSA and tPSA.

[0186] In one set of embodiments, another example of the system includes a device (e.g., a microfluidic cartridge) comprising a first analytical region containing a first binding ligand and a second analytical region containing a second binding ligand. The first binding ligand is adapted to bind to at least one of fPSA, iPSA, and tPSA, and the second binding ligand is adapted to bind to at least another of fPSA, iPSA, and tPSA. In some embodiments, the device includes a third analytical region comprising a third binding ligand adapted to bind to a third of fPSA, iPSA, and tPSA. Optionally, the device may include a fourth analytical region comprising a fourth binding ligand adapted to bind to hK2. The system includes a detector associated with the first and second analytical regions, and a processor programmed to evaluate a logistic regression model based at least in part on information received from the detector to determine the probability of prostate cancer-related events in a person. Evaluating the logistic regression model involves scaling each of a plurality of variables with different coefficient values ​​to produce a scaled variable and summing the values ​​of the scaled variable to produce the probability of a person’s prostate cancer-related events, wherein the plurality of variables includes age and at least two variables included in the information received from the detector and selected from a group including fPSA, iPSA and tPSA.

[0187] Methods for determining the probability of prostate cancer-related events in such systems may include, for example, introducing a sample into a device (e.g., a microfluidic cartridge) comprising a first analytical region containing a first binding ligand and a second analytical region containing a second binding ligand, wherein the first binding ligand is adapted to bind to at least one of fPSA, iPSA, and tPSA, and wherein the second binding ligand is adapted to bind to at least another of fPSA, iPSA, and tPSA. In some embodiments, the device includes a third analytical region comprising a third binding ligand adapted to bind to a third of fPSA, iPSA, and tPSA. Optionally, the device includes a fourth analytical region comprising a fourth binding ligand adapted to bind to hK2. The method may involve binding any one of fPSA, iPSA, and / or tPSA from the sample to at least the first and / or second binding ligands in the first and second analytical regions, and characterizing the fPSA, iPSA, and / or tPSA using one or more detectors associated with the first and second analytical regions. This method involves inputting features of fPSA, iPSA, and / or tPSA into a processor programmed to evaluate a logistic regression model, at least in part, based on information received from at least one detector, to determine the probability of a person experiencing prostate cancer-related events. The evaluation of the logistic regression model includes scaling each of a plurality of variables by different coefficient values ​​to produce scaled variables and summing the values ​​of the scaled variables to produce the probability of a person experiencing prostate cancer-related events. The plurality of variables includes age and at least two variables included in the information received from the detector and selected from the group comprising fPSA, iPSA, and tPSA. Therefore, the probability of a prostate cancer-related event can be determined.

[0188] In some embodiments, a device is provided for determining blood parameters (e.g., fPSA, iPSA, tPSA, and / or hK2). In some cases, the device may allow, for example, simultaneous determination of blood parameters on a single cartridge. The device may include a microfluidic system comprising a first microfluidic channel including at least one inlet and one outlet, a first reagent stored in the first microfluidic channel, and a seal covering the inlet of the first microfluidic channel and a seal covering the outlet of the first microfluidic channel for storing the first reagent in the first microfluidic channel. The device may also include a second microfluidic channel including at least one inlet and one outlet, a first analytical region, a second analytical region, and a third analytical region. Each analytical region may include one of an anti-iPSA-specific capture antibody, an anti-fPSA-specific capture antibody, and an anti-tPSA-specific capture antibody (and optionally an hK2-specific capture antibody). One or more of the first, second, and third analytical regions may be in fluid communication with the second microfluidic channel. The device also includes a fluid connector connectable to a microfluidic system, wherein the fluid connector includes a fluid path with an inlet and an outlet, wherein, upon connection, the fluid path inlet connects to the outlet of a first microfluidic channel to enable fluid communication between the fluid path and the first microfluidic channel, and the fluid path outlet connects to the inlet of a second microfluidic channel to enable fluid communication between the fluid path and the second microfluidic channel. The first and second microfluidic channels are not fluidly connected to each other when not connected by the fluid connector. The device may optionally include a metal colloid source conjugated with an antibody bound to anti-PSA.

[0189] In some embodiments involving the device described herein, at least two (or at least three) of the first, second, and third analysis regions are in fluid communication with a second microfluidic channel. In some cases, the first, second, and third analysis regions (and optionally a fourth analysis region) are all in fluid communication with the second microfluidic channel. In some cases, the first analysis region is in fluid communication with the second microfluidic channel, and the second analysis region is in fluid communication with the third microfluidic channel. As described herein, the second and third analysis regions (and the second and third microfluidic channels) may be formed, for example, on the same substrate layer or on different substrate layers. Additionally, in some embodiments, the third analysis region is in fluid communication with the fourth microfluidic channel. As described herein, the third and fourth analysis regions (and the third and fourth microfluidic channels) may be formed, for example, on the same substrate layer or on different substrate layers. In some cases, each of the first, second, and third analysis regions (and optionally a fourth analysis region) is formed in a different substrate layer. In other embodiments, the fourth analytical region (which may include, for example, an anti-hK2 specific capture antibody) is formed in a different substrate layer than the substrate layer that includes at least one of the first, second, and third analytical regions. In some of these embodiments, the first, second, and third analytical regions are formed in the same substrate layer.

[0190] Regardless of whether the analytical regions are formed in different substrate layers or in the same substrate layer, in some embodiments, for example, reagents may be stored and sealed in a first analytical region, a second analytical region, and / or a third analytical region (and optionally a fourth analytical region) before the device is used. Reagents may include, for example, anti-iPSA specific capture antibodies, anti-fPSA specific capture antibodies, and anti-tPSA specific capture antibodies (and optionally hK2 specific capture antibodies). After the device is used (e.g., after the fluid connector is connected to the microfluidic system), a first microfluidic channel may be positioned in fluid communication with one or more of the first, second, and third analytical regions (and optionally the fourth analytical region). For example, the fluid connector may be connected to one or more inlets of the second, third, and / or fourth microfluidic channels after connection to the microfluidic system. Examples of device configurations are described in more detail below.

[0191] In some of the devices described herein, analysis involves using a detection antibody that recognizes one or more of iPSA, fPSA, tPSA, and hK2. For example, the detection antibody may recognize both PSA and hK2, and a blocking agent may subsequently be used to interfere with PSA, so that only hK2 is detected. For example, in one particular embodiment, the analysis region may include an anti-hK2 capture antibody (which may also capture, for example, 5-10% tPSA and may be stored in the analysis region prior to use as described herein), and a blocking antibody that blocks tPSA. An anti-hK2 detection antibody (which may also detect tPSA) may be used to detect the amount of hK2 bound. Different analysis regions may include, for example, an anti-tPSA capture antibody that captures both fPSA and tPSA (which may be stored in the analysis region prior to use as described herein). Detection may be performed using two different detection antibodies, such as an anti-tPSA detection antibody with a fluorescent tag of one wavelength and an anti-fPSA detection antibody with a fluorescent tag of a different wavelength. Different analysis regions may include, for example, an anti-fPSA capture antibody and, if applicable, an anti-iPSA capture antibody. Two different detection antibodies can be used for detection, such as an anti-fPSA detection antibody with a fluorescent tag of one wavelength and an anti-iPSA detection antibody with a fluorescent tag of a different wavelength.

[0192] However, in other embodiments, specific capture antibodies can be used for species detection. As described herein, each specific capture antibody may be located in a different analytical region. Advantageously, the use of specific capture antibodies and / or the location of capture antibodies in different analytical regions allows for the detection of individual species using the same detection antibody. In some such embodiments, the same wavelength can be used to determine individual species. This allows for detection using simplified detectors and / or optical components. For example, in some embodiments, as described in more detail below, detection involves the ability to determine the accumulation of opaque material in different analytical regions at a specific wavelength.

[0193] For example, in one set of embodiments, anti-iPSA specific capture antibodies, anti-fPSA specific capture antibodies, and anti-tPSA specific capture antibodies (and optionally hK2 specific capture antibodies) may be optionally included in different analytical regions along with negative and positive controls, as described herein. Each of iPSA, fPSA, tPSA, and / or hK2 can be detected using detection antibodies (e.g., gold-labeled antibodies against PSA and hK2). However, in other embodiments, a mixture of gold-labeled antibodies, such as gold-indexed anti-hK2 antibodies, gold-indexed anti-PSA antibodies, and / or gold-indexed anti-iPSA antibodies, can be used for detection. In this system, the individual species can be identified using the same wavelength, and this allows for detection using simplified detectors and / or optical components.

[0194] Examples of specific systems, devices, and analyzers that can be used in combination with the embodiments provided herein are described below.

[0195] Figure 5 Block diagram 510 illustrates a microfluidic system according to a set of embodiments and various components that may be included. The microfluidic system may include, for example: a cartridge 520 operatively associated with one or more components, such as a fluid flow source 540, such as a pump (e.g., for introducing one or more fluids into the cartridge and / or for controlling the fluid flow rate); optional fluid flow sources 540, such as a pump or vacuum device configured to apply either positive pressure or vacuum (e.g., for moving / removing one or more fluids from / from the cartridge and / or for controlling the fluid flow rate); a valve system 528 (e.g., for actuating one or more valves); a detection system 534 (e.g., for detecting one or more fluids and / or processes); and / or a temperature control system 541 (e.g., for heating and / or cooling one or more zones of the cartridge). These components may be external to or internal to the microfluidic device and may optionally include one or more processors for controlling the components or component system. In some embodiments, one or more of these components and / or processors are associated with a sample analyzer 547 configured to process and / or analyze samples contained in a cartridge. The processor may optionally be programmed to evaluate a linear regression model as described herein.

[0196] Generally speaking, as used herein, a component that is “operably associated” with one or more other components indicates that these components are directly connected to each other, in direct physical contact with each other when not connected or attached to each other, or are not directly connected to each other or in direct contact with each other but are mechanically, electrically (including through electromagnetic signal transmission across space), or fluidly interconnected (e.g., via a channel, such as a pipe) in order to cause or allow the components to be associated in order to perform their intended functions.

[0197] Figure 5 The components illustrated herein, as well as other optional components (such as those described herein), may be associated with the control system 550 in an operable manner. In some embodiments, the control system may be used to control the fluid and / or perform quality control by using feedback from one or more events occurring in the microfluidic system. For example, the control system may be configured to receive input signals from one or more components, calculate and / or control various parameters, compare one or more signals or signal patterns with pre-programmed signals in the control system, and / or send signals to one or more components to modulate fluid flow and / or control the operation of the microfluidic system. As described in more detail below, the control system may also optionally be associated with other components, such as user interface 554, identification system 556, external communication unit 558 (e.g., USB), and / or other components.

[0198] The channels and / or components in cartridge (e.g., microfluidic device) 520 for performing the desired analysis may have any suitable configuration. In one set of embodiments, for example, as described in more detail below, cartridge 520 contains stored reagents for performing chemical and / or biological reactions (e.g., immunoassays). The cartridge may include, for example, an optional reagent inlet 562 in fluid communication with an optional reagent storage area 564. The storage area may include, for example, one or more channels and / or reservoirs, which in some embodiments may be partially or completely filled with fluids (e.g., liquids and gases, including immiscible reagents, such as reagent solutions and washes, optionally separated by immiscible fluids, as described in more detail herein). The cartridge may also include an optional sample or reagent loading area 566, such as a fluid connector for connecting the reagent storage area 564 to an optional analysis area 568. An analysis area, which may include one or more areas for detecting sample components (e.g., an analysis zone), may be in fluid communication with an optional waste area 570 and coupled to an outlet 572. In some cases, these and other device features may be formed on or within different components or layers of the cartridge, as described in more detail herein. Therefore, it should be understood that a cartridge may comprise a single component or multiple components attached during use, such as a combination of the object described herein and an attached fluid connector. In one set of embodiments, fluid may flow in the direction of the arrows shown in the accompanying drawings. Further descriptions and examples of these and other components are provided herein.

[0199] In some embodiments, segments 571 and 577 of the cartridge are not in fluid communication with each other before a sample is introduced into the cartridge. In some cases, segments 571 and 577 are not in fluid communication with each other before the first use of the cartridge, wherein the segments are made in fluid communication with each other upon first use. However, in other embodiments, segments 571 and 577 are in fluid communication with each other before the first use and / or before a sample is introduced into the cartridge. Other configurations of the cartridge are also possible.

[0200] like Figure 5As illustrated in the exemplary embodiments, one or more fluid flow sources 540 (such as pumps and / or vacuum devices or other pressure control systems), valve systems 528, detection systems 534, temperature control systems 541, and / or other components may be operatively associated with one or more of the following areas: reagent inlet 562, reagent storage area 564, sample or reagent loading area 566, reaction area 568, waste area 570, outlet 572, and / or other areas of cartridge 520. Detection of a process or event in one or more areas of the cartridge may generate a signal or signal pattern that can be transmitted to the control system 550. Based on the signal received by the control system, this feedback may be used, for example, by controlling one or more of the pumps, vacuum devices, valve systems, detection systems, temperature control systems, and / or other components, to manipulate the fluid within and / or between each of these areas of the microfluidic device.

[0201] Turning Figure 6 An embodiment of a microfluidic sample analyzer 600 is illustrated. For example... Figure 6 As shown in the exemplary embodiment, the analyzer includes a housing 601 configured to cover or hold components of the analyzer, which are discussed in more detail below. An opening 620 in the housing is configured to receive a cartridge 520. As described in more detail below, the analyzer 600 may also include a user interface 650 located within the housing, configured to allow a user to input information into the sample analyzer. In this particular embodiment, the user interface 650 includes a touchscreen, but as discussed below, the user interface may be configured in different ways.

[0202] In some embodiments, the analyzer may include: a fluid flow source (e.g., a vacuum system) configured to pressurize a cartridge; an identification reader configured to read information associated with the cartridge; and a mechanical subsystem including components configured to connect with the cartridge to detect the cartridge within a housing. As described above, an opening in the housing is configured to receive a cartridge. The opening 620 may be configured as an elongated slot. The opening may be configured in this way to receive a substantially card-shaped cartridge. It should be understood that in other embodiments, the opening may be shaped and configured differently, as the invention is not limited thereto.

[0203] As described above, the microfluidic sample analyzer 600 can be configured to accommodate various types of cartridges 520 (e.g., microfluidic devices). Figures 7 to 11F Various exemplary embodiments of the cartridge 520 used with the analyzer 600 are illustrated. As shown, the cartridge may be substantially card-shaped (i.e., similar to a card key) and have a substantially rigid plate-like structure.

[0204] The cartridge 520 may be configured to include a fluid connector 720 that snaps into one end of the cartridge. In some embodiments, the fluid connector may be used to introduce one or more fluids (e.g., samples or reagents) into the cartridge.

[0205] In one set of embodiments, a fluid connector is used to fluidly connect two (or more) channels of the cartridge during first use, channels that were not connected prior to the first use. For example, before the first use of the cartridge, the cartridge may include two non-fluidally connected channels. In some cases, non-connected channels may be advantageous, such as for storing different reagents in each channel. For example, a first channel may be used to store a dry reagent, while a second channel may be used to store a humid reagent. Having physically separated channels can enhance the long-term stability of the reagents stored in each channel, for example, preventing the reagent stored in a dry form from being moistened by moisture generated by the reagent stored in a humid form. Upon first use, the channels may be connected via the fluid connector to fluidly connect the channels of the cartridge. For example, the fluid connector may be inserted into a seal covering the cartridge inlet and / or outlet to allow the fluid connector to be inserted into the cartridge.

[0206] As used herein, “before first use of the cartridge” means the time prior to the intended user’s first use of the cartridge after it has been commercially available. First use may include any steps required for the user to manipulate the device. For example, first use may involve one or more of the following steps: inserting a sealed inlet to introduce reagents into the cartridge; connecting two or more channels to enable fluid communication between the channels; preparing the device prior to sample analysis (e.g., loading reagents into the device); loading a sample onto the device; preparing a sample in a region of the device; reacting with the sample; detecting the sample; etc. In this context, first use does not include manufacturing or other preparative or quality control steps performed by the cartridge manufacturer. Those skilled in the art readily understand the meaning of first use in this context and can readily determine whether the cartridge of the present invention has undergone or not undergone first use. In one set of embodiments, the cartridge of the present invention may be discarded after first use (e.g., after analysis is completed), and this is particularly evident when using these devices for the first time, as these devices are generally not reusable after first use (e.g., for a second analysis).

[0207] like Figure 8As illustrated in the exemplary embodiments, the fluid connector 720 may include a substantially U-shaped channel 722 or a channel having any other suitable shape, which may contain fluid and / or reagents (e.g., fluid samples and / or one or more detection antibodies) prior to connection to a cartridge. The channel 722 may be positioned between two housing assemblies forming the connector 720. In some embodiments, the fluid connector may be used to collect patient samples prior to connection to the cartridge. For example, a finger blood sample may be obtained using a lancet or other suitable instrument, which can then be collected by the fluid connector 720 and loaded into the channel 722 via capillary action. In other embodiments, the fluid connector 720 may be configured to pierce a patient's finger to collect a sample in the channel 722. In some embodiments, the fluid connector 720 does not contain a sample (or reagent) prior to connection to the cartridge, but allows fluid communication between only two or more channels of the cartridge after connection. In one embodiment, a capillary is used to form the U-shaped channel. The fluid connector may also include other channel configurations, and in some embodiments, may include more than one channel that may or may not be fluidly connected to each other.

[0208] Figures 9-11F Various exemplary embodiments of the cartridge 520 are illustrated in more detail. For example... Figure 9 As exemplarily shown in the exploded assembly diagram, cartridge 520 may include cartridge body 704, which includes at least one channel 706 configured to receive a sample or reagent and allow flow of the sample or reagent. Cartridge body 704 may also include latch 708 located at one end and interlocking with fluid connector alignment assembly 702.

[0209] The cartridge 520 may also include a top cover 710 and a bottom cover 712, which may be made of, for example, a transparent material. In some embodiments, the covers may be in the form of a biocompatible adhesive and may be made of, for example, a polymer (e.g., polyethylene (PE), cyclic olefin copolymer (COC), polyvinyl chloride (PVC)) or an inorganic material. In some cases, one or more covers are in the form of an adhesive film (e.g., tape). In some applications, the material and size of the covers are chosen such that the covers are substantially impermeable to water vapor. In other embodiments, the covers may be non-adhesive but may be thermally bonded to the microfluidic matrix by direct application of heat, laser energy, or ultrasonic waves. Any inlet and / or outlet of the cartridge's passage may be sealed (e.g., by placing an adhesive on the inlet and / or outlet) using one or more covers. In some cases, the covers substantially seal one or more stored reagents within the cartridge.

[0210] As shown, the cartridge body 704 may include one or more ports 714 coupled to a channel 706 in the cartridge body 704. These ports 714 may be configured to align with a generally U-shaped channel 722 in the fluid connector 720 when the fluid connector 720 is coupled to the cartridge 520 to fluidly connect the channel 706 in the cartridge body 704 to the channel 722 in the fluid connector 720. In some embodiments, the generally U-shaped channel 722 may also be fluidly connected to a channel 707, thereby coupling channels 706 and 707. As shown, a cover 716 may be disposed on the ports 714 and the cover 716 may be configured to be segmented or otherwise opened (e.g., via connector 720 or via other components) to fluidly connect the two channels 706 and 722. Additionally, a cover 718 may be disposed to cover a port 719 (e.g., a vacuum port) in the cartridge body 704. As further detailed below, port 719 can be configured to fluidly connect fluid flow source 540 to channel 706, thereby allowing the sample to pass through the cartridge. The cover 718 on port 719 can be configured to be punctured or otherwise opened to fluidly connect channel 706 to fluid flow source 540.

[0211] The cartridge body 704 may optionally include a liquid containment area, such as a waste area, comprising absorbent material 717 (e.g., a waste absorbent pad). In some embodiments, the liquid containment area includes a zone that traps one or more liquids flowing within the cartridge while allowing gas or other fluids in the cartridge to pass through. In some embodiments, this can be achieved by placing one or more absorbent materials in the liquid containment area to absorb the liquid. This configuration can be used to remove air bubbles from the fluid flow and / or to separate hydrophobic and hydrophilic liquids. In some embodiments, the liquid containment area prevents liquid from passing through the zone. In some such cases, the liquid containment area can act as a waste area by substantially trapping all the liquid in the cartridge, thereby preventing liquid from flowing out of the cartridge (e.g., while allowing gas to escape from the cartridge outlet). For example, the waste area can be used to store the sample and / or reagent after it has passed through channel 706 during sample analysis. These and other configurations are useful when the cartridge is used as a diagnostic tool because the liquid containment area prevents the user from being exposed to potentially harmful fluids in the cartridge.

[0212] Figure 10 The schematic diagram of the cartridge 520 illustrated in the figure shows one embodiment, wherein the cartridge 520 includes a first channel 706 and a second channel 707 spaced apart from the first channel 706. In one embodiment, the maximum cross-sectional dimensions of the channels 706, 707 are in the range of about 50 micrometers to about 500 micrometers, but other channel sizes and configurations may be used, as described in more detail below.

[0213] The first channel 706 may include one or more analytical regions 709 for analyzing a sample. For example, in one exemplary embodiment, channel 706 includes four analytical regions 709 (e.g., connected in series or parallel) utilized during sample analysis. As described herein, each analytical region may be suitable for detecting one or more of iPSA, fPSA, tPSA, and / or hK2.

[0214] In some embodiments, one or more analysis zones are in the form of meandering zones (e.g., zones involving meandering channels). The meandering zone may, for example, consist of at least 0.25 mm... 2 At least 0.5mm 2 At least 0.75mm 2 Or at least 1.0mm 2 The area is defined by the meandering region, wherein at least 25%, 50%, or 75% of the area contains the optical detection path. A detector capable of measuring a single signal passing through one or more adjacent segments of the meandering region may be placed adjacent to the meandering region. In some cases, channel 706 is fluidly connected to at least two meandering regions connected in series.

[0215] As described herein, prior to the first use of the cartridge, the first channel 706 and / or the second channel 707 may be used to store one or more reagents (e.g., capture antibodies for iPSA, fPSA, tPSA, and / or hK2) for processing and analyzing samples. In some embodiments, a dry reagent is stored in one channel or segment of the cartridge, while a wet reagent is stored in a second channel or segment of the cartridge. Alternatively, two spaced segments or channels of the cartridge may contain both dry and / or wet reagents. Reagents may be stored and / or placed in the form of liquids, gases, gels, multiple particles, or membranes. Reagents may be placed in any suitable portion of the cartridge, including but not limited to in channels, in reservoirs, on surfaces, and in or on membranes, which may optionally be part of a reagent storage area. Reagents may be associated with the cartridge (or components of the cartridge) in any suitable manner. For example, reagents may be cross-bonded (e.g., covalently or ionicly), absorbed, or adsorbed (physically adsorbed) onto a surface within the cartridge. In one particular embodiment, all or part of the channels (e.g., the fluid path of a fluid connector or the channels of a cartridge) are coated with an anticoagulant (e.g., heparin). In some cases, the liquid is contained within the channels or reservoir of the cartridge before first use and / or before a sample is introduced into the cartridge.

[0216] In some embodiments, the stored reagents may include fluid plugs placed in a linear order, such that during use, as the fluid flows to the analytical zone, the reagents are delivered in a predetermined sequence. For example, a cartridge designed to perform an analysis may sequentially include rinse fluid, labeled antibody fluid, rinse fluid, and amplification fluid, all stored in the cartridge. When storing the fluids, these fluids may be kept separate by a substantially immiscible separating fluid (e.g., a gas, such as air), such that fluid reagents that react normally with each other upon contact can be stored in a common channel.

[0217] Reagents can be stored in cartridges for varying durations. For example, reagents can be stored for more than 1 hour, 6 hours, 12 hours, 1 day, 1 week, 1 month, 3 months, 6 months, 1 year, or 2 years. Optionally, to extend the storage time, the cartridges can be handled in a suitable manner. For example, cartridges containing the stored reagents can be vacuum-sealed, stored in the dark, and / or stored at low temperatures (e.g., below 0°C). The length of storage time depends on one or more factors, such as the specific reagent used, the form of the stored reagent (e.g., wet or dry), the size and materials used to form the substrate and capping, the method of bonding the substrate and capping, and how the cartridge is handled or stored as a whole. Storing reagents (e.g., liquid or dry reagents) in channels may involve sealing the inlet and outlet of the channel before first use or during device packaging.

[0218] like Figure 10 and Figures 11A-11F As illustrated in the exemplary embodiments, channels 706 and 707 may not be in fluid communication with each other until the fluid connector 720 is coupled to the cartridge 520. In other words, in some embodiments, the two channels are not in fluid communication with each other before first use and / or before the sample is introduced into the cartridge. Specifically, as illustrated, the substantially U-shaped channel 722 of the connector 720 allows the first channel 706 to be fluidly connected to the second channel 707, such that reagents in the second channel 707 can pass through the U-shaped channel 522 and selectively enter the analytical zone 709 in the first channel 706. In other embodiments, the two channels 706 and 707 are in fluid communication with each other before first use and / or before the sample is introduced into the cartridge, but the fluid connector further connects the two channels upon first use (e.g., forming a dead loop system).

[0219] In some embodiments, the cartridges described herein may include another microfluidic channel, but these cartridges are not limited to microfluidic systems and may be associated with other types of fluid systems. A cartridge, device, apparatus, or system as a microfluidic may include, for example, at least one fluid channel having a maximum cross-sectional dimension of less than 1 mm and a length-to-maximum cross-sectional dimension ratio of at least 3:1.

[0220] The cross-sectional dimensions (e.g., diameter) of the channels are measured perpendicular to the direction of fluid flow. Most fluid channels in the cassette components described herein have a maximum cross-sectional dimension of less than 2 mm, and in some cases, less than 1 mm. In one set of embodiments, all fluid channels in the cassette are microfluidic channels or have a maximum cross-sectional dimension of at most 2 mm or 1 mm. In another set of embodiments, the maximum cross-sectional dimensions of the channels are less than 500 micrometers, less than 200 micrometers, less than 100 micrometers, less than 50 micrometers, or less than 25 micrometers. In some cases, the channel size can be selected such that fluid can flow freely through an object or substrate. The channel size can also be selected, for example, to allow the fluid in the channel to have a specific volumetric flow rate or linear flow rate. Of course, the number and shape of the channels can be varied by any suitable method known to those skilled in the art. In some cases, more than one channel or capillary can be used.

[0221] The channel may include features on or inside an object (e.g., a cartridge) that guide fluid flow in at least a portion. The channel may have any suitable cross-sectional shape (circular, elliptical, triangular, irregular, square, or rectangular, etc.) and may be covered or uncovered. In a fully covered embodiment, at least a portion of the channel may have a completely enclosed cross-section, or the entire channel may be completely enclosed along its entire length except for its inlet and outlet. The channel may also have an aspect ratio (the ratio of length to average cross-sectional size) of at least 2:1, more typically at least 3:1, 5:1, or 10:1 or greater.

[0222] The cartridges described herein may include channels or channel segments located on one or both sides of the cartridge (or on the cartridge substrate layer). In some cases, the channels are formed in the surface of the cartridge. The channel segments may be connected by a central channel through the cartridge. In some embodiments, the channel segments are used to store reagents in the device before first use by the end user. The specific geometry of the channel segments and their location within the cartridge allow for extended storage of fluid reagents, even unmixed, during routine operation of the cartridge (e.g., during cartridge transport), and even when the cartridge is subjected to physical shock or vibration.

[0223] In some embodiments, the cartridge includes an optical element fabricated on one side of the cartridge opposite a series of fluid channels. The term "optical element" is used to refer to a feature formed or disposed on or within an object or cartridge that, relative to light incident on the object or cartridge in its absence, is provided and serves to alter the direction (e.g., via refraction or reflection), focus, polarization, and / or other properties of incident electromagnetic radiation. For example, an optical component may include lenses (e.g., concave or convex lenses), mirrors, gratings, grooves, or other features formed or disposed within or on the cartridge. However, a cartridge that does not inherently possess unique features does not constitute an optical element, even if it alters one or more properties of the incident light when interacting with the cartridge. An optical element can guide incident light through the cartridge such that most of the light is dispersed away from specific areas of the cartridge, such as the intermediate portions between the fluid channels. By reducing the amount of light incident on these intermediate portions, the amount of noise in the detection signal can be reduced when using certain optical detection systems. In some embodiments, the optical element includes a triangular groove formed on or within the surface of the cartridge. The draft angle of the triangular groove can be selected so that incident light perpendicular to the cartridge surface changes direction at an angle depending on the refractive index of the external medium (e.g., air) and the cartridge material. In some embodiments, one or more optical elements are disposed between adjacent sections of the meandering zone of the analysis region.

[0224] The cartridge or a portion thereof may be made of any material suitable for forming channels or other components. Non-limiting examples of materials include polymers (e.g., polyethylene, polystyrene, polymethyl methacrylate, polycarbonate, poly(dimethylsiloxane), PVC, PTFE, PET, and cyclic olefin copolymers), glass, quartz, and silicon. The material forming the cartridge and any associated components (e.g., cover) may be rigid or flexible. Those skilled in the art can readily select suitable materials based on factors such as material rigidity, the material's inertness to fluids passing through it (e.g., non-degradation by the fluid), the material's stability at the operating temperature of a particular device, the material's transparency / opaqueness (e.g., in the ultraviolet and visible light regions), and / or the method used to manufacture the features in the material. For example, for injection molding or other extrusion objects, the materials used may include thermoplastic materials (e.g., polypropylene, polycarbonate, acrylonitrile-butadiene-styrene, Nylon 6), elastomers (e.g., polyisoprene, isobutylene-isoprene, nitrile, chloroprene rubber, ethylene-propylene, hypoallergenic, polysiloxane), thermosetting materials (e.g., epoxides, unsaturated polyesters, phenolic resins) or combinations thereof. As described in more detail below, for example based on those factors mentioned above and herein, cartridges comprising two or more components or layers may be formed of different materials such that the components are suited to the primary function of each component.

[0225] In some embodiments, the material and dimensions (e.g., thickness) of the cartridge and / or cover are selected to make it substantially impermeable to water vapor. For example, a cartridge designed to store one or more fluids may include a cover containing materials known to provide a high vapor barrier (e.g., metal foil, certain polymers, certain ceramics, and combinations thereof) before its first use. Examples of materials with low water vapor permeability are provided below. In other cases, the material is selected at least in part based on the shape and / or configuration of the cartridge. For example, some materials are suitable for forming planar devices, while others are better suited for forming devices with curved or irregular shapes.

[0226] In some cases, cartridges contain combinations of two or more materials, such as those listed above. For example, the cartridge channel may be formed using polystyrene or other polymers (e.g., by injection molding), and biocompatible tape may be used to seal the channel. Biocompatible tape or flexible materials may include materials known to improve vapor barrier properties (e.g., metal foil, polymers, or other materials known to have high vapor barrier properties), and access to the inlet and outlet may optionally be permitted by piercing or peeling the tape. Various methods may be used to seal microfluidic channels or portions thereof, or to bond multiple layers of a device; these methods include, but are not limited to, the use of adhesives, tapes, glues, bonding, lamination, or mechanical methods (e.g., clamping, locking mechanisms, etc.).

[0227] In some cases, a cartridge comprises a combination of two or more separate components (e.g., layers or cartridges) mounted together. Independent channel networks (e.g., ...) may be included on or within the different components of the cartridge. Figure 5 Sections 571 and 577), these channel networks may optionally include reagents stored therein before first use. The separating components may be mounted together or otherwise associated with each other by any suitable method (e.g., by the methods described herein), for example, to form a single (composite) cartridge. In some embodiments, two or more channel networks are situated in different components or layers of the cartridge and are not fluidly connected before first use, but are fluidly connected upon first use, for example, by using a fluid connector. In other embodiments, two or more channel networks are fluidly connected before first use.

[0228] Advantageously, each visible component or layer of the different components or layers forming the composite cartridge is individually customized to its design function. For example, in one set of embodiments, one component of the composite cartridge may be customized to store a wetting reagent. In some of these embodiments, the component may be formed using a material with relatively low vapor permeability. Additionally or alternatively, for example, depending on the amount of fluid stored, the cross-sectional dimension of the cartridge storage area may be larger than the channels or areas of other components not used for storing liquid. The material used to form the cartridge may be compatible with manufacturing techniques suitable for forming larger cross-sectional dimensions. In contrast, in some embodiments, a second component that may be customized to detect an analyte may include a channel portion with a smaller cross-sectional dimension. A smaller cross-sectional dimension would be useful for a given volume of fluid, for example, in some embodiments, allowing the fluid flowing in the channel to have a longer contact time with the analyte bonded to the channel surface. Additionally or alternatively, the surface roughness of the channel portion of the second component is lower than (e.g., increasing the signal-to-noise ratio during detection) the channel portion of the other component. In some embodiments, the smaller cross-sectional dimension or lower surface roughness of the channel portion of the second component may require specific manufacturing techniques or tools different from those used to form the different components of the cartridge. Furthermore, in some specific embodiments, the material used for the second component can be adequately characterized for protein attachment and detection. Therefore, it is advantageous to form different channel portions for different purposes on different components of the cartridge, which can then be joined together and subsequently used by the intended user. Other advantages, component features, and examples are provided below.

[0229] Figures 11B-11E An apparatus is shown that may include multiple components or layers 520B and 520C combined to form a single cartridge. As shown in these exemplary embodiments, component 520B may include a first surface 521A and a second surface 521B. Component 520C may include a first surface 522A and a second surface 522B. In some embodiments, the device components or parts described herein (e.g., channels or other entities) may be formed at, above, or inside, at, above, or inside, and / or through the component at the first surface of the component, at the second surface of the component, and / or through the component. For example, as... Figure 11CAs illustrated herein, component 520C may include a channel 706 having an inlet and an outlet, and may be formed of a first material. Channel 706 may have any suitable configuration as described herein and may include, for example, one or more reagent storage areas, analytical areas, liquid containment areas, mixing areas, etc. In some embodiments, channel 706 is not formed throughout the entire thickness of component 520B. That is, the channel may be formed on one side of the component or inside. Channel 706 may optionally be closed by a cover as described herein (e.g., tape (not shown), another component or layer of the cartridge, or other suitable component). In other embodiments, channel 706 is formed throughout the entire thickness of component 520B and a cover is required on both sides of the cartridge to close the channel. As described herein, different layers or components may include different analytical areas for determining species within a sample. For example, capture antibodies for iPSA, fPSA, tPSA, and / or hK2 may be placed in different analytical areas, optionally in different components or layers of the cartridge (e.g., the components or layers shown).

[0230] Component 520B may include a channel 707 having an inlet and an outlet and may be formed of a second material, which may be the same as or different from the first material. Channel 707 may also have any suitable configuration as described herein and may or may not be formed throughout the entire thickness of component 520C. Channel 707 may be closed by one or more covers. In some cases, the cover is not a component including one or more fluid channels, such as component 520C. For example, the cover may be biocompatible tape or other surfaces placed between components 520B and 520C. In other embodiments, channel 707 may be substantially closed by component 520C. That is, when components 520B and 520C are placed directly adjacent to each other, surface 522A of component 520C may form part of channel 707.

[0231] like Figure 11D and Figure 11E As illustrated, components 520B and 520C can be substantially flat and positioned vertically relative to each other. However, two or more components forming a cartridge can generally be positioned relative to each other in any suitable configuration. In some cases, components are placed adjacent to each other (e.g., side-by-side, vertically relative to each other). The first component may completely overlap or only a portion of the components may overlap each other. For example, as... Figure 11D and Figure 11E As illustrated, component 520C may extend further than component 520B, such that a portion of component 520C is not overlapped or covered by component 520B. This configuration may be advantageous in some cases where component 520C is substantially transparent and light needs to pass through a portion of the component (e.g., the reaction zone, analysis zone, or detection zone), and where component 520B is opaque or has less transparency than component 520C.

[0232] Furthermore, the first and second components may include any suitable shape and / or configuration. For example, in some embodiments, the first component includes features complementary to those of the second component to form a non-fluid connection between the first and second components. For instance, complementary features may facilitate alignment of the first and second components during assembly.

[0233] In some embodiments, the first and second components may be integrally connected to each other. As used herein, when referring to two or more objects, the term "integrated" means that the objects are not separated from each other during normal use, for example, they cannot be separated manually; separation requires at least the use of a tool, and / or by causing damage to at least one component, such as by breaking, peeling, or separating components held together by adhesives or tools. Integrated components may be irreversibly attached to each other during normal use. For example, components 520B and 520C may be integrally connected by the use of adhesives or other bonding methods. In other embodiments, two or more components of the cartridge may be reversibly attached to each other.

[0234] As described herein, in some embodiments, at least the first and second components forming the composite cartridge may be formed of different materials. The system may be designed such that the first component includes a first material that contributes to or enhances one or more functions of the first component. For example, if the first component is designed to store liquid reagents (e.g., stored in the component's channels) before the user's first use (e.g., for at least one day, one week, one month, or one year), a first material with relatively low vapor permeability may be selected to reduce the evaporation of the stored liquid over time. However, it should be understood that in some embodiments, the same material may be used for multiple components (e.g., layers) of the cartridge. For example, the first and second components of the cartridge may be formed of a material with low water vapor permeability.

[0235] In some embodiments, the first and second components of the cartridge have different optical transparency. For example, the first component may be substantially opaque, while the second component may be substantially transparent. The substantially transparent component is suitable for optical detection of the sample or analyte contained within it.

[0236] In one set of embodiments, the material used to form the cartridge components (e.g., a first or second component) has an optical transmittance greater than 90% for light with wavelengths between 400 nm and 800 nm (e.g., light in the visible region). The optical transmittance of a material with a thickness of, for example, about 2 mm (or, in other embodiments, about 1 mm or about 0.1 mm) can be measured. In some cases, the optical transmittance for light with wavelengths between 400 nm and 800 nm is greater than 80%, greater than 85%, greater than 88%, greater than 92%, greater than 94%, or greater than 96%. Another component of the device can be formed from a material having an optical transmittance for light with wavelengths between 400 nm and 800 nm of less than 96%, less than 94%, less than 92%, less than 90%, less than 85%, less than 80%, less than 50%, less than 30%, or less than 10%.

[0237] As described herein, in some embodiments, the channels of the first component of the cartridge are not in fluid communication with the channels of the second component of the cartridge before the user's first use. For example, even after the two components have engaged, such as Figure 11D As illustrated, channels 706 and 707 are not in fluid communication with each other. However, the cartridge may also include other parts or components, such as the fluid connector alignment element 702. Figure 11E These other parts or components may be attached to the first component 520B and / or the second component 520C or other portions of the cartridge. As described herein, a fluid connector alignment element may be configured to receive and mate with the fluid connector 720, which may fluidly communicate between the channel 706 of the first component and the channel 707 of the second component, respectively. For example, the fluid connector may include a fluid path (including a fluid path inlet and a fluid path outlet), wherein the fluid path inlet may fluidly communicate with the outlet of channel 706 and the fluid path outlet may fluidly connect with the inlet of channel 707 (or vice versa). The fluid path of the fluid connector may have any suitable length suitable for connecting the channels (e.g., at least 1 cm, at least 2 cm, at least 3 cm, at least 5 cm). The fluid connector, together with the cartridge, may be part of a kit and packaged such that the fluid connector does not fluidly connect channels 706 and 707.

[0238] The fluid connector can have any suitable configuration relative to the cartridge or cartridge components. For example... Figure 11E As illustrated, after the fluid connector is connected to the cartridge, it can be positioned on the side of a component (e.g., component 520B) opposite to another component (e.g., component 520C). In other embodiments, the fluid connector can be located between the two components of the cartridge. For example, the fluid connector can be a component or layer located between (e.g., sandwiched between) the two components of the cartridge. Other configurations are also possible.

[0239] While most of the description herein pertains to a cartridge having one or more components or layers including a channel network, in other embodiments, the cartridge may include more than two, three, or four of these components or layers. For example, as Figure 11F As illustrated, the cartridge may include components 520B, 520C, 520D, and 520E, each component including at least one channel or channel network. In some cases, the channels of one or more components (e.g., two, three, or all components) may not be fluidly connected prior to first use, but may be fluidly connected upon first use, for example, by using a fluid connector. In other embodiments, the channels of one or more components (e.g., two, three, or all components) are fluidly connected prior to first use.

[0240] As described herein, each component or layer of the cartridge may be designed to have a specific function that differs from the function of another component of the cartridge. In other embodiments, two or more components may have the same function. For example, as Figure 11F As illustrated in the exemplary embodiments, each of components 520C, 520D, and 520E may have one or more analytical zones 709 connected in series. After the fluid connector 722 is connected to the composite cartridge, a portion of a sample (or multiple samples) may be introduced into the channel network of each of components 520C, 520D, and 520E for multiple analyses. For example, each analytical zone may include one or more binding ligands (e.g., capture antibodies for iPSA, fPSA, tPSA, and / or hK2) for detecting one or more of iPSA, fPSA, tPSA, and / or hK2. As described herein, in some embodiments, using specific capture antibodies and / or separating capture antibodies in different analytical zones allows for the detection of each species using the same detection antibody. In some such embodiments, the same wavelength may be used to determine each species. This allows for detection using simplified detectors and / or optical components. For example, in some embodiments, detection involves the ability to determine the accumulation of opaque materials in different analytical zones at a specific wavelength.

[0241] In some embodiments, at least the first and second components of the cartridge may be part of a device or assembly for determining specific chemical or biological conditions. The device or assembly may include, for example, a first component made of a first material containing a first channel, the first channel including an inlet, an outlet, and at least one portion having a cross-sectional dimension greater than 200 micrometers between the first inlet and the outlet. The device or assembly may also include a second component made of a second material containing a second channel, the second channel including an inlet, an outlet, and at least one portion having a cross-sectional dimension less than 200 micrometers between the second inlet and the outlet. In some cases, the packaging device or assembly is configured such that the first and second components are connected to each other. For example, the first and second components may be integrally connected to each other. In other embodiments, the first and second components are reversibly attached to each other. The device or assembly may also include a fluid connector for fluidly connecting the first and second channels, the fluid connector including a fluid path including a fluid path inlet and a fluid path outlet, wherein the fluid path inlet is fluidly connected to the outlet of the first channel and the fluid path outlet is fluidly connected to the inlet of the second channel. In some embodiments, the packaging device or assembly is configured such that the fluid connector does not fluidly connect the first and second channels within the packaging. When the intended user uses the device for the first time, a fluid connector can be used to fluidly connect the first and second channels to each other.

[0242] The cartridges described herein may have any volume suitable for performing analyses (e.g., chemical and / or biological reactions or other processes). The entire volume of the cartridge includes, for example, any reagent storage area, analysis area, liquid containment area, waste area, and any fluid connectors and associated fluid channels. In some embodiments, small amounts of reagents and samples are used and the entire volume of the fluid device is, for example, less than 10 mL, 5 mL, 1 mL, 500 μL, 250 μL, 100 μL, 50 μL, 25 μL, 10 μL, 5 μL, or 1 μL.

[0243] The cartridges described herein can be portable, and in some embodiments, are handheld. The length and / or width of the cartridge can be, for example, less than or equal to 20 cm, 15 cm, 10 cm, 8 cm, 6 cm, or 5 cm. The thickness of the cartridge can be, for example, less than or equal to 5 cm, 3 cm, 2 cm, 1 cm, 8 mm, 5 mm, 3 mm, 2 mm, or 1 mm. Advantageously, the portable device is suitable for use in on-site care configurations.

[0244] It should be understood that the cartridges and their corresponding components described herein are exemplary and other configurations and / or types of cartridges and components can be used with the systems and methods described herein.

[0245] The methods and systems described herein can relate to a variety of different types of analysis and can be used to identify a wide variety of different samples. In some cases, the analysis involves chemical and / or biological reactions. In some embodiments, the chemical and / or biological reactions involve binding. Different types of binding can occur in the cartridges described herein. Binding can involve interactions between corresponding molecular pairs (e.g., binding ligands) that exhibit mutual affinity or binding capacity, typically specific or non-specific binding or interactions, including biochemical, physiological, and / or drug interactions. Biological binding is defined as a class of interactions between molecular pairs (e.g., binding ligands) that include proteins, nucleic acids, glycoproteins, carbohydrates, hormones, etc. Specific examples include antibody / antigen, antibody fragment / antigen, antibody / hapten, antibody fragment / hapten, enzyme / receptor, enzyme / inhibitor, enzyme / cofactor, binding protein / receptor, carrier protein / receptor, lectin / carbohydrate, receptor / hormone, receptor / effect factor, complementary nucleic acid pairs, protein / nucleic acid inhibitor / inducer, ligand / cell surface receptor, virus / ligand, etc. Binding can also occur between proteins or other components and cells. Furthermore, the devices described herein can be used for other fluid analyses (which may or may not involve binding and / or reactions), such as detecting components, concentrations, etc.

[0246] In some cases, heterogeneous reactions (or analyses) can occur in the cartridge; for example, binding ligands can associate with channel surfaces, and complementary binding ligands can be present in the liquid phase. Other solid-phase analyses can also be performed, involving affinity reactions between proteins or other biomolecules (e.g., DNA, RNA, carbohydrates) or molecules that are not naturally occurring. Non-limiting examples of typical reactions that can be performed in the cartridge include chemical reactions, enzyme-catalyzed reactions, immune-based reactions (e.g., antigen-antibody), and cell-based reactions.

[0247] Typical sample fluids include physiological fluids such as human or animal whole blood, serum, plasma, semen, tears, urine, sweat, saliva, cerebrospinal fluid, and vaginal secretions; and in vitro or environmental fluids used for research, such as aqueous liquids suspected of being contaminated by analytes.

[0248] In some embodiments, one or more reagents (e.g., binding ligands of the analyte to be identified) used to determine a sample analyte may be stored in the channel or chamber of the cartridge prior to first use for specific testing or analysis. In the case of analyzing an antigen, the corresponding antibody or aptamer may be a binding ligand that associates with the surface of a microfluidic channel. If the antibody is the analyte, a suitable antigen or aptamer may be a binding ligand that associates with the surface. When determining disease symptoms, it is preferable to place the antigen on the surface and to allow antibodies to be generated in the subject. It should be understood that when antibodies are mentioned herein, antibody fragments may be used in combination with or in place of antibodies.

[0249] In some embodiments, the cartridge is adapted and configured to perform analysis involving the deposition of an opaque material on a microfluidic channel region, exposing the region to light, and determining the transmittance of light through the opaque material. The opaque material may include substances that interfere with the transmittance of light at one or more wavelengths. The opaque material not only refracts light but also reduces the amount of light transmitted through it by, for example, absorbing or reflecting light. Different opaque materials or different amounts of opaque material may result in the transmittance of light irradiating the opaque material being less than, for example, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 1%. Examples of opaque materials include molecular layers of metals (e.g., elemental metals), ceramic layers, polymer layers, and layers of opaque substances (e.g., dyes). In some cases, the opaque material may be a metal that can be electrodeposited. These metals may include, for example, silver, copper, nickel, cobalt, palladium, and platinum.

[0250] The opaque material formed in the channel may comprise a series of discontinuous, independent particles forming an opaque layer together, but in one embodiment, it is a continuous material exhibiting a generally flat shape. The opaque material may have dimensions (e.g., width or length) greater than or equal to 1 micrometer, greater than or equal to 5 micrometers, greater than 10 micrometers, greater than or equal to 25 micrometers, or greater than or equal to 50 micrometers. In some cases, the opaque material spans the width of the channel (e.g., the analysis zone) containing the opaque material. The opaque layer may have a thickness of, for example, less than or equal to 10 micrometers, less than or equal to 5 micrometers, less than or equal to 1 micrometer, less than or equal to 100 nanometers, or less than or equal to 10 nanometers. Even at these smaller thicknesses, detectable changes in transmittance can still be obtained. Compared to techniques that do not form an opaque layer, the opaque layer can increase analytical sensitivity.

[0251] In one set of embodiments, the cartridge described herein is used for immunoassays (e.g., for determining tPSA, iPSA, fPSA, and / or hK2) and optionally employs silver-enhanced signal amplification. In this immunoassay, after a sample containing the blood marker to be detected is passed to the analytical region, binding can occur between the blood marker and the corresponding binding ligand. One or more reagents, optionally stored in the device channel prior to use, can subsequently flow through this binding-pairing complex. One of the stored reagents may include a solution containing one or more metal colloids bound to the antigen to be detected. For example, gold-labeled antibodies—anti-PSA and anti-hK2 antibodies—can be used to detect each of iPSA, fPSA, tPSA, and / or hK2. In another example, a mixture of gold-labeled antibodies (e.g., gold-labeled anti-hK2 antibody, gold-labeled anti-PSA antibody, and / or gold-labeled anti-iPSA antibody) can be used for detection. These reagents may, for example, be stored in the cartridge prior to use. The metal colloids provide a catalytic surface for depositing an opaque material layer, such as a metal (e.g., silver), on the surface of one or more analytical regions. The metal layer can be formed using a two-component system: a metal precursor (e.g., a solution of a silver salt) and a reducing agent (e.g., hydroquinone, chlorohydroquinone, pyrogallol, metol, 4-aminophenol, and phenidone), which may optionally be stored in different channels prior to use.

[0252] When a positive or negative pressure differential is applied to the system, the silver salt and reducing solution can be mixed (e.g., at the channel intersection) and then flow through the analytical zone. Therefore, if antibody-antigen binding occurs in the analytical zone, the flow of the metal precursor solution through this zone can lead to the formation of an opaque layer (e.g., a silver layer) due to the presence of catalytic metal colloids that associate with the antibody-antigen complex. The opaque layer may include a substance that interferes with the transmittance of one or more wavelengths of light. The opaque layer formed in the channel can be detected optically, for example, by measuring the decrease in transmittance through a portion of the analytical zone (e.g., a spiral channel region) compared to a portion that does not contain the antibody or antigen. Alternatively, as the membrane forms in the analytical zone, a signal can be obtained by measuring the change in transmittance over time. The opaque layer can increase analytical sensitivity compared to techniques that do not form an opaque layer. In addition, various amplified chemical reactions that generate optical signals (e.g., absorbance, fluorescence, glow or flash chemiluminescence, electrochemiluminescence), electrical signals (e.g., resistance or conductivity of a metallic structure formed by an electrical-free process), or magnetic signals (e.g., magnetic beads) can be used to detect signals in detectors.

[0253] Various types of fluids can be used with the cartridges described herein. As described herein, fluids can be introduced into the cartridge upon first use and / or stored in the cartridge prior to first use. Fluids include liquids, such as solvents, solutions, and suspensions. Fluids also include gases and gas mixtures. When a cartridge contains multiple fluids, these fluids can be separated by another fluid that is preferably substantially immiscible with each of the first two fluids. For example, if the channel contains two different aqueous solutions, the separating plug of the third fluid can be substantially immiscible with both aqueous solutions. When it is desired to maintain the separation of aqueous solutions, substantially immiscible fluids that can be used as separators may include gases (e.g., air or nitrogen) or hydrophobic fluids that are substantially immiscible with aqueous fluids. Fluids can also be selected based on their reactivity with adjacent fluids. For example, inert gases such as nitrogen can be used in some embodiments and may help preserve and / or stabilize any adjacent fluids. An example of a substantially immiscible liquid used for separating aqueous solutions is perfluoronaphthalene. Separating fluids can also be selected based on other factors, including any effect the separating fluid may have on the surface tension of adjacent fluid plugs. Preferably, the surface tension within any fluid plug is maximized to promote the fluid plug maintaining a single, continuous unit form under varying environmental conditions (e.g., vibration, shock, and temperature variations). The isolating fluid can also be inert to the analytical region from which the fluid will be supplied. For example, if the analytical region includes biobinding ligands, an isolating fluid such as air or nitrogen may have little or no effect on the binding ligands. Using a gas (e.g., air) as the isolating fluid can also provide expansion space within the channels of the fluid device so that the liquid contained within the device will expand or contract due to changes such as temperature (including freezing) or pressure variations.

[0254] The microfluidic sample analyzer may include a fluid flow source (e.g., a pressure control system) that is fluidly connected to channels 706, 707, 722 to pressurize the channels to allow samples and / or other reagents to pass through them. Specifically, the fluid flow source may be configured to allow samples and / or reagents to initially move from the substantially U-shaped channel 722 into the first channel 706. The fluid flow source may also be used to allow reagents in the second channel 707 to pass through the substantially U-shaped channel 722 and into the first channel 706. After the samples and reagents have passed through the analysis zone 709 and been analyzed, the fluid flow source 540 may be configured to move fluid into the absorbent material 717 of the cartridge. In one embodiment, the fluid flow source is a vacuum system. However, it should be understood that other fluid flow sources, such as valves, pumps, and / or other components, may be used.

[0255] As described herein, in some embodiments, a vacuum source can be used to drive fluid flow. The vacuum source may include a pump, such as an electromagnetically operated diaphragm pump. In other embodiments, fluid flow can be driven / controlled by using other types of pumps or fluid flow sources. For example, in one embodiment, a syringe pump can be used to create a vacuum by pulling the syringe plunger outward. In other embodiments, a positive pressure is applied to one or more inlets of the cartridge to provide a fluid flow source.

[0256] In some embodiments, fluid flow occurs when a substantially constant non-zero pressure drop (i.e., ΔP) is applied between the cartridge's inlet and outlet. In one set of embodiments, the entire analysis is performed when a substantially constant non-zero pressure drop (i.e., ΔP) is applied between the cartridge's inlet and outlet. A substantially constant non-zero pressure drop can be achieved, for example, by applying a positive pressure at the inlet or a reduced pressure (e.g., a vacuum) at the outlet. In some cases, when no fluid flow occurs, a substantially constant non-zero pressure drop is achieved primarily through capillary forces and / or by not using an actuating valve (e.g., not altering the cross-sectional area of ​​the cartridge's fluid path channel). In some embodiments, when the entire analysis is performed substantially within the cartridge, a substantially constant non-zero pressure drop can exist, for example, between the analysis zone inlet (which may be connected to a fluid connector) and the downstream outlet of the analysis zone (e.g., the downstream outlet of the liquid-containing confinement zone).

[0257] In one embodiment, the vacuum source is configured to pressurize the channel to approximately -60 kPa (approximately 2 / 3 of an atmosphere). In another embodiment, the vacuum source is configured to pressurize the channel to approximately -30 kPa. In some embodiments, the vacuum source is configured to pressurize the channel to, for example, between -100 kPa and -70 kPa, between -70 kPa and -50 kPa, between -50 kPa and -20 kPa, or between -20 kPa and -1 kPa.

[0258] After the cartridge is placed inside the analyzer, a fluid flow source can be coupled to the cartridge to ensure a liquid-tight connection. As described above, the cartridge may include ports configured to couple channels 706 and 707 (if fluid is connected to 706) to the fluid flow source. In one embodiment, a seal or O-ring is placed around the port and a linear solenoid is positioned above the O-ring to press the O-ring and seal the cartridge body. For example, as... Figure 11A As shown in the exemplary embodiment, in addition to port 719, there may be two exhaust ports 715 and a mixing port 713. The interfaces between each port and the manifold may be independent (e.g., there may be no fluid connection within the manifold).

[0259] In one embodiment, when the fluid flow source is activated, channels 706 and 707 in the cartridge can be pressurized (e.g., to about -30 kPa) to drive the fluid (fluid sample and reagent) within the channels toward the outlet. In one embodiment, which includes an vent port 715 and a mixing port 713, an vent valve connected to port 713 via a manifold can first be opened, causing all reagents downstream of mixing port 713 to move toward the outlet, but not reagents upstream of mixing port 713. After the vent valve is closed, the reagents upstream of mixing port 713 move toward the mixing port and subsequently to the outlet. For example, fluid can be continuously stored in the channel upstream of the mixing port, and after the vent valve disposed along the channel is closed, the fluid can continue to flow toward the channel outlet. In some cases, fluid can be stored in individual phase-connecting channels, and after the vent valve is closed, the fluids will flow together toward the junction point. This set of embodiments can be used, for example, to allow for controlled mixing of fluids during fluid confluence. The timing and volume of fluid transfer can be controlled, for example, by the timing of vent valve actuation.

[0260] Advantageously, the vent valve can be operated without shrinking the cross-sectional area of ​​the microfluidic channel operated by the vent valve, whereas some valves using existing technology can shrink. This mode of operation effectively prevents valve leakage. Furthermore, because the vent valve can be used, some systems and methods described herein do not require the use of certain internal valves that may be problematic due to, for example, their high cost, manufacturing complexity, fragility, limited compatibility with mixed gas and liquid systems, and / or unreliability in microfluidic systems.

[0261] It should be understood that while an exhaust valve is described, other types of valve mechanisms can be used with the systems and methods described herein. Non-limiting examples of valve mechanisms that can be operably associated with a valve include diaphragm valves, ball valves, gate valves, butterfly valves, needle valves, pinch valves, lift valves, or pinch valves. The valve mechanism can be actuated by any suitable component (including solenoids, motors), manually, electronically, or hydraulically / pneumatically.

[0262] As mentioned above, all liquids (samples and reagents) in the cartridge can be moved into a liquid containment area including absorbent material 717. In one embodiment, the absorbent material absorbs only liquids, allowing gas to exit the cartridge via an outlet.

[0263] Various deterministic techniques (e.g., measurement, quantification, detection, and identification) can be used, for example, to analyze sample components or other components or conditions associated with the microfluidic system or cartridge described herein. Deterministic techniques may include optical-based techniques such as light transmission, light absorption, light scattering, light reflection, and visual techniques. Deterministic techniques may also include luminescence techniques such as photoluminescence (e.g., fluorescence), chemiluminescence, bioluminescence, and / or electrochemiluminescence. In other embodiments, deterministic techniques may measure conductivity or resistance. Therefore, the analyzer may be configured to include these and other suitable detection systems.

[0264] Different optical detection techniques offer a wide range of options for determining the outcome of a reaction (e.g., analysis). In some embodiments, the measurement of transmittance or absorbance means that light can be detected at the same wavelength as that emitted from the light source. While the light source can be a narrowband source emitting a single wavelength, it can also be a broadband source emitting multiple wavelengths because various opaque materials can effectively block a wide range of wavelengths. In some embodiments, the system can operate with minimal optical equipment (e.g., a simplified optical detector). For example, the determining device may not contain a photomultiplier, a wavelength selector such as a grating, prism, or filter, a device for guiding or focusing light such as a collimator, or a magnifying optical system (e.g., a lens). Eliminating or reducing these features makes the device less expensive and more robust.

[0265] Figure 12 An exemplary optical system 800, which may be housed within an analyzer housing, is illustrated. As illustrated illustratively in this embodiment, the optical system includes at least one first light source 882 and a detector 884 spaced apart from the first light source. The first light source 882 may be configured to allow light to pass through a first analysis zone of the cartridge when it is inserted into the analyzer. The first detector 884 may be positioned opposite the first light source 882 to detect the amount of light passing through the first analysis zone of the cartridge 520. It should be understood that the number of light sources and detectors may vary in other embodiments, as the invention is not limited thereto. As described above, the cartridge 520 may include a plurality of analysis zones 709, and the cartridge 520 may be housed within the analyzer such that each analysis zone is aligned with a light source and a corresponding detector. In some embodiments, the light source includes an optical aperture that facilitates directing light from the light source to a specific area within the cartridge's analysis zone.

[0266] In one embodiment, the light source is a light-emitting diode (LED) or a laser diode. For example, an InGaAlP red semiconductor laser diode emitting at 654 nm can be used. Other light sources may also be used. The light source may be placed within a housing or casing. The housing or casing may include a narrow aperture or thin-walled tube that facilitates the calibration of the light. The light source may be positioned above the location where the cartridge is inserted into the analyzer, such that the light source illuminates downwards onto the top surface of the cartridge. Other suitable configurations of the light source relative to the cartridge are also possible.

[0267] It should be understood that the wavelength of the light source can vary, as the present invention is not limited thereto. For example, in one embodiment, the wavelength of the light source is approximately 670 nm, while in another embodiment, the wavelength of the light source is approximately 650 nm. It should be understood that in one embodiment, the wavelengths of the light sources may be different, such that the different analytical zones of the cartridge receive different wavelengths of light. However, in other embodiments, the wavelengths of the light sources may be the same, such that the different analytical zones of the cartridge receive the same wavelength of light. Combinations of light sources with the same wavelength and different wavelengths are also possible.

[0268] As mentioned, detector 884 may be spaced apart from and located below light source 882 to detect the amount of light passing through the cartridge. In one embodiment, one or more detectors are photodetectors (e.g., photodiodes). In some embodiments, the photodetector may be any suitable device capable of detecting the transmittance of light emitted by the light source. One type of photodetector is an optical integrated circuit (IC) including a photodiode with peak sensitivity at 700 nm, an amplifier, and a voltage regulator. The detector may be placed within a nest or housing that may include a narrow aperture or thin-walled tube to ensure that detector 884 measures light only from the center of analysis region 709. If the light source is pulse-modulated, the photodetector may include a filter to remove the influence of light that does not have the selected frequency. When multiple signals and adjacent signals are detected simultaneously, the light source used for each analysis region (e.g., detection region) may be modulated at a frequency significantly different from that of its adjacent light sources. In this configuration, each detector may be configured (e.g., using software) to select its attribute light source to avoid interference light forming adjacent light pairs.

[0269] The applicant has recognized that the amount of light transmitted through the cartridge's analytical zone can be used not only to determine information related to the sample but also to determine information related to a specific process occurring within the cartridge's fluid system (e.g., reagent mixing, flow rate, etc.). In some cases, measurements of the light passing through the zone can be used as feedback to control fluid flow in the system. In certain embodiments, quality control or anomalies in cartridge operation can be identified. For example, feedback from the analytical zone to the control system can be used to determine an anomaly that has occurred in the microfluidic system, and the control system can send signals to one or more components to shut down the system, either fully or partially. Therefore, the quality of processes occurring in microfluidic systems can be controlled using the systems and methods described herein.

[0270] It should be recognized that a clear liquid (e.g., water) allows a significant amount of light from the light source 882 to pass through the analysis zone 709 and reach the detector 884. Air within the analysis zone 709 results in less light transmission compared to the presence of a clear liquid, as more light is scattered within the channel. When a blood sample is in the analysis zone 709, significantly less light passes through to reach the detector 884 due to light scattering by blood cells and also due to light absorption. In one embodiment, silver associates with sample components bound to the surfaces within the analysis zone, and as silver accumulates within the analysis zone, less and less light is transmitted through the analysis zone 709.

[0271] It is recognized that measuring the amount of light detected by each detector 884 allows the user to determine what reagent is present in a specific analytical region 709 at a specific time point. It is also recognized that by measuring the amount of light detected using each detector 884, the amount of silver deposited in each analytical region 709 can be measured. This amount corresponds to the amount of analyte captured during the reaction, thereby allowing the measurement of the analyte concentration in the sample.

[0272] As stated above, the applicant recognizes that the optical system 880 can be used for various quality control reasons. First, the time it takes for the sample to reach the analysis zone can be used to determine if there are leaks or blockages in the system, where the optical system detects light passing through the analysis zone. Similarly, when a sample is expected to have a certain volume (e.g., approximately 10 microliters), there is an expected flow time associated with the sample passing through the channel and analysis zone. If the sample exceeds the expected flow time range, it may indicate that insufficient sample for analysis and / or an incorrect type of sample has been loaded into the analyzer. Additionally, the expected range of results can be determined based on the sample type (e.g., serum, blood, urine, etc.), and if the sample is outside the expected range, it may be an erroneous indication.

[0273] In one embodiment, the analyzer includes a temperature control system housed within a housing, configured to regulate the temperature within the analyzer. For a particular sample analysis, the sample may need to be maintained within a specific temperature range. For example, in one embodiment, it is necessary to maintain the temperature within the analyzer at approximately 37°C. Therefore, in one embodiment, the temperature control system includes a heater configured to heat the cartridge. In one embodiment, the heater is a resistance heater, which may be positioned on the bottom surface of the analyzer where the cartridge is located. In one embodiment, the temperature control system also includes a thermistor to measure the temperature of the cartridge and provides control circuitry to control the temperature.

[0274] In one embodiment, passive airflow within the analyzer can be used to cool the air within the analyzer, if desired. Optionally, a fan may be provided within the analyzer to reduce the temperature within the analyzer. In some embodiments, the temperature control system may include a Peltier thermoelectric heater and / or cooler within the analyzer.

[0275] In some embodiments, an identification system including one or more identifiers is used, and this identification system is associated with one or more components or materials associated with the cartridge and / or analyzer. As described in more detail below, the "identifier" itself may be "encoded" with information relating to the component (including the identifier) ​​(i.e., carried or contained by an information-carrying, storing, generating, or delivering device such as a radio frequency identification (RFID) tag or barcode), or it may not be encoded with information relating to the component itself, but may be associated only with information contained in a database, such as on a computer or computer-readable medium (e.g., information about the user and / or the sample to be analyzed). In the latter case, detection of such an identifier may trigger the retrieval and use of relevant information from the database.

[0276] An identifier that “encodes” information related to a component does not necessarily need to encode a complete set of information related to the component. For example, in some embodiments, an identifier may encode only information sufficient to uniquely identify the cartridge (e.g., serial number, part number, etc.), while other information about the cartridge (e.g., type, purpose (e.g., analysis type), ownership, location, position, connectivity, contents, etc.) may be stored remotely and associated only with the identifier.

[0277] "Information relating to a cartridge, material, or component" or "information associated with a cartridge, material, or component" is information relating to the identity, location, or place of the cartridge, material, or component, or the identity, location, or place of the contents of the cartridge, material, or component, and may additionally include information relating to the nature, state, or composition of the cartridge, material, component, or contents. "Information relating to a cartridge, material, or component or its contents" or "information associated with a cartridge, material, or component or its contents" may include information that identifies the cartridge, material, or component or its contents and distinguishes it from others. For example, "information relating to a cartridge, material, or component or its contents" or "information associated with a cartridge, material, or component or its contents" may refer to information indicating the following: the type or substance of the cartridge, material, or component or its contents; where it is or will be placed; how or how it should be placed; the function or purpose of the cartridge, material, or component or its contents; how the cartridge, material, or component or its contents are connected to other components of the system; the batch number, place of origin, calibration information, expiration date, destination, manufacturer or owner of the cartridge, material, or component or its contents; the type of analysis performed in the cartridge; information regarding whether the cartridge has been used / analyzed, etc.

[0278] Non-limiting examples of identifiers that can be used in the context of this invention include radio frequency identification (RFID) tags, barcodes, serial numbers, color labels, fluorescent or optical labels (e.g., using quantum dots), compounds, wireless labels, and magnetic labels.

[0279] In one embodiment, the identifier reader is an RFID reader configured to read an RFID identifier associated with a cartridge. For example, in one embodiment, the analyzer includes an RFID module and an antenna configured to read information from a cartridge inserted into the analyzer. In another embodiment, the identifier reader is a barcode reader configured to read a barcode associated with a cartridge. After the cartridge is inserted into the analyzer, the identifier reader can read information from the cartridge. The identifier on the cartridge may include one or more types of information, such as cartridge type, type of analysis to be performed, batch number, information about whether the cartridge has been used / analyzed, and other information described herein. The reader may also be configured to read information provided by a group of cartridges, such as information in a box of cartridges, such as (but not limited to) calibration information, expiration date, and any other information specific to that batch. Optionally, the identified information may be displayed to the user, for example to confirm the correct cartridge and / or the type of analysis being performed.

[0280] In some cases, the tag reader can be integrated with the control system via a communication path. Communication between the tag reader and the control system can occur along a hardwired network or can be transmitted wirelessly. In one embodiment, the control system can be programmed to identify a specific identifier (e.g., a tag identifier associated with information about the tag type, manufacturer, and analysis to be performed) indicating that the tag is suitable for connection to or insertion into a specific type of analyzer.

[0281] In one embodiment, the database contains identifiers for cartridges associated with pre-defined or programmed information about the system or cartridge's intended use for a specific purpose, user or product, or specific reaction conditions, sample type, reagent, user, etc. If an incorrect match or invalid identifier is detected, the process can be interrupted or the system rendered inoperable until the user is notified or when the user confirms.

[0282] In some embodiments, information from or associated with an identifier may be stored, for example, in computer memory or on a computer-readable medium, for future reference and record-keeping purposes. For example, some control systems may employ information from or associated with an identifier to identify which component (e.g., a cartridge) or cartridge type was used in a specific analysis, the date, time, duration of use, and conditions of use. This information may be used, for example, to determine whether one or more components of the analyzer should be cleaned or replaced. Optionally, the control system or any other suitable system may generate reports based on the collected information (including information encoded by or associated with an identifier), which may be used to provide proof of compliance with regulatory standards or verification of quality control.

[0283] Identifiers can also be used to encode or associate information with identifiers, for example, to determine whether a component associated with an identifier (e.g., a cartridge) is genuine or counterfeit. In some embodiments, determining the presence of a counterfeit component results in system latch-up. In one instance, the identifier may contain a unique identification code. In this instance, if an external or mismatched identification code (or no identification code) is detected, the process control software or analyzer will not allow the system to start (e.g., it may disable the system).

[0284] In some embodiments, information obtained from or associated with an identifier can be used to verify the identity of a consumer purchasing the cartridge and / or analyzer, or a person performing a biological, chemical, or pharmaceutical process. In some cases, information obtained from or associated with an identifier is used as part of a process for collecting data for system troubleshooting. The identifier may also include or be associated with information such as batch history, assembly process and instrument configuration diagrams (P and ID), troubleshooting history, etc. In some cases, system troubleshooting may be performed via remote access or may include the use of diagnostic software.

[0285] In one embodiment, the analyzer includes a user interface, which may be housed within a housing and configured to allow a user to input information into the sample analyzer. In another embodiment, the user interface is a touchscreen.

[0286] The touchscreen can guide the user through the operation of the analyzer, providing text and / or graphical instructions. For example, the touchscreen user interface can guide the user to insert a cartridge into the analyzer. The user can then be guided to enter the patient's name or other patient identification source / number into the analyzer (e.g., age, DRE test results, etc.). It should be understood that patient information (e.g., name, date of birth, and / or patient ID number) can be entered into the touchscreen user interface to identify the patient. The touchscreen can indicate the amount of time remaining to complete the sample analysis. The touchscreen user interface can then display the results of the sample analysis along with the patient's name or other identifying information.

[0287] In another embodiment, the user interface can be configured differently, such as using an LCD display and a single-button scrolling menu. In another embodiment, the user interface may consist only of a start button to activate the analyzer. In other embodiments, the user interface of a separate, independent device (e.g., a smartphone or mobile computer) can be used to interface with the analyzer.

[0288] The analyzer described above can be used in various ways to process and analyze samples placed within it. In one particular embodiment, after a mechanical component configured to connect with the cartridge indicates that the cartridge is correctly loaded into the analyzer, an identifier reader reads and identifies the information associated with the cartridge. The analyzer can be configured to compare the information with data stored in the control system to ensure it has calibration information for this specific sample. If the analyzer does not have appropriate calibration information, it can send a request to the user to upload the required specific information. The analyzer can also be configured to review the expiration date information associated with the cartridge and cancel the analysis if the expiration date has passed.

[0289] In one embodiment, after the analyzer has determined that the cartridge can be analyzed, a fluid flow source (e.g., a vacuum manifold) can be configured to contact the cartridge to ensure an hermetically sealed environment around the vacuum and exhaust ports. In one embodiment, the optical system can employ an initial measurement to obtain a reference reading. This reference reading can be used in both cases where the light source is enabled and disabled.

[0290] To initiate sample movement, a vacuum system can be activated, which rapidly alters the pressure within one or more channels (e.g., reducing it to approximately -30 kPa). This reduction in channel pressure forces the sample into the channel and through each of the analytical zones 709A-709D (see [link to analytical section]). Figure 10 After the sample reaches the final analysis zone 709D, it can continue to flow into the liquid containment zone 717.

[0291] In a specific set of embodiments, a microfluidic sample analyzer is used to measure the levels of iPSA, fPSA, tPSA, and / or hK2 in blood samples. In some embodiments, three, four, five, six, or more analysis zones (e.g., analysis zones 709A-709D) may be used to analyze the sample. For example, in a first analysis zone, a blocking protein (e.g., bovine serum albumin) may be used to block the channel wall, resulting in little or no protein adhesion to the analysis zone wall in the blood sample (aside from some non-specific bindings that may be washed away). This first analysis zone may serve as a negative control.

[0292] In the second analytical zone, the channel wall may be coated with a predetermined amount of prostate-specific antigen (PSA) to serve as a high-level or positive control. As the blood sample passes through the second analytical zone, little or no PSA protein in the blood binds to the channel wall. Gold-conjugated detection antibodies in the sample may dissolve inside the fluid connector 722 or may flow out from any other suitable location. These antibodies may still not bind to PSA in the sample, and therefore may bind to PSA on the channel wall to serve as a high-level or positive control.

[0293] In the third analytical zone, the channel wall may be coated with an iPSA-capturing antibody (e.g., an anti-iPSA antibody) that binds to an antigenic determinant on the PSA protein that is different from the gold-conjugated signaling antibody. As the blood sample flows through the third analytical zone, the iPSA protein in the blood sample can bind to the anti-iPSA antibody in a manner proportional to the concentration of these proteins in the blood.

[0294] In the fourth analytical zone, the channel wall may be coated with a capture antibody for fPSA (e.g., an anti-fPSA antibody), which binds to an antigenic determinant on the PSA protein that is different from the signaling antibody conjugated with gold. As the blood sample flows through the fourth analytical zone, the fPSA protein in the blood sample can bind to the anti-fPSA antibody in a manner proportional to the concentration of these proteins in the blood.

[0295] In the fifth analytical zone, the channel wall may be coated with a tPSA capture antibody (e.g., an anti-tPSA antibody) that binds to an antigenic determinant on the PSA protein that is different from the gold-conjugated signaling antibody. As the blood sample flows through the fifth analytical zone, the tPSA protein in the blood sample can bind to the anti-tPSA antibody in a manner proportional to the concentration of these proteins in the blood.

[0296] Optionally, in the sixth analytical zone, the channel wall may be coated with an hK2 capture antibody (e.g., an anti-hK2 antibody) that binds to an antigenic determinant on the protein that is different from the signal antibody conjugated with gold. As the blood sample flows through the sixth analytical zone, the hK2 protein in the blood sample can bind to the anti-hK2 antibody in a manner proportional to the concentration of these proteins in the blood.

[0297] Anti-PSA and anti-hK2 detection antibodies (such as gold-labeled antibodies) can be used to detect each of iPSA, fPSA, tPSA, and / or hK2. However, in other embodiments, a mixture of gold-labeled antibodies (such as gold-labeled anti-hK2 antibody, gold-labeled anti-PSA antibody, and / or gold-labeled anti-iPSA antibody) can be used for detection. In some embodiments, the gold-conjugated detection antibody in the sample may be dissolved inside the fluid connection tube 722 or may flow out from any other suitable location.

[0298] In some cases, measurements in the analytical region can be used not only to determine the concentration of the analyte in the sample but also as a control. For example, a threshold measurement can be established early in the amplification process. Measurements above (or below) this value can indicate that the analyte concentration is outside the range required for analysis. This technique can be used to identify, for example, whether a high-dose hook effect occurs during analysis, i.e., extremely high concentrations of the analyte result in artificially low readings.

[0299] In other embodiments, a number of different analytical zones may be provided, and the analysis may optionally include more than one analytical zone of the actual test sample. Other analytical zones can be used to measure other analytes, allowing the system to perform multiplexed analysis simultaneously using a single sample.

[0300] In one particular embodiment, a 10 μL blood sample takes approximately eight minutes to flow through four analysis zones. The analysis can be presumed to begin when the pressure within the channels reaches approximately -30 kPa. During this time, the optical system measures the light transmittance of each analysis zone, and in one embodiment, this data is transmitted to the control system approximately every 0.1 seconds. Using reference values, these measurements can be converted using the following formula:

[0301] Transmittance = (l-ld) / (lr-ld) (1)

[0302] in:

[0303] l = the intensity of transmitted light passing through the analysis region at a given time point

[0304] ld = the intensity of transmitted light passing through the analysis region when the light source is off.

[0305] lr = reference intensity (i.e., the intensity of transmitted light in the analysis zone when the light source is enabled or when the channel is only filled with air before the analysis begins).

[0306] and

[0307] Optical density = -log(transmittance) (2)

[0308] Therefore, the optical density of the analysis region can be calculated using these formulas.

[0309] Figure 13 This is an example control system 550 according to one embodiment (see...) Figure 12 Block diagram 900 illustrates how the control system described herein can be operationally associated with a variety of different components. The control system described herein can be implemented in many ways using a processor, such as using dedicated hardware or firmware, which is programmed using microcode or software to perform the functions listed above or any suitable combination thereof. The control system can control one or more operations of a single analysis (e.g., a biological, biochemical, or chemical reaction) or multiple analyses (separate or interconnected). For example, the control system may be housed within the analyzer housing and configured to communicate with an identification reader, user interface, fluid flow source, optical system, and / or temperature control system to analyze samples in a cartridge.

[0310] In one embodiment, the control system includes at least two processors, including a real-time processor that controls and monitors all subsystems directly connected to the cartridge. In one embodiment, at specific time intervals (e.g., every 0.1 seconds), this processor communicates with a higher-level second processor and directs the analyzer's operation (e.g., determining when to begin analyzing the sample and interpreting results), the higher-level second processor communicating with the user via a user interface and / or a communication subsystem (described below). In one embodiment, the two processors communicate via a serial communication bus. It should be understood that in another embodiment, the analyzer may include only one processor or two or more processors, as the invention is not limited thereto.

[0311] In one embodiment, the analyzer is capable of connecting to external devices and may include, for example, a port for connecting to one or more external communication units. External communication may be achieved, for example, via USB communication. Figure 13 As shown, the analyzer can output sample analysis results to a USB printer 901 or a computer 902. Additionally, a data stream generated by the real-time processor can be output to a computer or a USB memory stick 904. In some embodiments, the computer can also directly control the analyzer via a USB connection. Furthermore, other types of communication options are available, as the invention is not limited in this respect. For example, communication between the analyzer and Ethernet, Bluetooth, and / or Wi-Fi can be established via the processor.

[0312] The computational methods, steps, simulations, algorithms, systems, and system components described herein can be implemented using computer-implemented control systems, such as various embodiments of the computer-implemented systems described below. The methods, steps, systems, and system components described herein are not limited to any particular computer system described herein, as many other different machines can be used in their implementation.

[0313] A computer-implemented control system may be part of or operatively associated with a sample analyzer, and in some embodiments, as described above, is configured and / or programmed to control and adjust the operating parameters of the sample analyzer and to analyze and calculate values. In some embodiments, the computer-implemented control system may send and receive reference signals to set and / or control the operating parameters of the sample analyzer and optionally other system devices. In other embodiments, the computer-implemented system may be separate from and / or located remotely from the sample analyzer, and may be configured to receive data from one or more remote sample analyzer devices via indirect and / or portable devices, such as portable electronic data storage devices (e.g., disks), or via communication over a computer network (e.g., the Internet or a local intranet).

[0314] As described in more detail below, a computer-implemented control system may include several known components and circuits, including processing units (i.e., processors), storage systems, input / output devices and interfaces (e.g., interconnect mechanisms), and other components such as transmission circuitry (e.g., one or more buses), video and audio data input / output (I / O) subsystems, dedicated hardware, and other components and circuits. Additionally, the computer system may be a multiprocessor computer system or may include multiple computers connected via a computer network.

[0315] The computer-implemented control system may include a processor, such as commercially available processors, including x86, Celeron, and Pentium processors from Intel, similar devices from AMD and Cyrix, the 680X0 series microprocessors from Motorola, the PowerPC microprocessors from IBM, and one of the ARM processors. Many other processors are available, and the computer system is not limited to a specific processor.

[0316] The processor typically executes programs called the operating system. Examples of operating systems include Windows NT, Windows 95 or 98, Windows 7, Windows 8, UNIX, Linux, DOS, VMS, macOS, OSX, and iOS. The operating system controls the execution of other computer programs and provides scheduling, troubleshooting, input / output control, reporting, compilation, memory allocation, data and memory management, communication control, and related services. Together, the processor and operating system define the computer platform for applications written in high-level programming languages. However, the control system implemented by a computer is not limited to a specific computer platform.

[0317] A computer-implemented control system may include a memory system, which typically comprises a non-volatile recording medium that is readable and writable by a computer, examples of which include hard disks, optical disks, flash memory, and magnetic tape. This recording medium can be removable, such as a floppy disk, a read / write CD, or a memory stick, or it can be permanent, such as a hard disk drive.

[0318] The recording medium typically stores signals in binary form (i.e., in the form of sequences of 1s and 0s). A disk (such as a magnetic disk or optical disk) has many tracks on which these signals can typically be stored in binary form (i.e., in the form of sequences of 1s and 0s). These signals can define software programs, such as applications, to be executed by a microprocessor or information to be processed by the application.

[0319] The memory system of a computer-implemented control system may also include integrated circuit memory elements, which are typically volatile random access memories, such as dynamic random access memory (DRAM) or static random access memory (SRAM). In operation, the processor typically loads programs and data read from non-volatile recording media into the integrated circuit memory elements, which usually makes processor access to program instructions and data faster than non-volatile recording media.

[0320] Processors typically manipulate data within integrated circuit memory elements according to program instructions, and then copy the manipulated data to a non-volatile recording medium after processing is complete. Various mechanisms are known for managing data transfer between non-volatile recording media and integrated circuit memory elements, and... Figure 13 The computer-implemented control system that implements the above methods, steps, systems, and system components is not limited thereto. The computer-implemented control system is not limited to a specific memory system.

[0321] At least a portion of such a memory system can be used to store one or more of the aforementioned data structures (e.g., lookup tables) or equations. For example, at least a portion of a non-volatile recording medium can store at least a portion of a database comprising one or more of these data structures. Such a database can be any of a variety of database types, such as a file system including one or more flat file data structures in which data is organized into data units separated by delimiters, a relational database in which data is organized into data units stored in tables, an object-oriented database in which data is organized into data units stored as objects, another type of database, or any combination thereof.

[0322] A computer-implemented control system may include video and audio data I / O subsystems. The audio portion of the subsystem may include an analog-to-digital (A / D) converter that receives analog audio information and converts it into digital information. The digital information can be compressed using known compression systems for storage on a hard disk for later use. A typical video portion of the I / O subsystem may include a video image compressor / decompressor, many of which are known in the art. This compressor / decompressor converts analog video information into compressed digital information and vice versa. The compressed digital information can be stored on a hard disk for later use.

[0323] A computer-implemented control system may include one or more output devices. Examples of output devices include cathode ray tube (CRT) displays, liquid crystal displays (LCDs) and other video output devices, printers, communication devices (such as modems or network interfaces), storage devices (such as disks or tapes), and audio output devices (such as speakers).

[0324] Computer-implemented control systems may also include one or more input devices. Examples of input devices include keyboards, keypads, trackballs, mice, pens, and input tablets; communication devices such as those described above; and data input devices (e.g., audio and video capture devices and sensors). Computer-implemented control systems are not limited to the specific input or output devices described herein.

[0325] It should be understood that one or more computer-implemented control systems of any type can be used to implement the various embodiments described herein. Aspects of the invention can be implemented in software, hardware, or firmware, or any combination thereof. Computer-implemented control systems may include specially programmed special-purpose hardware, such as application-specific integrated circuits (ASICs). This special-purpose hardware can be configured to implement one or more of the methods, steps, simulations, algorithms, systems, and system components described above, either as part of the aforementioned computer-implemented control system or as a separate component.

[0326] Computer-implemented control systems and their components can be programmed using one or more suitable computer programming languages. These languages ​​may include procedural programming languages ​​such as C, Pascal, Fortran, and BASIC; object-oriented languages ​​such as C++, Java, and Eiffel; and other languages ​​such as scripting languages ​​or even assembly languages.

[0327] The methods, steps, simulations, algorithms, systems, and system components can be implemented using any of a variety of suitable programming languages, including procedural programming languages, object-oriented languages, other languages, and combinations thereof, which can be executed by such a computer system. These methods, steps, simulations, algorithms, systems, and system components can be implemented as modules of a computer program or as separate computer programs. These modules and programs can be executed on a separate computer.

[0328] This method, step, simulation, algorithm, system, and system component may be implemented individually or in combination as a computer program product that is physically realized as computer-readable signals on a computer-readable medium (e.g., a non-volatile recording medium, an integrated circuit memory element, or a combination thereof). For each of this method, step, simulation, algorithm, system, or system component, such computer program product may include computer-readable signals containing defined instructions physically embodied on a computer-readable medium as part of, for example, one or more programs, which, because they are executed by a computer, instruct the computer to perform the method, step, simulation, algorithm, system, or system component.

[0329] It should be understood that various embodiments having one or more of the above features can be formed. The above aspects and features can be used in any suitable combination, as the invention is not limited thereto. It should also be understood that the drawings illustrate various components and features that can be incorporated into various embodiments. For simplicity, some drawings may illustrate more than one optional feature or component. However, the invention is not limited to the specific embodiments disclosed in the drawings. It should be recognized that the invention covers embodiments that may include only a portion of the components illustrated in any one of the figures, and / or may also cover embodiments that combine components illustrated in multiple different figures.

[0330] Other preferred embodiments

[0331] It should be understood that the methods of the present invention can be incorporated in various embodiments, only a few of which are disclosed herein. It will be apparent to those skilled in the art that other embodiments exist without departing from the spirit of the invention. Therefore, the embodiments described are illustrative and should not be considered limiting.

[0332] Example

[0333] Example 1

[0334] Research

[0335] A total of seven separate studies have been performed using statistical models. These studies included a total of 7,647 men with elevated PSA, of whom 2,270 had cancer, and five of these studies served as external validation. In addition, these studies were systematically designed to cover a wide range of clinical scenarios. Perhaps most importantly, one study included a natural history approach. Since biopsy results are a surrogate endpoint, the key is not whether a man has prostate cancer, but whether he is at risk of prostate cancer that will affect his life. Ideally, the study would take blood from the patient and then follow him for several years without further screening to determine prostate cancer outcomes. We have been fortunate to be able to conduct this study [Vickers, AJ, et al., Cancer Epidemiol Biomarkers Prey, 2011. 20(2): p. 255-61].

[0336] The Malmö diet and cancer cohort was part of a large-group study identifying dietary risk factors for cancer mortality, in which 11,063 men living in Malmö, Sweden, born between 1923 and 1945, provided EDTA-anticoagulated blood samples from 1991–1996. Results were verified via the Swedish Cancer Registry. Indicator values ​​were obtained from archived blood samples analyzed in 2008, which had previously been validated for obtaining accurate kallikrein measurements from stored blood. [Ulmert, D., et al., Clin. Chem., 2006. 52(2): 235–9]. PSA testing was very low-grade, with almost all cases undergoing clinical diagnosis. Therefore, this study tracked the “natural history” of prostate cancer in men with elevated PSA. Of the 792 men with a baseline PSA of 3 ng / ml, 474 were subsequently diagnosed with prostate cancer during a median follow-up of 11 years. In predicting any cancer and advanced cancer (T3 or T4 stage, or metastatic) (specifically, those cancers that are likely to be fatal), the four kallikrein group statistical models showed significantly higher predictive discriminant value than PSA. As found in previous studies, according to the models, approximately 50% of men have a risk of less than 20% for prostate cancer. Based on our model estimates, only 13 out of every 1000 men with elevated PSA have a risk of <20% but are diagnosed with cancer within five years; only 1 man is diagnosed with advanced cancer at the time of diagnosis.

[0337] The Malmö cohort demonstrates several important features of our predictive model. First, it constitutes external validation. Second, it shows that the model predicts clinically diagnosed cancers that, by definition, do not constitute overdiagnosis. Third, the study shows that the cancers missed by the model are those considered overdiagnosed: our biopsy study data indicate that this cohort is classified as low-risk: approximately 60 out of 1000 men have biopsy-detectable cancers; the Malmö cohort data indicate that less than a quarter of these will become clinically apparent after 5 years of follow-up. Fourth, it demonstrates that the model very strongly predicts the types of aggressive cancers that are likely to shorten men's lives. Finally, the data show that clinical use of the model does not lead to significant harm in terms of delayed diagnosis, as only 1 out of 1000 men with a low risk of prostate cancer according to the model was subsequently diagnosed with advanced cancer. Table 2 provides an overview of our research on our model.

[0338] In short, our preliminary research can be summarized as follows:

[0339] 1. Multiple forms of kallikrein in the blood (total PSA, free PSA, intact PSA, and hK2) can predict prostate biopsy results in men with elevated total PSA.

[0340] 2. Construct a statistical prediction model based on four kallikrein enzymes using a single training set.

[0341] 3. This combines information from the new indicators with clinical examinations to provide a predicted probability of cancer.

[0342] 4. In the five separate studies that constitute external validation, the research group has involved a total of more than 7,500 men, of whom nearly 2,250 were diagnosed with cancer.

[0343] 5. This model has a high discrimination rate for prostate cancer, with a much higher AUC than statistical models based solely on standard predictors (total PSA, age, and digital rectal examination).

[0344] 6. Based on the analysis of judgments, using four kallikrein statistical prediction models to determine referral for prostate biopsy will improve clinical outcomes compared to alternative strategies (e.g., performing biopsies on all men).

[0345] 7. The model is valuable across the following clinical configurations: with and without prior screening; with and without prior biopsy; with and without clinical examination prior to referral for biopsy.

[0346] Table 2. Research Overview

[0347]

[0348]

[0349] * Diagnosed as T3 / T4 or metastatic.

[0350] 8. Applying this model to archived blood samples from unscreened, longitudinally tracked men demonstrated that men with elevated PSA levels but at low risk according to the statistical model were extremely unlikely to develop invasive cancers in the following 5 to 10 years. Conversely, clinically diagnosed invasive cancers were common in men at high risk according to the model.

[0351] Illustrative model used for this example:

[0352] Age: Enter your age

[0353] tPSA: Enter the total PSA (ng / ml)

[0354] fPSA: Enter free PSA (ng / ml)

[0355] iPSA: Enter the complete PSA (ng / ml)

[0356] hK2: Enter hK2 (ng / ml)

[0357] If tPSA ≥ 25, then use: L = 0.0733628 × tPSA - 1.377984

[0358] Prostate cancer risk = exp(L) / [1+exp(L)]

[0359] If tPSA < 25, then use one of the following two equations, one of which incorporates clinical information and the other does not:

[0360] The cubic spline variables are determined as follows:

[0361] Spline1_tPSA

[0362] =-(162-4.4503) / (162-3)x(tPSA-3)^3+max(tPSA-4.4503,0)^3

[0363] Spline2_tPSA

[0364] =-(162-6.4406) / (162-3)x(tPSA-3)^3+max(tPSA-6.4406,0)^3

[0365] If fPSA < 11.8, then Spline1_fPSA

[0366] =-(11.8-0.84) / (11.8-0.25)x(fPSA-0.25)^3+max(fPSA-0.84,0)^3

[0367] If fPSA > 11.8, then Splinel_fPSA

[0368] =(11.8-0.84)x(0.84-0.25)x(11.8+0.84+0.25-3x fPSA)

[0369] If fPSA < 11.8, then Spline2_fPSA

[0370] =-(11.8-1.29) / (11.8-0.25)x(fPSA-0.25)^3+max(fPSA-1.29,0)^3

[0371] If fPSA > 11.8, then Spline2_fPSA

[0372] =(11.8-1.29)x(1.29-0.25)x(11.8+1.29+0.25-3x fPSA)

[0373] For laboratory models:

[0374] The definition is as follows:

[0375] xl=0.0846726x tPSA+-.0211959x Spline1_tPSA+.0092731x Spline2_tPSA

[0376] x2=-3.717517x fPSA-0.6000171x Spline1_fPSA+0.275367x Spline2_fPSA

[0377] x3 = 3.968052x iPSA

[0378] x4=4.508231x hK2

[0379] but:

[0380] L = -1.735529 + 0.0172287 × age + x1 + x2 + x3 + x4

[0381] Prostate cancer risk = exp(L) / [1+exp(L)]

[0382] This provides a risk of prostate cancer in the absence of any clinical information. We assume that if this risk is high, the clinician will order a clinical examination and digital rectal exam. Then, with the DRE coded as 0 or 1, the following model is run twice to provide the risk based on whether the DRE is normal or abnormal, respectively. The definitions are as follows:

[0383] xl=0.0637121x tPSA-0.0199247x Spline1_PSA+0.0087081x Spline2_tPSA

[0384] x2=-3.460508x fPSA-0.4361686x Spline1_fPSA+0.1801519x Spline2_fPSA

[0385] x3 = 4.014925x iPSA

[0386] x4 = 3.523849x hK2

[0387] If the DRE test is positive, the risk is:

[0388] L = -1.373544 + 0.9661025 + 0.0070077 × age + xl + x2 + x3 + x4

[0389] For DRE negative:

[0390] L = -1.373544 + 0.0070077 × age + x1 + x2 + x3 + x4

[0391] The risks are identified as follows:

[0392] Prostate cancer risk = exp(L) / [1+exp(L)]

[0393] Regarding recalibration:

[0394] Recalibration can be used for men with previously negative biopsies, but it can also be used in other cases where the event rate differs significantly from the event rate (29%) observed in the (previously unscreened) Rotterdam cohort. The definitions are as follows:

[0395] Win rate_cancer = Pr(cancer) / (1 - (Pr(cancer)))

[0396] Win rate prediction = predicted cancer risk / (1 - predicted cancer risk), then:

[0397] Bayes Factor = Win Rate - Cancer / Win Rate - Prediction

[0398] y_adj = y + log(Bayes factor)

[0399] Recalibrated prostate cancer risk = exp(y_adj) / [1+exp(y_adj)]

[0400] Example 2 (Predictability)

[0401] This is a illustrative example describing the use of a cartridge and analyzer to detect iPSA, fPSA, tPSA, and hK2 in a sample by electroless deposition of silver onto gold particles associated with the sample. Figure 14 A schematic diagram of a microfluidic system 1500 including the cartridge used in this example. The cartridge has... Figure 7 The cartridge 520 shown has a similar shape.

[0402] The microfluidic system includes analytical zones 1510A-1510F, a waste containment zone 1512, and an outlet 1514. The analytical zone includes a microfluidic channel 50 μm deep, 120 μm wide, and 175 mm in total length. The microfluidic system also includes a microfluidic channel 1516 and channel branches 1518 and 1520 (each with inlets 1519 and 1521). Channel branches 1518 and 1520 are 350 μm deep and 500 μm wide. Channel 1516 is formed by sub-channels 1515, each 350 μm deep and 500 μm wide, located at the intersecting surface of the cartridge and connected by through-holes 1517 with a diameter of approximately 500 μm. Although... Figure 14The illustration shows reagents stored on a single side of the cartridge, but in other embodiments, reagents are stored on both sides of the cartridge. Channel 1516 has a total length of 390 mm, and branches 1518 and 1520 are both 360 mm long. Before sealing the channels, anti-PSA and anti-hK2 capture antibodies are attached to the microfluidic system surfaces in analytical regions 1510 and 1511, as described in more detail below.

[0403] Before first use, the microfluidic system is loaded with liquid reagents stored in the cartridge. Using a pipette, a series of seven wash plugs 1523-1529 (approximately 2 μL each of water or buffer solution) are loaded into subchannel 1515 of channel 1516 using the through-hole. Each wash plug is separated by an air plug. Using a pipette, fluid 1528 containing silver salt solution is loaded into branch channel 1519 via port 1519. Fluid 1530 containing reducing solution is loaded into branch channel 1520 via port 1521. Each liquid shown is separated from the other by an air plug. Ports 1514, 1519, 1521, 1536, 1539, and 1540 are sealed with easily removable or puncturable tape. This allows the liquids to be stored in the microfluidic system before first use.

[0404] Upon first use, the user peels off the tape covering the port openings to open ports 1514, 1519, 1521, 1536, 1539, and 1540. Connect tube 1544, containing lyophilized anti-PSA and anti-hK2 antibodies labeled with colloidal gold and supplemented with 10 μL of sample blood (1522), to ports 1539 and 1540. This tube is designed for use with… Figure 7 This is part of a fluid connector with the shape and configuration shown. It forms a fluid connection between the analysis zone 1510 and the channel 1516, which would otherwise not be connected and not in fluid communication with each other before first use.

[0405] A cartridge, including a microfluidic system 1500, is inserted into an opening in the analyzer. The analyzer housing includes an arm disposed within the housing and configured to engage with a cam surface on the cartridge. This arm extends at least partially into the opening in the housing, so that when the cartridge is inserted into the opening, the arm is pushed away from the opening to a second position, allowing the cartridge to enter the opening. After the arm engages with the inward cam surface of the cartridge, the cartridge is positioned and held within the analyzer housing, and spring offset prevents the cartridge from slipping out of the analyzer. The analyzer senses the cartridge insertion via a position sensor.

[0406] An RFID reader housed within the analyzer housing reads the RFID tags on the cartridges, which contain batch identification information. The analyzer uses this identifier to match batch information stored within the analyzer (e.g., calibration information, cartridge expiration date, verification that the cartridge is new, and the type of analysis to be performed on the cartridge). The user is prompted to input information about the patient (from whom the sample was obtained) into the analyzer using the touchscreen. After the user verifies the information about the cartridge, the control system begins the analysis.

[0407] The control system includes programmed instructions for performing the analysis. To initiate the analysis, signals are sent to electronics controlling the vacuum system, which is part of the analyzer and provides fluid flow. A manifold with an O-ring is pressed against the cartridge surface by a solenoid. One port on the manifold (via the O-ring) seals port 1536 of the cartridge's microfluidic system. This port on the manifold is connected via a tube to a simple solenoid valve open to the atmosphere. Another vacuum port on the manifold (via the O-ring) seals port 1514 of the cartridge's microfluidic system. A vacuum of approximately -30 kPa is applied to port 1514. Throughout the analysis, the channel comprising analysis zone 1510 located between ports 1540 and 1514 has a substantially constant non-zero pressure drop of approximately -30 kPa. Sample 1522 flows in the direction of arrow 538 into each of analysis zones 1510A-1510H. As described in more detail below, as the fluid flows through the analysis zone, the PSA and hK2 proteins in sample 1522 are captured by anti-PSA and anti-hK2 antibodies immobilized on the walls of the analysis zone. The sample takes approximately 7-8 minutes to pass through the analysis zone, after which the remaining sample is trapped in the waste containment zone 1512.

[0408] The initiation of analysis also involves the control system sending signals to optical detectors positioned adjacent to each of the analysis zones 1510 to initiate detection. Each detector associated with an analysis zone records the transmittance of light passing through the analysis zone channel. As the sample passes through each analysis zone, peaks are generated. The peaks (and troughs) measured by the detectors are (or converted into) signals sent to the control system, which compares the measured signals with reference signals or values ​​pre-programmed into the control system. The control system includes a pre-programmed instruction table to provide feedback to the microfluidic system, at least in part, based on the signal / value comparison.

[0409] exist Figure 14 In the first analytical zone 1510-A of the device 1500, the channel wall of this analytical zone is blocked with a blocking protein (bovine serum albumin) before first use (e.g., before sealing the device). Few or no proteins in the blood sample adhere to the wall of analytical zone 1510-A (aside from some non-specific bindings that may be washed away). This first analytical zone serves as a negative control.

[0410] In the second analytical zone 1510-B, the channel wall of this analytical zone is coated with a predetermined amount of prostate-specific antigen (PSA) before first use (e.g., before sealing the device) to serve as a high-level or positive control. As the blood sample flows through the second analytical zone 1510-B, little or no PSA protein in the blood binds to the channel wall. Gold-conjugated signaling antibodies in the sample may still not bind to PSA in the sample, and therefore, they may bind to PSA on the channel wall to serve as a high-level or positive control.

[0411] In the third analytical zone 1510-C, the channel walls are coated with a capture antibody—an anti-iPSA antibody—that binds to an antigenic determinant on the iPSA protein that is different from the gold-conjugated signaling antibody. These walls are coated before first use (e.g., before sealing the device). As a blood sample flows through the fourth analytical zone during use, the iPSA protein in the blood sample binds to the anti-iPSA antibody in a manner proportional to the concentration of these proteins in the blood. Because the sample, which includes iPSA, also includes gold-labeled anti-iPSA antibodies coupled to iPSA, the iPSA captured on the analytical zone walls forms a sandwich immune complex.

[0412] In the fourth analytical zone 1510-D, the channel walls are coated with a capture antibody—an anti-fPSA antibody—that binds to an antigenic determinant on the fPSA protein that is different from the gold-conjugated signaling antibody. These walls are coated before first use (e.g., before sealing the device). As a blood sample flows through the fourth analytical zone during use, the fPSA protein in the blood sample binds to the anti-fPSA antibody in a manner proportional to the concentration of these proteins in the blood. Because the sample, which includes fPSA, also includes a gold-labeled anti-fPSA antibody coupled to fPSA, the fPSA captured on the analytical zone walls forms a sandwich immune complex.

[0413] In the fifth analytical zone 1510-E, the channel walls are coated with a capture antibody—an anti-tPSA antibody—that binds to an antigenic determinant on the tPSA protein that is different from the gold-conjugated signaling antibody. These walls are coated before first use (e.g., before sealing the device). As a blood sample flows through the fifth analytical zone during use, the tPSA protein in the blood sample can bind to the anti-tPSA antibody in a manner proportional to the concentration of these proteins in the blood. Because the sample, which includes tPSA, also includes a gold-labeled anti-tPSA antibody coupled to tPSA, the tPSA captured on the analytical zone walls forms a sandwich immune complex.

[0414] While gold-labeled anti-iPSA, anti-fPSA, and anti-tPSA antibodies can be used, in other embodiments, gold-labeled anti-PSA antibodies bound to any PSA protein can be used for detection.

[0415] The first, second, third, fourth and fifth analytical regions are formed on a single substrate layer. The sixth (1510-F), seventh (1510-G) and eighth (1510-H) analytical regions are formed on another substrate layer (1511).

[0416] In the sixth analytical zone 1510-F, the channel walls are coated with a capture antibody—an anti-hK2 antibody—that binds to an antigenic determinant on the hK2 protein that is different from the gold-conjugated signaling antibody. These walls are coated before first use (e.g., before sealing the device). As a blood sample flows through the sixth analytical zone during use, the hK2 protein in the blood sample can bind to the anti-hK2 antibody in a manner proportional to the concentration of these proteins in the blood. Because the sample containing hK2 also includes a gold-labeled anti-hK2 antibody coupled to hK2, the hK2 captured on the analytical zone walls forms a sandwich immune complex.

[0417] The seventh analytical region 1510-G can be used as a negative control as described above regarding analytical region 1510-A. The eighth analytical region 1510-H can be used as a high-level or positive control as described above regarding analytical region 1510-B.

[0418] Optionally, a ninth analytical zone (not shown) can be used as a low-level control. In this embodiment, the channel wall of this analytical zone may be coated with a predetermined small amount of PSA before first use (e.g., before sealing the device) to serve as a low-level control. As the blood sample flows through this analytical zone, little or no PSA protein in the sample binds to the channel wall. Gold-conjugated signaling antibodies in the sample may bind to the PSA on the channel wall to serve as a low-level control.

[0419] Washing fluids 1523-1529 follow the sample in the direction of arrow 1538 through the analysis zone 1510 to the waste containment zone 1512. As the washing fluid flows through the analysis zone, it washes away any remaining unbound sample components. Each wash plug cleans the channels of the analysis zone, providing progressively more thorough cleaning. The final wash fluid 1529 (water) washes away salts that can react with silver salts (e.g., chlorides, phosphates, azides).

[0420] like Figure 15 As illustrated in the graph, each detector associated with the analysis zone measures a pattern 1620 of peaks and troughs as the wash fluid flows through the analysis zone. The troughs correspond to the wash plugs (which are the clarifying fluid and therefore provide maximum light transmittance). The peaks between each plug represent air between each clarifying fluid plug. Since the analysis includes seven wash plugs, there are seven troughs and seven peaks in graph 1600. The first trough 1622 is generally less deep than the other troughs 1624 because the first wash plug often traps blood cells remaining in the channel and is therefore not completely clear.

[0421] The final air peak 1628 is much longer than the previous peaks because there is no wash plug following it. When the detector detects the length of this air peak, one or more signals are sent to the control system, which compares the duration of this peak with a preset reference signal or input value of a specific length. If the measured duration of the peak is sufficiently longer than the reference signal, the control system sends a signal to the electronics controlling the exhaust valve 1536 to actuate the valve and begin mixing fluids 1528 and 1530. (Note: The signal for air peak 1628 can be combined with signals indicating: 1) peak intensity; 2) the position of this peak over time; and / or 3) one or more signals indicating that a series of peaks 1620 of a specific intensity have passed. In this way, the control system, for example, uses a signal pattern to distinguish air peak 1628 from other long-duration peaks, such as peak 1610 from the sample.)

[0422] Refer to Figure 14 To initiate mixing, the solenoid connecting the manifold to exhaust port 1536 is closed. Since a vacuum is maintained and no air can enter via exhaust valve 1536, air enters the device through ports 1519 and 1521 (which are open). This forces two fluids 1528 and 1530 in the two storage channels upstream of exhaust valve 1536 to move substantially simultaneously towards outlet 1514. These reagents mix at the channel intersection to form an amplification reagent (reactive silver solution) with a viscosity of approximately 1 × 10⁻³ Pa·s. The volume ratio of fluids 1528 and 1530 is approximately 1:1. The amplification reagent continues through the downstream storage channel, through tube 1544, through the analysis zone 1510, and subsequently into the waste containment zone 1512. After a set time (12 seconds), the analyzer reopens exhaust valve 1536, allowing air to flow through exhaust valve 1536 (instead of the non-exhaust port). This leaves some reagent in the upstream storage channels 1518 and 1520. This also produces a single mixed amplification reagent plug. Closing the exhaust valve for 12 seconds produces approximately 50 μL of the amplification plug. (Another way to trigger the exhaust valve to reopen, instead of simple timing, is to detect the amplification reagent when it first enters the analysis area.)

[0423] Because the mixed amplification reagent stabilizes for only a few minutes (typically less than 10 minutes), it is used in the analysis zone 1510 less than one minute after mixing. The amplification reagent is a clear solution, therefore the optical density is at its lowest when it enters the analysis zone. As the amplification reagent passes through the analysis zone, silver is deposited on the captured gold particles, increasing the colloidal size and thus amplifying the signal. (As mentioned above, gold particles can be present in both low- and high-grade positive control analysis zones, and to some extent, PSA and hK2 are present in the sample and in the test analysis zone.) Silver can subsequently deposit on top of the already deposited silver, resulting in more and more silver deposited in the analysis zone. The deposited silver ultimately reduces the transmittance of light through the analysis zone. The reduction in transmitted light is proportional to the amount of silver deposited and can be related to the amount of gold colloid trapped on the channel walls. In analysis zones without silver deposition (e.g., negative controls, or test zones when the sample does not contain the target protein), the optical density does not increase (or increases minimally). In analysis zones with significant silver deposition, the slope and final grade of the pattern of increased optical density are higher. The analyzer monitors the pattern of this optical density during amplification in the test region to determine the concentration of the analyte in the sample. In one test version, the pattern is monitored during the first three minutes of amplification. The optical density over time in each analytical region is recorded and... Figure 14 Curves 1640-1647 are shown in the diagram. These curves correspond to the signals generated in the analysis region. After three minutes of amplification, the analyzer stops testing. Optical measurements are no longer recorded, and the manifold is disengaged from the device.

[0424] A computer (e.g., within the analyzer) determines the values ​​(e.g., concentrations) of blood parameters (e.g., iPSA, fPSA, tPSA, and / or hK2) based on a curve. The values ​​are sent to a processor (which communicates electronically with the analyzer) programmed to evaluate a logistic regression model (e.g., as described herein) based at least in part on the received values ​​to determine the odds of a patient's prostate cancer risk, an indication of the estimated prostate gland volume, and / or an indication of the likelihood of a positive prostate cancer biopsy.

[0425] Test results are displayed on the analyzer screen and transmitted to a printer, computer, or any output device selected by the user. The user can remove and discard the device from the analyzer. The sample and all reagents used in the analysis remain in the device. The analyzer is ready for another test.

[0426] This illustrative example demonstrates that an analyzer controlling fluid flow within a cartridge can be used in a single microfluidic system to modulate fluid flow using feedback from one or more measurement signals to analyze samples containing iPSA, fPSA, tPSA, and / or hK2. This illustrative example also shows that the results of this analysis can be used to determine the probability of a patient's prostate cancer risk, an indication of estimated prostate gland volume, and / or an indication of the likelihood of a positive prostate cancer biopsy.

Claims

1. An analysis system, comprising: The analysis region includes one or more binding ligands fixed thereto in a solid phase portion, wherein the one or more binding ligands are selected from the group consisting of binding ligands that bind free prostate-specific antigen fPSA, binding ligands that bind intact prostate-specific antigen iPSA, binding ligands that bind total prostate-specific antigen tPSA, and binding ligands that bind human kallikrein 2 hK2. At least one detector configured to detect the presence of an analyte in a sample from the analytical region, wherein the analyte is selected from the group consisting of four markers: tPSA, fPSA, iPSA, and hK2; and A processor, programmed to: evaluate a logistic regression model based on information received from the at least one detector to determine its association with prostate cancer in humans, wherein evaluating the logistic regression model includes: When the value of tPSA is equal to or greater than the threshold, a first logistic regression model is selected from multiple logistic regression models, and when the value of tPSA is lower than the threshold, a second logistic regression model is selected from the multiple logistic regression models. The first logistic regression model includes the coefficients of age and each of tPSA, and the second logistic regression model uses different coefficients for each of multiple variables, including age and at least two variables included in the information received from the at least one detector and selected from the group including fPSA, iPSA and tPSA. Determine whether the chosen logistic regression model includes all or fewer markers; If the selected logistic regression model includes fewer than all markers, the first logistic regression model is used to determine the probability of a positive biopsy for prostate cancer. If the selected logistic regression model includes all markers, the second logistic regression model is used to determine the probability of a positive biopsy for prostate cancer. The logarithm is determined by multiplying each variable in the selected logistic regression model by its corresponding coefficient value to produce a calibrated variable, and then summing the values ​​of the calibrated variable; and The logarithm is used to generate the probability of a positive biopsy for prostate cancer in the person in question. The processor is also programmed to output an indication of the probability of a positive biopsy for prostate cancer.

2. The analysis system according to claim 1, wherein, The plurality of variables includes fPSA and tPSA, and wherein the processor is further programmed to: The first clause that defines fPSA; The first fPSA value is calculated by evaluating the first line of fPSA using the fPSA value included in the information received from the at least one detector; The first clause of the tPSA is limited; and The first tPSA value is calculated by evaluating the first line of tPSA using the tPSA values ​​included in the information received from the at least one detector. The values ​​of the calibrated variables include the first fPSA value calibrated by the first coefficient value and the first tPSA value calibrated by the second coefficient value.

3. The analysis system according to claim 2, wherein, The processor is also programmed to: The second spline of the fPSA is constrained; The second fPSA value is calculated by evaluating a second spline of fPSA using the fPSA value included in the information received from the at least one detector; The second spline of tPSA is constrained; as well as The second tPSA value is calculated by evaluating the tPSA using a second spline that includes the tPSA value from the information received from the at least one detector. The values ​​of the calibrated variables also include the second fPSA value calculated by calibration using the third coefficient value and the second tPSA value calculated by calibration using the fourth coefficient value.

4. The analysis system according to claim 3, wherein, Each of the first spline of fPSA, the second spline of fPSA, the first spline of tPSA, and the second spline of tPSA is a cubic spline.

5. The analysis system according to claim 1, wherein, The information received from the at least one detector includes information on fPSA, iPSA, tPSA, and hK2, wherein the plurality of variables includes age, fPSA, iPSA, tPSA, and hK2.

6. The analysis system according to claim 1, wherein, Indicating the probability of a positive biopsy for prostate cancer includes communicating to the patient or physician the likelihood that a prostate cancer biopsy will be positive.

7. The analysis system according to claim 1, wherein, The at least one detector is configured to utilize an optical or luminescent detection technique selected from the group consisting of light transmission, light absorption, light scattering, light reflection, visual technology, photoluminescence, fluorescence, chemiluminescence, bioluminescence, and electrochemiluminescence.

8. The analysis system according to claim 1, wherein, The at least one detector is configured to detect chemiluminescent or fluorescent emission, wherein the chemiluminescent or fluorescent emission indicates an analyte bound to an analyte binding ligand.

9. The analysis system according to claim 1, wherein, The at least one detector is configured to detect changes in the optical signal over time.

10. The analysis system according to claim 1, wherein, The sample is whole blood, serum, or plasma.

11. The analysis system according to claim 1, wherein, The analysis zone includes a microfluidic channel comprising at least one inlet and one outlet.

12. The analysis system according to claim 1, wherein, The one or more binding ligands include a first binding ligand and a second binding ligand, wherein the first binding ligand and the second binding ligand are different.

13. The analysis system according to claim 12, wherein, The first binding ligand is adapted to specifically bind to the first of fPSA, iPSA, and tPSA.

14. The analysis system according to claim 13, wherein, The second binding ligand is adapted to specifically bind to a second of fPSA, iPSA, and tPSA.

15. The analysis system according to claim 14, wherein, The one or more binding ligands also include a third binding ligand adapted to bind specifically to hK2.

16. The analysis system according to claim 1, wherein, The indication of the probability of a positive biopsy for prostate cancer includes an interpretable scale used to guide the judgment regarding whether a person should have a biopsy.

17. The analysis system according to claim 1, wherein, The indication of the probability of a positive biopsy for prostate cancer includes the determination of a positive biopsy for high-grade or low-grade cancer.

18. A non-volatile computer-readable storage medium having a computer program stored thereon, the computer program causing, when executed by a computer, to: At least one detector detects the presence of an analyte in a sample from an analytical region of the analytical system, said analytical region comprising one or more binding ligands immobilized therein in a solid phase portion, wherein, The one or more binding ligands are selected from the group consisting of binding ligands that bind total prostate-specific antigen tPSA, binding ligands that bind free prostate-specific antigen fPSA, binding ligands that bind intact prostate-specific antigen iPSA, and binding ligands that bind human kallikrein 2 hK2, wherein the analyte is selected from the group consisting of the four markers tPSA, fPSA, iPSA, and hK2. At least one computer processor: When the value of tPSA is equal to or greater than the threshold, a first logistic regression model is selected from multiple logistic regression models, and when the value of tPSA is lower than the threshold, a second logistic regression model is selected from the multiple logistic regression models. The first logistic regression model includes the coefficients of age and each of tPSA, and the second logistic regression model uses different coefficients for each of multiple variables, including age and at least two variables included in the information received from the at least one detector and selected from the group including fPSA, iPSA and tPSA. Determine whether the chosen logistic regression model includes all or fewer markers; If the selected logistic regression model includes fewer than all markers, the first logistic regression model is used to determine the probability of a positive biopsy for prostate cancer. If the selected logistic regression model includes all markers, the second logistic regression model is used to determine the probability of a positive biopsy for prostate cancer. The logarithm is determined by multiplying each variable in the selected logistic regression model by its corresponding coefficient value to produce a calibrated variable, and the values ​​of the calibrated variable are summed to produce the probability of a positive biopsy for prostate cancer; and Outputs an indication of the probability of a positive biopsy for prostate cancer.

19. The non-volatile computer-readable storage medium according to claim 18, wherein, The computer program also causes the at least one computer processor to: The first clause that defines fPSA; The first fPSA value is calculated by evaluating the first line of fPSA using the fPSA value included in the information received from the at least one detector; The first clause of tPSA is specified; as well as The first tPSA value is calculated by evaluating the first line of tPSA using the tPSA values ​​included in the information received from the at least one detector. The values ​​of the calibrated variables include the first fPSA value calibrated by the first coefficient value and the first tPSA value calibrated by the second coefficient value.

20. The non-volatile computer-readable storage medium according to claim 19, wherein, The computer program also causes the at least one computer processor to: The second spline of the fPSA is constrained; The second fPSA value is calculated by evaluating a second spline of fPSA using the fPSA value included in the information received from the at least one detector; The second spline of tPSA is constrained; as well as The second tPSA value is calculated by evaluating the tPSA using a second spline that includes the tPSA value from the information received from the at least one detector. The values ​​of the calibrated variables also include the second fPSA value calculated by calibration using the third coefficient value and the second tPSA value calculated by calibration using the fourth coefficient value.

21. The non-volatile computer-readable storage medium according to claim 20, wherein, Each of the first spline of fPSA, the second spline of fPSA, the first spline of tPSA, and the second spline of tPSA is a cubic spline.

22. The non-volatile computer-readable storage medium according to claim 20, wherein, The information received from the at least one detector includes information on fPSA, iPSA, tPSA, and hK2, wherein the plurality of variables includes age, fPSA, iPSA, tPSA, and hK2.

23. The non-volatile computer-readable storage medium according to claim 20, wherein, Indicating the probability of a positive biopsy for prostate cancer includes communicating to the patient or physician the likelihood that a prostate cancer biopsy will be positive.

24. The non-volatile computer-readable storage medium according to claim 20, wherein, Detection of the presence of an analyte in a sample includes optical or luminescent detection techniques selected from the group consisting of light transmission, light absorption, light scattering, light reflection, visual technology, photoluminescence, fluorescence, chemiluminescence, bioluminescence, and electrochemiluminescence.

25. The non-volatile computer-readable storage medium according to claim 20, wherein, Detecting the presence of an analyte in a sample includes detecting chemiluminescent or fluorescent emission of the analyte that indicates binding to the analyte's binding ligand.

26. The non-volatile computer-readable storage medium according to claim 20, wherein, The detection of the presence of analytes in a sample includes detecting changes in the optical signal over time.

27. The non-volatile computer-readable storage medium according to claim 20, wherein, The indication of the probability of a positive biopsy for prostate cancer includes an interpretable scale used to guide the judgment regarding whether a person should have a biopsy.

28. The non-volatile computer-readable storage medium according to claim 20, wherein, The indication of the probability of a positive biopsy for prostate cancer includes the determination of a positive biopsy for high-grade or low-grade cancer.

29. An analysis system, comprising: At least one detector configured to detect the presence of an analyte in a sample from an analytical region of the analytical system, the analytical region comprising one or more binding ligands immobilized therein, wherein the one or more binding ligands are selected from the group consisting of binding ligands binding total prostate-specific antigen (tPSA), binding ligands binding free prostate-specific antigen (fPSA), binding ligands binding intact prostate-specific antigen (iPSA), and binding ligands binding human kallikrein 2 (hK2), wherein the analyte is selected from the group consisting of four labels: tPSA, fPSA, iPSA, and hK2; and A non-volatile computer-readable storage medium encoding multiple instructions, which, when executed by a computer processor, perform a method, wherein the method includes: When the value of tPSA is equal to or greater than the threshold, a first logistic regression model is selected from multiple logistic regression models, and when the value of tPSA is lower than the threshold, a second logistic regression model is selected from the multiple logistic regression models. The first logistic regression model includes the coefficients of age and each of tPSA, and the second logistic regression model uses different coefficients for each of multiple variables, including age and at least two variables included in the information received from the at least one detector and selected from the group including fPSA, iPSA and tPSA. Determine whether the chosen logistic regression model includes all or fewer markers; If the selected logistic regression model includes fewer than all markers, the first logistic regression model is used to determine the probability of a positive biopsy for prostate cancer. If the selected logistic regression model includes all markers, the second logistic regression model is used to determine the probability of a positive biopsy for prostate cancer. Specifically, the logarithm is determined by multiplying each variable in the selected logistic regression model by its corresponding coefficient value to produce a calibrated variable, and the values ​​of the calibrated variable are summed to produce the probability of a positive biopsy for prostate cancer; and Outputs an indication of the probability of a positive biopsy for prostate cancer.

30. A method for determining whether a prostate biopsy is worthwhile, the method comprising: Obtain blood samples from the subject; Serum or plasma from the blood sample is subjected to multiplex analysis, which is configured to determine the levels of at least four kallikrein markers: tPSA, fPSA, iPSA, and hK2. When the value of tPSA is equal to or greater than a threshold, a first prediction algorithm is selected from a plurality of prediction algorithms, and when the value of tPSA is lower than the threshold, a second prediction algorithm is selected from the plurality of prediction algorithms. The first prediction algorithm includes a coefficient for each of age and tPSA, and the second prediction algorithm uses a different coefficient for each of a plurality of variables, wherein the plurality of variables includes age and at least two variables selected from the group including fPSA, iPSA and tPSA. Determine whether the selected prediction algorithm includes all or fewer markers; If the selected prediction algorithm includes fewer than all markers, the first prediction algorithm is used to determine the probability of a positive biopsy for prostate cancer. If the selected prediction algorithm includes all markers, the second prediction algorithm is used to determine the probability of a positive biopsy for prostate cancer. The logarithm is determined by multiplying each variable in the selected prediction algorithm by its corresponding coefficient value to produce a calibrated variable, and the values ​​of the calibrated variable are summed; and The logarithm is used to generate the probability of a positive biopsy for prostate cancer in the subject.

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