Microfluidic chip-based rapid detection device for tacrolimus drug concentration

Abstract

The present application relates to the field of drug concentration detection, and particularly relates to a microfluidic chip-based tacrolimus drug concentration rapid detection device. The detection device comprises a blood sampling area, a separation area, a drug solution storage area, a waste liquid storage area and a spectrometer. The separation area is used for separating tacrolimus drugs in a blood sample solution, and obtaining a drug solution sample and a waste liquid sample. The spectrometer is used for collecting drug solution spectrum data of the drug solution sample in the drug solution storage area and waste liquid spectrum data of the waste liquid sample in the waste liquid storage area, and detecting the tacrolimus drug concentration in the blood sample solution according to the drug solution spectrum data and the waste liquid spectrum data. The present application can improve the accuracy of the tacrolimus drug concentration detection in blood.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of drug concentration detection, in particular to a tacrolimus drug concentration rapid detection device based on a microfluidic chip. BACKGROUND

[0002] Microfluidic chip technology is a kind of miniaturized platform based on micron channel and micro processing technology, which realizes the integration and automation of traditional laboratory functions by accurately controlling and analyzing fluid. Its basic principle is to use microfluidic mechanics to control fluid through micro channels, micro valves and micro pumps, to realize functions such as sample separation, mixing, transmission and detection. Tacrolimus is a powerful immunosuppressant, mainly used to prevent rejection after organ transplantation. Its pharmacological effect depends on its combination with plasma proteins to exert immunosuppressive effect.

[0003] In related technologies, the spectral data of blood samples containing tacrolimus drugs is usually collected, and the tacrolimus drug concentration is detected by using the spectral data. However, since tacrolimus drugs can combine with red blood cells and plasma proteins in blood, the combined products will interfere with the collected spectral data, thereby reducing the accuracy of detecting the tacrolimus drug concentration in blood. SUMMARY

[0004] In order to solve the technical problem that the combination of tacrolimus drugs with red blood cells and plasma proteins will interfere with the spectral data, thereby reducing the accuracy of detecting the tacrolimus drug concentration in blood, the purpose of the present application is to provide a tacrolimus drug concentration rapid detection device based on a microfluidic chip, and the technical solution adopted is as follows:

[0005] The present application provides a tacrolimus drug concentration rapid detection device based on a microfluidic chip, which comprises a blood collection area, a separation area, a drug solution storage area, a waste liquid storage area and a spectrometer. The separation area is used to separate tacrolimus drugs in the blood sample solution and obtain drug solution samples and waste liquid samples. The spectrometer is used to collect drug solution spectral data of the drug solution samples in the drug solution storage area and waste liquid spectral data of the waste liquid samples in the waste liquid storage area, and detect the tacrolimus drug concentration in the blood sample solution according to the drug solution spectral data and the waste liquid spectral data. The method for detecting the tacrolimus drug concentration in the blood sample solution comprises the following steps:

[0006] The initial wavelengths are screened according to the difference between the reflection light intensity at the same wavelength of the drug solution spectrum data and the waste liquid spectrum data; the standard reflection light intensity of a plurality of characteristic wavelengths is obtained from the standard spectrum diagram of the tacrolimus drug component, the reference characteristic wavelength of each initial wavelength is obtained according to the distance between each initial wavelength and the characteristic wavelength, the effective degree of each initial wavelength is obtained according to the difference between each initial wavelength and the reference characteristic wavelength and the reflection light intensity of the same initial wavelength of the drug solution spectrum data and the waste liquid spectrum data, and the wavelength to be analyzed is screened from all the initial wavelengths based on the effective degree;

[0007] The relative intensity coefficient of each wavelength to be analyzed in the waste liquid spectrum data is obtained according to the difference between the reflection light intensity of each wavelength to be analyzed in the waste liquid spectrum data and the standard reflection light intensity of the reference characteristic wavelength of each wavelength to be analyzed, and the regression weight of each wavelength to be analyzed in the waste liquid spectrum data is obtained according to the difference between the relative intensity coefficients of the wavelengths to be analyzed in the waste liquid spectrum data and the effective degree of each wavelength to be analyzed.

[0008] The reflection light intensity of each wavelength to be analyzed in the drug solution spectrum data and the waste liquid spectrum data is subjected to weighted regression analysis based on the regression weight of each wavelength to be analyzed in the waste liquid spectrum data, so as to obtain the tacrolimus drug concentration in the blood sample solution.

[0009] Further, the screening of the initial wavelength comprises:

[0010] The absolute value of the difference between the reflection light intensity at the same wavelength of the drug solution spectrum data and the waste liquid spectrum data is subjected to normalization processing, so as to obtain the reflection light intensity difference value between the drug solution spectrum data and the waste liquid spectrum data at each wavelength;

[0011] The wavelength with the reflection light intensity difference value greater than a preset difference threshold value is taken as the initial wavelength.

[0012] Further, the reference characteristic wavelength of each initial wavelength comprises:

[0013] Any one initial wavelength is taken as a target initial wavelength, and the absolute value of the difference between the target initial wavelength and each characteristic wavelength is taken as the distance parameter between the target initial wavelength and each characteristic wavelength;

[0014] The characteristic wavelength corresponding to the minimum value of the distance parameter is taken as the reference characteristic wavelength of the target initial wavelength.

[0015] Further, the effective degree of each initial wavelength comprises:

[0016] The distance parameter between the target initial wavelength and the reference characteristic wavelength is subjected to negative correlation mapping, so as to obtain the first effective coefficient of the target initial wavelength.

[0017] averaging the reflectance intensity of the drug solution spectrum data and the waste liquid spectrum data at the target initial wavelength to obtain a second effective coefficient of the target initial wavelength;

[0018] combining the first effective coefficient and the second effective coefficient and performing normalization processing to obtain an effective degree of the target initial wavelength.

[0019] Further, the screening of the to-be-analyzed wavelengths from all initial wavelengths comprises:

[0020] taking the initial wavelength with an effective degree greater than a preset effective threshold as the to-be-analyzed wavelength.

[0021] Further, the obtaining of the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data comprises:

[0022] taking the reflectance intensity of the waste liquid spectrum data at each to-be-analyzed wavelength as the numerator and the standard reflectance intensity of the reference characteristic wavelength of each to-be-analyzed wavelength as the denominator, and taking the ratio as the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data.

[0023] Further, the obtaining of the regression weight of each to-be-analyzed wavelength in the waste liquid spectrum data comprises:

[0024] taking any one to-be-analyzed wavelength as a target to-be-analyzed wavelength, and obtaining a stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data according to the difference between the relative intensity coefficients between the target to-be-analyzed wavelength and each other to-be-analyzed wavelength except the target to-be-analyzed wavelength in the waste liquid spectrum data;

[0025] combining the stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data and the effective degree of the target to-be-analyzed wavelength and performing normalization processing to obtain the regression weight of the target to-be-analyzed wavelength in the waste liquid spectrum data, wherein the cumulative value of the regression weights of all to-be-analyzed wavelengths in the waste liquid spectrum data is equal to the numerical value 1.

[0026] Further, the obtaining of the stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data comprises:

[0027] taking the absolute value of the difference between the relative intensity coefficients between the target to-be-analyzed wavelength and each other to-be-analyzed wavelength except the target to-be-analyzed wavelength in the waste liquid spectrum data as the relative intensity difference value between the target to-be-analyzed wavelength and each other to-be-analyzed wavelength in the waste liquid spectrum data;

[0028] performing negative correlation mapping on the cumulative value of the relative intensity difference values between the target to-be-analyzed wavelength and all other to-be-analyzed wavelengths in the waste liquid spectrum data to obtain the stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data.

[0029] Further, the obtaining the tacrolimus drug concentration in the blood sample solution comprises:

[0030] The product of the reflection light intensity of the drug solution spectral data at each wavelength to be analyzed and the reflection light intensity of the waste liquid spectral data at each wavelength to be analyzed and the regression weight is input into the weighted regression model, and the tacrolimus drug concentration in the blood sample solution is output by the weighted regression model.

[0031] Further, the detection device further comprises a water electromagnet for separating red blood cells in the blood sample solution and a red blood cell wall breaking region for wall breaking treatment of the red blood cells separated by the water electromagnet.

[0032] The present application has the following beneficial effects:

[0033] The present application considers that the product of the combination of the tacrolimus drug with the red blood cells and the plasma proteins in the blood will interfere with the spectral data, thereby reducing the accuracy of the detection of the tacrolimus drug concentration in the blood, so firstly, the separation region of the detection device is used to separate the tacrolimus drug in the blood sample solution to obtain a drug sample and a waste sample, considering that there may be incomplete separation, so that the two samples contain tacrolimus drugs, in order to improve the accuracy of the detection of the tacrolimus drug concentration in the blood, the present application uses the spectrometer in the detection device to collect spectral data of the drug sample and the waste sample respectively to obtain drug spectral data and waste spectral data, and preliminarily screens out initial wavelengths related to the tacrolimus drug, then the effective degree reflects the degree of the spectral data of the drug spectral data and the waste spectral data at the same initial wavelength, which can represent the tacrolimus drug, and further screens out the wavelengths to be analyzed which can more represent the tacrolimus drug, thereby improving the accuracy of the subsequent drug concentration detection, considering that the content of the tacrolimus drug in the waste sample is less, if the reflection light intensity of the waste spectral data at the wavelength to be analyzed is directly used for regression analysis in the subsequent, the calculation result will be distorted, therefore, the present application calculates the regression weight of the waste spectral data at each wavelength to be analyzed, and performs weighted regression analysis on the reflection light intensity of the drug spectral data and the waste spectral data at each wavelength to be analyzed, so as to accurately calculate the tacrolimus drug concentration in the blood sample solution, thereby improving the accuracy of the detection of the tacrolimus drug concentration in the blood. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, the following will briefly introduce the drawings needed in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Fig. 1 A whole structure diagram of a tacrolimus drug concentration rapid detection device based on a microfluidic chip provided by an embodiment of the present application;

[0036] Fig. 2 A separation area structure diagram in a tacrolimus drug concentration rapid detection device based on a microfluidic chip provided by an embodiment of the present application;

[0037] Fig. 3 A tacrolimus drug concentration rapid detection method flow chart based on a microfluidic chip provided by an embodiment of the present application.

[0038] The drawings are as follows: 1-blood sampling area, 2-water electromagnetic iron, 3-red blood cell wall breaking area, 4-drug solution storage area, 5-waste liquid storage area, 6-catheter, 7-separation area, 8-drug solution outlet, 9-waste liquid outlet. DETAILED DESCRIPTION

[0039] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined purposes, the following will combine the drawings and the preferred embodiments to specifically describe a tacrolimus drug concentration rapid detection device based on a microfluidic chip according to the present application, the specific implementation, structure, features and effects thereof, in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0041] The following will specifically describe the specific scheme of the tacrolimus drug concentration rapid detection device based on a microfluidic chip provided by the present application in combination with the drawings.

[0042] Please refer to Figs. 1-2respectively show the overall structure diagram of a microfluidic chip-based tacrolimus drug concentration rapid detection device and the separation region structure diagram provided by an embodiment of the application. The blood sample solution collected from a patient is first placed in the blood collection region 1. The liquid sample solution in the blood collection region 1 flows along the conduit 6. Since the tacrolimus drug is combined with the red blood cells and plasma proteins in the blood, the combined product will interfere with the collected spectral data. During the flow process, the red blood cells in the blood sample solution are first separated by using the magnetic field generated by the water electromagnet 2. The separated red blood cells enter the red blood cell wall breaking region 3. In the red blood cell wall breaking region 3, the red blood cell wall can be broken by, for example, chemical drug surfactant Triton X-100. Then the blood sample solution carrying the broken red blood cells enters the separation region 7. Since the tacrolimus drug is hydrophobic, in the separation region 7, the tacrolimus drug is separated from the red blood cells and plasma proteins in the blood by using a solvent that is not soluble in water but can dissolve the tacrolimus drug, such as ethyl oleate solvent. Thus, the liquid sample and the waste liquid sample are obtained. The liquid sample passes through the liquid outlet 8 to the liquid storage region 4, and the waste liquid sample passes through the waste liquid outlet 9 to the waste liquid storage region 5. Then the liquid spectral data of the liquid sample in the liquid storage region 4 and the waste liquid spectral data of the waste liquid sample in the waste liquid storage region 5 are collected by using a spectrometer, and the tacrolimus drug concentration in the blood sample solution is detected according to the liquid spectral data and the waste liquid spectral data. In an embodiment of the application, Raman spectroscopy is selected for tacrolimus drug concentration analysis, which is not limited herein.

[0043] Please refer to Fig. 3 which shows a microfluidic chip-based tacrolimus drug concentration rapid detection method flowchart provided by an embodiment of the application, including:

[0044] Step S1: According to the difference in the reflected light intensity at the same wavelength between the liquid spectral data and the waste liquid spectral data, an initial wavelength is selected. The standard reflected light intensity of a plurality of characteristic wavelengths is obtained from the standard spectrum diagram of the tacrolimus drug component. According to the distance between each initial wavelength and the reference characteristic wavelength, the reference characteristic wavelength of each initial wavelength is obtained. According to the difference between each initial wavelength and the reference characteristic wavelength, and the reflected light intensity at the same initial wavelength between the liquid spectral data and the waste liquid spectral data, the effective degree of each initial wavelength is obtained. Based on the effective degree, the to-be-analyzed wavelength is selected from all the initial wavelengths.

[0045] Because the above operation involves incomplete separation of tacrolimus from the blood sample solution, the drug solution sample contains a large amount of tacrolimus and a small amount of impurities, while the waste liquid sample contains a small amount of tacrolimus and a large amount of impurities. The impurities refer to components such as plasma proteins, hemoglobin, and albumin in the blood. Therefore, for the wavelength representing the tacrolimus drug components, the reflected light intensity at the same wavelength differs significantly between the drug solution spectral data and the waste liquid spectral data. Therefore, in this embodiment of the invention, the initial wavelength representing the tacrolimus drug components is initially screened based on the difference in reflected light intensity at the same wavelength between the drug solution spectral data and the waste liquid spectral data.

[0046] Preferably, in one embodiment of the present invention, the method for obtaining the initial wavelength specifically includes:

[0047] The absolute values ​​of the differences in reflected light intensity at the same wavelength between the spectral data of the pharmaceutical solution and the spectral data of the waste liquid are normalized, and the calculation results are limited to [a certain range]. Within this range, the difference in reflected light intensity at each wavelength between the spectral data of the drug solution and the spectral data of the waste liquid is obtained.

[0048] In one embodiment of the present invention, the normalization process can be specifically, for example, maximum and minimum value normalization. Furthermore, the normalization in subsequent steps can all adopt maximum and minimum value normalization. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of the numerical values, which will not be elaborated further.

[0049] As an example, in one embodiment of the present invention, the expression for the difference in reflected light intensity at each wavelength between the drug liquid spectral data and the waste liquid spectral data can be specifically, for example, as follows:

[0050]

[0051] in, This indicates the relationship between the drug liquid spectral data and the waste liquid spectral data at the 1st... The difference in reflected light intensity at each wavelength; Indicates the spectral data of the drug solution in the first... The intensity of reflected light at each wavelength; Indicates the waste liquid spectral data in the first... The intensity of reflected light at each wavelength; This represents the normalization function, used for normalization processing.

[0052] The greater the difference value of the reflected light intensity of a certain wavelength, the greater the difference in the content of the same component represented by the drug sample and the waste sample at the wavelength, and the more likely the wavelength to represent the tacrolimus drug component. Therefore, the wavelength with a reflected light intensity difference value greater than a preset difference threshold value can be used as an initial wavelength, wherein the preset difference threshold value is in the range of In an embodiment of the present application, the preset difference threshold value is set to 0.6. The specific value of the preset difference threshold value can also be set by the implementer according to the specific implementation scenario, which is not limited herein.

[0053] Since not only the tacrolimus drug content but also the impurity content between the drug sample and the waste sample is large, the obtained initial wavelengths not only contain wavelengths representing the tacrolimus drug component, but also contain wavelengths representing impurity components. Therefore, the embodiment of the present application first obtains the standard reflected light intensity of a plurality of characteristic wavelengths from the standard spectrum of the tacrolimus drug component, wherein the standard spectrum of the tacrolimus drug component can be obtained from a database. The characteristic wavelengths of the tacrolimus drug component and the standard reflected light intensity of each characteristic wavelength are known data. For example, 1557 , 1648 and 1342 , etc. are characteristic wavelengths of the tacrolimus drug component.

[0054] Since the drug sample and the waste sample both contain impurities, which will cause certain interference to the corresponding spectrum data, such as the shift of the characteristic peak, etc., the embodiment of the present application first obtains the reference characteristic wavelength of each initial wavelength according to the distance between each initial wavelength and the characteristic wavelength. Subsequently, based on the difference between the initial wavelength and the reference characteristic wavelength, the wavelength that can more represent the tacrolimus drug component can be further screened, and the accuracy of the subsequent concentration detection can be improved.

[0055] Preferably, in an embodiment of the present application, the method for obtaining the reference characteristic wavelength of each initial wavelength specifically comprises:

[0056] Taking any one initial wavelength as a target initial wavelength, taking the absolute value of the difference between the target initial wavelength and each characteristic wavelength as the distance parameter between the target initial wavelength and each characteristic wavelength. The smaller the distance parameter between the target initial wavelength and a certain characteristic wavelength, the closer the distance between them, and the greater the reference value of the characteristic wavelength to the target initial wavelength. Therefore, the characteristic wavelength corresponding to the minimum distance parameter can be used as the reference characteristic wavelength of the target initial wavelength.

[0057] The reference characteristic wavelength of each initial wavelength can be obtained by the same method as described above.

[0058] The smaller the difference between the initial wavelength and the corresponding reference characteristic wavelength, and the greater the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at the initial wavelength, the more likely the initial wavelength represents the wavelength of the tacrolimus drug component rather than the wavelength of the impurity component. Therefore, the effective degree of each initial wavelength can be obtained according to the difference between each initial wavelength and the reference characteristic wavelength, and the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at the same initial wavelength. Subsequently, the to-be-analyzed wavelength representing the tacrolimus drug component can be further screened based on the effective degree.

[0059] Preferably, in an embodiment of the present application, the method for obtaining the effective degree of each initial wavelength specifically comprises:

[0060] The distance parameter between the target initial wavelength and the reference characteristic wavelength is negatively correlated to obtain a first effective coefficient of the target initial wavelength, and the average value of the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at the target initial wavelength is taken as a second effective coefficient of the target initial wavelength.

[0061] Further, the first effective coefficient and the second effective coefficient are integrated and normalized to limit the calculation result in the range of 0 to 1, so as to obtain the effective degree of the target initial wavelength.

[0062] In an embodiment of the present application, the integration of the first effective coefficient and the second effective coefficient can be realized by calculating the sum or product value of the two, which is not limited herein.

[0063] As an example, in an embodiment of the present application, the expression of the effective degree of the target initial wavelength can be specifically as follows:

[0064]

[0065] wherein, represents the effective degree of the target initial wavelength; represents the distance parameter between the target initial wavelength and the corresponding reference characteristic wavelength; represents the first effective coefficient of the target initial wavelength; represents the reflection light intensity of the drug solution spectrum data at the target initial wavelength; represents the reflection light intensity of the waste liquid spectrum data at the target initial wavelength; represents the second effective coefficient of the target initial wavelength; represents a normalization function for normalization processing; represents a preset first adjustment parameter for preventing the denominator from being 0, the value range of the first adjustment parameter is 0 to 1, in an embodiment of the present application, the first adjustment parameter is 0.5. ​is set to 0.01, The specific value of the preset effective threshold can also be set by the implementer according to the specific implementation scenario, and is not limited herein.

[0066] It should be noted that in other embodiments of the present application, negative correlation mapping can also be achieved through other basic mathematical operations, which are not described herein.

[0067] The effective degree of each initial wavelength can be obtained by the same method as described above. The greater the effective degree of a certain initial wavelength, the more likely it is that the initial wavelength represents the wavelength of the tacrolimus drug component in the drug solution spectrum data and the waste liquid spectrum data. Therefore, the to-be-analyzed wavelength can be selected from all initial wavelengths based on the effective degree.

[0068] Preferably, in an embodiment of the present application, the initial wavelength with an effective degree greater than a preset effective threshold can be used as the to-be-analyzed wavelength, wherein the preset effective threshold has a value range of 0.5 to 1. In an embodiment of the present application, the preset effective threshold is set to 0.8, and the specific value of the preset effective threshold can also be set by the implementer according to the specific implementation scenario, and is not limited herein.

[0069] Step S2: obtaining a relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data according to the difference between the reflection intensity of each to-be-analyzed wavelength in the waste liquid spectrum data and the standard reflection intensity of the reference characteristic wavelength of each to-be-analyzed wavelength; and obtaining a regression weight of the waste liquid spectrum data at each to-be-analyzed wavelength according to the difference between the relative intensity coefficients of the to-be-analyzed wavelengths in the waste liquid spectrum data and the effective degree of each to-be-analyzed wavelength.

[0070] Compared with the drug sample, the waste sample contains a large amount of impurities, and the characteristic peaks formed by these impurities in the waste liquid spectrum data can overlap with the characteristic peaks of the tacrolimus drug, thereby masking the tacrolimus drug information in the waste liquid spectrum data and causing serious information interference. Therefore, if the reflection intensity of the to-be-analyzed wavelength in the waste liquid spectrum data is directly used for regression analysis in the subsequent process, the calculation result will be distorted. Therefore, in the embodiment of the present application, the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data is first obtained according to the difference between the reflection intensity of each to-be-analyzed wavelength in the waste liquid spectrum data and the standard reflection intensity of the reference characteristic wavelength of each to-be-analyzed wavelength. Subsequently, the degree of interference on the waste liquid spectrum data at each to-be-analyzed wavelength can be accurately analyzed based on the difference between the relative intensity coefficients of the to-be-analyzed wavelengths in the waste liquid spectrum data, thereby improving the accuracy of the tacrolimus drug concentration detection.

[0071] Preferably, in an embodiment of the present application, the method for obtaining the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data specifically comprises:

[0072] The relative intensity coefficient of each analysis wavelength in the waste liquid spectrum data is obtained by taking the reflected light intensity of each analysis wavelength in the waste liquid spectrum data as the numerator and taking the standard reflected light intensity of the reference characteristic wavelength of each analysis wavelength as the denominator.

[0073] As an example, in an embodiment of the present application, the expression of the relative intensity coefficient of each analysis wavelength in the waste liquid spectrum data can be specifically as follows:

[0074]

[0075] wherein, represents the relative intensity coefficient of the i-th analysis wavelength in the waste liquid spectrum data; represents the reflected light intensity of the i-th analysis wavelength in the waste liquid spectrum data; represents the reference characteristic wavelength of the i-th analysis wavelength.

[0076] The smaller the difference between the relative intensity coefficient of a certain analysis wavelength and other analysis wavelengths in the waste liquid spectrum data, the smaller the interference degree of the waste liquid spectrum data at the analysis wavelength, and the greater the reference value of the reflected light intensity of the analysis wavelength in the subsequent regression analysis. At the same time, the greater the effective degree of the analysis wavelength, the greater the reference value of the reflected light intensity of the analysis wavelength in the waste liquid spectrum data. Therefore, the regression weight of each analysis wavelength in the waste liquid spectrum data can be obtained according to the difference between the relative intensity coefficients of the analysis wavelengths in the waste liquid spectrum data and the effective degree of each analysis wavelength.

[0077] Preferably, in an embodiment of the present application, the method for obtaining the regression weight of each analysis wavelength in the waste liquid spectrum data specifically comprises:

[0078] Taking any one analysis wavelength as the target analysis wavelength, the stability coefficient of the target analysis wavelength in the waste liquid spectrum data is obtained according to the difference between the relative intensity coefficients of the target analysis wavelength and each other analysis wavelength except the target analysis wavelength in the waste liquid spectrum data. The greater the stability coefficient, the smaller the interference degree of the waste liquid spectrum data at the target analysis wavelength.

[0079] Preferably, in an embodiment of the present application, the method for obtaining the stability coefficient of the target analysis wavelength in the waste liquid spectrum data specifically comprises:

[0080] ​​​First, the absolute value of the difference between the relative intensity coefficients between the target wavelength and each other wavelength in the waste liquid spectral data is used as the relative intensity difference value between the target wavelength and each other wavelength in the waste liquid spectral data. Then, a negative correlation mapping is performed on the cumulative value of the relative intensity difference values ​​between the target wavelength and all other wavelengths in the waste liquid spectral data to obtain the stability coefficient of the waste liquid spectral data at the target wavelength.

[0081] As an example, in one embodiment of the present invention, the expression for the stability coefficient of the waste liquid spectral data at the target wavelength to be analyzed can be specifically as follows:

[0082]

[0083] in, This indicates the stability coefficient of the waste liquid spectral data at the target wavelength to be analyzed; This represents the relative intensity coefficient of the target wavelength to be analyzed in the spectral data of the waste liquid; This indicates the first wavelength in the waste liquid spectral data, excluding the target wavelength to be analyzed. The relative intensity coefficients of other wavelengths to be analyzed; This indicates the target wavelength to be analyzed and the first wavelength in the waste liquid spectral data. The relative intensity difference between the other wavelengths to be analyzed; The range of values ​​is In one embodiment of the present invention, the following is used: Set to 0.01, The specific value can also be set by the implementer according to the specific implementation scenario, and is not limited here. M represents the total number of other wavelengths to be analyzed besides the target wavelength.

[0084] It should be noted that negative correlation mapping can also be achieved through other basic mathematical operations in other embodiments of the present invention, which will not be elaborated here.

[0085] Then, the stability coefficient and effectiveness of the waste liquid spectral data at the target wavelength are combined and normalized to obtain the regression weight of the waste liquid spectral data at the target wavelength. The cumulative value of the regression weight of the waste liquid spectral data at all wavelengths is equal to the value 1.

[0086] In embodiments of the present invention, the combination of the two can be achieved by calculating the sum or product of the stability coefficient of the waste liquid spectral data at the target wavelength to be analyzed and the effectiveness of the target wavelength to be analyzed, without limitation.

[0087] As an example, in an embodiment of the present application, the expression of the regression weight of the waste liquid spectrum data at the target wavelength to be analyzed can be specifically as follows:

[0088]

[0089] wherein, represents the regression weight of the waste liquid spectrum data at the target wavelength to be analyzed; represents the stability coefficient of the waste liquid spectrum data at the target wavelength to be analyzed; represents the effective degree of the target wavelength to be analyzed; represents the stability coefficient of the waste liquid spectrum data at the target wavelength to be analyzed; represents the effective degree of the target wavelength to be analyzed; represents the effective degree of the target wavelength to be analyzed; represents the number of all wavelengths to be analyzed.

[0090] wherein, is used for normalization processing, so that the cumulative value of the regression weight of the waste liquid spectrum data at all wavelengths to be analyzed is equal to the numerical value 1. The regression weight of the waste liquid spectrum data at each wavelength to be analyzed can be obtained by the same method as described above.

[0091] Step S3: based on the regression weight of the waste liquid spectrum data at each wavelength to be analyzed, weighted regression analysis is performed on the reflectance intensity of the drug liquid spectrum data and the waste liquid spectrum data at each wavelength to be analyzed, to obtain the tacrolimus drug concentration in the blood sample solution.

[0092] The regression weight of the waste liquid spectrum data at each wavelength to be analyzed is obtained through the above process, and the greater the regression weight of the waste liquid spectrum data at a certain wavelength to be analyzed, the greater the reference value of the reflectance intensity of the waste liquid spectrum data at the wavelength to be analyzed in the regression analysis. At the same time, since the impurity content in the drug liquid sample is less, the interference of the drug liquid spectrum data by the impurity is weak, and therefore the reflectance intensity of the drug liquid spectrum data at each wavelength to be analyzed can be directly used for regression analysis. Therefore, based on the regression weight of the waste liquid spectrum data at each wavelength to be analyzed, weighted regression analysis can be performed on the reflectance intensity of the drug liquid spectrum data and the waste liquid spectrum data at each wavelength to be analyzed, to obtain the tacrolimus drug concentration in the blood sample solution, thereby improving the accuracy of the detection of the tacrolimus drug concentration in the blood sample solution.

[0093] Preferably, in an embodiment of the present application, the method for obtaining the tacrolimus drug concentration in the blood sample solution specifically comprises:

[0094]

[0095] ​​Since the interference of the drug solution spectrum data at each wavelength to be analyzed is relatively weak, the regression weight of the drug solution spectrum data at each wavelength to be analyzed can be regarded as a numerical value 1. Therefore, the reflected light intensity of the drug solution spectrum data at each wavelength to be analyzed, and the product value of the reflected light intensity of the waste liquid spectrum data at each wavelength to be analyzed and the regression weight are input into the weighted regression model. The tacrolimus drug concentration in the blood sample solution is output through the weighted regression model. The weighted regression model can be obtained through the spectrum data of the tacrolimus drug solution with a known concentration, and will not be described here.

[0096] It should be noted that the above-mentioned embodiment sequence of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0097] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the difference from other embodiments.

Claims

1. A microfluidic chip-based device for rapid detection of tacrolimus drug concentration, characterized in that, The detection device comprises a blood sampling area, a separation area, a drug solution storage area, a waste liquid storage area and a spectrometer, the separation area is used for separating the tacrolimus drug in the blood sample solution, and obtaining a drug solution sample and a waste liquid sample, the spectrometer is used for collecting drug solution spectrum data of the drug solution sample in the drug solution storage area and waste liquid spectrum data of the waste liquid sample in the waste liquid storage area, and detecting the tacrolimus drug concentration in the blood sample solution according to the drug solution spectrum data and the waste liquid spectrum data, wherein the method for detecting the tacrolimus drug concentration in the blood sample solution comprises: According to the difference between the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at the same wavelength, an initial wavelength is screened out; the standard reflection light intensity of a plurality of characteristic wavelengths is obtained from the standard spectrum diagram of the tacrolimus drug component, the reference characteristic wavelength of each initial wavelength is obtained according to the distance between each initial wavelength and the characteristic wavelength; the effective degree of each initial wavelength is obtained according to the difference between each initial wavelength and the reference characteristic wavelength, and the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at the same initial wavelength; based on the effective degree, the to-be-analyzed wavelength is screened out from all the initial wavelengths; According to the difference between the reflection light intensity of the waste liquid spectrum data at each to-be-analyzed wavelength and the standard reflection light intensity of the reference characteristic wavelength of each to-be-analyzed wavelength, the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data is obtained; according to the difference between the relative intensity coefficients of the to-be-analyzed wavelengths in the waste liquid spectrum data and the effective degree of each to-be-analyzed wavelength, the regression weight of the waste liquid spectrum data at each to-be-analyzed wavelength is obtained; Based on the regression weight of the waste liquid spectrum data at each to-be-analyzed wavelength, the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at each to-be-analyzed wavelength is subjected to weighted regression analysis, and the tacrolimus drug concentration in the blood sample solution is obtained; The regression weight of the waste liquid spectrum data at each to-be-analyzed wavelength comprises: Taking any one to-be-analyzed wavelength as a target to-be-analyzed wavelength, according to the difference between the relative intensity coefficients of the target to-be-analyzed wavelength and each other to-be-analyzed wavelength except the target to-be-analyzed wavelength in the waste liquid spectrum data, the stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data is obtained; The stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data and the effective degree of the target to-be-analyzed wavelength are comprehensively processed and normalized to obtain the regression weight of the target to-be-analyzed wavelength in the waste liquid spectrum data, wherein the cumulative value of the regression weights of the waste liquid spectrum data at all to-be-analyzed wavelengths is equal to the numerical value 1.

2. The rapid detection device for tacrolimus concentration based on microfluidic chip according to claim 1, characterized in that, The screening out of the initial wavelength comprises: The absolute value of the difference between the reflection light intensity of the drug solution spectrum data and the waste liquid spectrum data at the same wavelength is normalized to obtain the reflection light intensity difference value between the drug solution spectrum data and the waste liquid spectrum data at each wavelength; The wavelength with the reflection light intensity difference value greater than the preset difference threshold value is taken as the initial wavelength.

3. The microfluidic chip-based device for rapid detection of tacrolimus drug concentration according to claim 1, characterized in that, The reference characteristic wavelength of each initial wavelength comprises: Taking any one initial wavelength as a target initial wavelength, taking an absolute value of a difference between the target initial wavelength and each characteristic wavelength as a distance parameter between the target initial wavelength and each characteristic wavelength; Taking a characteristic wavelength corresponding to a minimum value of the distance parameter as a reference characteristic wavelength of the target initial wavelength.

4. The rapid detection device for tacrolimus concentration based on microfluidic chip according to claim 3, characterized in that, The obtaining of the effective degree of each initial wavelength comprises: performing negative correlation mapping on the distance parameter between the target initial wavelength and the reference characteristic wavelength to obtain a first effective coefficient of the target initial wavelength; taking an average value of the reflected light intensity of the drug solution spectrum data and the waste liquid spectrum data at the target initial wavelength as a second effective coefficient of the target initial wavelength; performing comprehensive processing on the first effective coefficient and the second effective coefficient and performing normalization processing to obtain the effective degree of the target initial wavelength.

5. The rapid detection device for tacrolimus concentration based on microfluidic chip according to claim 1, characterized in that, The screening of the to-be-analyzed wavelengths from all the initial wavelengths comprises: taking an initial wavelength with an effective degree greater than a preset effective threshold as a to-be-analyzed wavelength.

6. The rapid detection device for tacrolimus concentration based on microfluidic chip according to claim 1, characterized in that, The obtaining of the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data comprises: taking a reflected light intensity of the waste liquid spectrum data at each to-be-analyzed wavelength as a numerator and taking a standard reflected light intensity of the reference characteristic wavelength of each to-be-analyzed wavelength as a denominator, and taking a ratio as the relative intensity coefficient of each to-be-analyzed wavelength in the waste liquid spectrum data.

7. The microfluidic chip-based device for rapid detection of tacrolimus drug concentration according to claim 1, characterized in that, The obtaining of the stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data comprises: taking an absolute value of a difference between the relative intensity coefficient of the target to-be-analyzed wavelength and the relative intensity coefficient of each other to-be-analyzed wavelength except the target to-be-analyzed wavelength as a relative intensity difference value between the target to-be-analyzed wavelength and each other to-be-analyzed wavelength in the waste liquid spectrum data; performing negative correlation mapping on an accumulated value of the relative intensity difference values between the target to-be-analyzed wavelength and all the other to-be-analyzed wavelengths in the waste liquid spectrum data to obtain the stability coefficient of the target to-be-analyzed wavelength in the waste liquid spectrum data.

8. The microfluidic chip-based device for rapid detection of tacrolimus drug concentration according to claim 1, characterized in that, The obtaining of the tacrolimus drug concentration in the blood sample solution comprises: inputting a product value of the reflected light intensity of each to-be-analyzed wavelength of the drug solution spectrum data and the reflected light intensity of each to-be-analyzed wavelength of the waste liquid spectrum data and the regression weight into a weighted regression model, and outputting the tacrolimus drug concentration in the blood sample solution by the weighted regression model.

9. The microfluidic chip-based device for rapid detection of tacrolimus drug concentration according to claim 1, characterized in that, The detection device further comprises a water electromagnetic magnet and a red blood cell wall breaking region, the water electromagnetic magnet is used for separating red blood cells in the blood sample solution, and the red blood cell wall breaking region is used for wall breaking processing on the red blood cells separated by the water electromagnetic magnet.

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