High performance liquid chromatography system of clinical mass spectrum

Abstract

The invention relates to the technical field of clinical mass spectrometry, in particular to a high performance liquid chromatography system of clinical mass spectrometry, which comprises a sample processing module, a sample distribution module, a separation effect prediction module, a mass spectrometry detection module and a data analysis module, the sample processing module is used for processing a sample to be analyzed; the sample distribution module automatically adjusts the sample injection amount and the sample injection mode; the separation effect prediction module is used for analyzing a plurality of operation parameter data from a chromatographic system in real time, predicting a chromatographic separation effect and adjusting chromatographic separation conditions in combination with the properties of a sample and separation requirements; the mass spectrum detection module is used for acquiring mass information of a sample in real time; the data analysis module is used for analyzing the relative relationship between the sample and the coexisting substance and generating a final quantitative result; according to the invention, the maximization of the separation effect is ensured, the sample separation accuracy and the analysis depth are improved, and the requirement on efficient separation in clinical diagnosis is met.

Description

Technical Field

[0001] The present invention relates to the technical field of clinical mass spectrometry, in particular to a high performance liquid chromatography system of clinical mass spectrometry. Background Art

[0002] In clinical diagnosis, accurate and rapid analysis of multi-component substances in biological samples is crucial. High performance liquid chromatography (HPLC) combined with mass spectrometry (MS) technology has been widely used in the field of clinical analysis, especially in drug testing, metabolite analysis and identification of pathological biomarkers. High performance liquid chromatography technology can effectively analyze target molecules in complex samples by separating samples in the chromatographic column and combining the high sensitivity and high resolution of mass spectrometry. With the increase in clinical diagnostic needs, the complexity and diversity of analytical samples are also showing an upward trend, which puts higher requirements on separation efficiency, analysis accuracy and operational stability.

[0003] Although the existing liquid chromatography-mass spectrometry (LC-MS) technology has been widely used in clinical analysis, it still faces some technical bottlenecks. First, the traditional sample processing and distribution process mostly relies on manual operation or traditional fixation methods, and there are problems of sample overload or uneven distribution, which affects the separation effect and subsequent analysis accuracy. Secondly, the prediction and condition adjustment of chromatographic separation effects in existing technologies mostly rely on experience or manual intervention, and it is impossible to optimize the separation parameters in real time according to the actual analysis conditions and sample properties, resulting in low separation efficiency and unsatisfactory resolution. Finally, in the data analysis stage, the relative relationship between samples and coexisting substances such as impurities and metabolites is complex. Existing methods are often unable to efficiently distinguish the interference between target molecules and other components, which in turn affects the accuracy and reliability of quantitative analysis.

[0004] In view of the deficiencies in the prior art, the object of the present invention is to provide a high performance liquid chromatography system for clinical mass spectrometry, which improves sample separation efficiency, optimizes data analysis accuracy, and enhances system stability to meet the needs of modern clinical diagnosis for high-precision quantitative analysis. Summary of the invention

[0005] The present invention provides a high performance liquid chromatography system for clinical mass spectrometry.

[0006] A high performance liquid chromatography system for clinical mass spectrometry includes a sample processing module, a sample distribution module, a separation effect prediction module, a mass spectrometry detection module and a data analysis module, wherein; The sample processing module processes the sample to be analyzed and removes impurities in the sample; The sample distribution module automatically adjusts the injection volume and injection mode according to the nature and concentration of the sample and matches it with the processing capacity of the chromatographic column; The separation effect prediction module uses multimodal data fusion technology to analyze multiple operating parameter data from the chromatographic system in real time, including flow rate, temperature, and pressure, to predict the chromatographic separation effect, and based on the predicted results of the chromatographic separation effect, adjust the chromatographic separation conditions in combination with the properties of the sample and the separation requirements, including the composition of the mobile phase, gradient change, and temperature setting; The mass spectrometry detection module detects the separated sample components based on the adjusted chromatographic separation conditions and obtains the quality information of the sample in real time; The data analysis module analyzes the relative relationship between the sample and coexisting substances (impurities or metabolites) based on the acquired mass information of the sample, and generates a final quantitative result.

[0007] Optionally, the sample processing module includes: Sample pretreatment: Pre-treat the sample to be analyzed by removing large particle impurities, suspended matter and insoluble matter in the sample by centrifugation; Impurity removal: Remove dissolved impurities and tiny particles in the sample by selective ultrafiltration.

[0008] Optionally, the sample distribution module includes: Injection volume adjustment: Automatically adjust the injection volume according to the properties of the sample to be analyzed (viscosity, solubility, complexity of components) and concentration; Injection mode control: According to the processing capacity of the chromatographic column, the injection mode is automatically selected, including manual injection, automatic injection, and online injection.

[0009] Optionally, the injection volume adjustment includes: Sample property analysis: Viscosity of the sample is measured by a viscometer sensor, solubility is measured by a refractive index sensor, and the spectral response of the sample is analyzed by a multispectral sensor to evaluate its compositional complexity (diversity of ingredients); Sample concentration calculation: Using the sample concentration and the standard requirements of chromatographic analysis, combined with the properties of the sample (viscosity , solubility , ingredient complexity ), calculate the injection volume ; Injection volume adjustment: calculated injection volume , adjust the injection volume of the injection system or pump.

[0010] Optionally, the injection mode control includes: Chromatographic column processing capacity evaluation: by real-time monitoring of the working status of the chromatographic column (pressure, flow rate, temperature), the processing capacity of the chromatographic column is evaluated and the current load capacity of the chromatographic column is calculated. ; Injection method selection: by the current loading capacity of the column With load threshold lower limit and upper load threshold Compare and automatically select the injection method. When you select manual injection, When you select automatic injection, , select Online Injection.

[0011] Optionally, the separation effect prediction module includes: Multimodal data fusion: real-time acquisition of operating parameters in the chromatography system, including flow rate, temperature and pressure, and integration of the operating parameters into comprehensive parameters using multimodal data fusion technology; Prediction of separation effect and adjustment of conditions: Based on the integrated parameters after fusion, the chromatographic separation effect is predicted in real time. According to the prediction results, combined with the properties of the sample (viscosity, solubility, component complexity) and separation requirements, the chromatographic separation conditions (mobile phase composition, gradient change and temperature setting) are automatically adjusted to optimize the separation process.

[0012] Optionally, the multimodal data fusion includes: Operation parameter acquisition: real-time acquisition of flow rate, temperature and pressure in the chromatography system through sensors; Data fusion: Use weighted algorithms to fuse the collected operating parameters into comprehensive parameters .

[0013] Optionally, the separation effect prediction and condition adjustment include: Separation effect prediction: using integrated parameters after fusion The properties of the sample (viscosity, solubility, composition complexity) are input into the linear regression model to predict the chromatographic separation effect in real time. ; Optimizing separation conditions: Predicting results based on separation performance , combined with the sample properties, the chromatographic separation conditions are adjusted using an optimization algorithm to maximize the separation effect.

[0014] Optionally, the mass spectrometry detection module includes: Mass spectrometry analysis: According to the adjusted chromatographic separation conditions, the sample components after chromatographic separation are received in real time, and the separated sample components are detected by mass spectrometry analysis technology; Mass spectrometry data acquisition: Based on the detection results of mass spectrometry analysis technology, the mass information of the sample components is collected in real time, including the mass and concentration of the target molecule and the mass and concentration of the internal standard substance.

[0015] Optionally, the data analysis module includes: Analyze the relative relationship between the sample and coexisting substances: Based on the mass spectrometry data and the mass and concentration of coexisting substances (impurities or metabolites) in the sample, use the peak area ratio method to analyze the relative concentration and mass ratio between the target molecule and the coexisting substances; Calculate quantitative results: By analyzing the mass ratio and concentration ratio between the target molecule and the coexisting substances, interference is removed and the final quantitative results are optimized.

[0016] Beneficial effects of the present invention: The present invention realizes efficient and accurate sample analysis by integrating sample processing, sample distribution, separation effect prediction, mass spectrometry detection and data analysis modules. By adjusting the separation conditions in real time and optimizing the chromatographic operating parameters, the system can accurately control the chromatographic separation process, thereby significantly improving the separation efficiency and resolution. Combined with multimodal data fusion technology, the separation effect prediction module can analyze the operating parameter data in real time, and dynamically optimize the separation conditions according to the properties of the sample and the separation requirements, ensuring the maximization of the separation effect, improving the accuracy of sample separation and the depth of analysis, and meeting the needs for efficient separation in clinical diagnosis.

[0017] The present invention can accurately obtain the mass information of the sample through the mass spectrometry detection module, and generate the final quantitative result by analyzing the relative relationship between the sample and the coexisting substances in the data analysis module. Through the comprehensive collection and analysis of the sample quality information, the concentration of the target molecule can be accurately evaluated, and the interference of the coexisting substances on the analysis result can be removed, which significantly improves the accuracy and reliability of the data, avoids the interference caused by the complexity of the sample components or the presence of impurities, ensures that the final quantitative analysis result has a high degree of credibility, and adapts to the actual needs of complex sample analysis.

[0018] The present invention realizes automatic injection volume adjustment based on sample properties and concentrations through a sample distribution module, and automatically selects a suitable injection mode according to the processing capacity of a chromatographic column to ensure uniform sample distribution and stable injection. The injection volume can be accurately controlled according to the viscosity, solubility and component complexity of the sample to be analyzed to avoid overload or underload, thereby optimizing the distribution and separation effect of the sample in the chromatographic column. The combination of automatic injection volume adjustment and injection mode control improves the system's adaptability and operational stability, effectively reduces errors caused by human operation, and provides reliable data support for clinical diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A schematic diagram of system function modules according to an embodiment of the present invention; Figure 2 Schematic diagram of a separation effect prediction module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0022] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0023] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0024] like Figure 1-Figure 2 As shown, the high performance liquid chromatography system of clinical mass spectrometry includes a sample processing module, a sample distribution module, a separation effect prediction module, a mass spectrometry detection module and a data analysis module, wherein; The sample processing module processes the sample to be analyzed and removes impurities in the sample; The sample distribution module automatically adjusts the injection volume and injection method according to the nature and concentration of the sample and matches it with the processing capacity of the chromatographic column to ensure uniform sample distribution, improve separation effect and avoid sample overload; The separation effect prediction module uses multimodal data fusion technology to analyze multiple operating parameter data from the chromatographic system in real time, including flow rate, temperature, and pressure, to predict the chromatographic separation effect. Based on the predicted results of the chromatographic separation effect, the chromatographic separation conditions are adjusted in combination with the properties of the sample and the separation requirements, including the composition of the mobile phase, gradient changes, and temperature settings, to improve the separation efficiency and resolution. The mass spectrometry detection module detects the separated sample components based on the adjusted chromatographic separation conditions and obtains the sample quality information in real time; The data analysis module analyzes the relative relationship between the sample and coexisting substances (impurities or metabolites) based on the acquired sample quality information and generates the final quantitative results; Through the above content, efficient and accurate sample analysis can be achieved. By adjusting the separation conditions and optimizing the operating parameters in real time, the separation efficiency and resolution are improved, ensuring the accuracy and reliability of the analysis results. In addition, the system can effectively respond to the multi-component analysis needs of complex samples, improve the data quality in clinical diagnosis, and provide strong technical support for accurate quantitative analysis.

[0025] The sample processing module includes: Sample pretreatment: Pre-treat the sample to be analyzed by removing large particle impurities, suspended matter and insoluble matter in the sample by centrifugation; Impurity removal: Remove dissolved impurities and tiny particles in the sample by selective ultrafiltration to ensure the purity of the sample; Through the above, large particle impurities, suspended matter and insoluble substances in the sample are effectively removed to ensure that the sample reaches a high degree of purity before entering the subsequent analysis stage. In addition, ultrafiltration is used to further improve the purity of the sample and optimize its stability and adaptability in chromatographic analysis, thereby improving the accuracy and reliability of the analysis and ensuring the accuracy and repeatability of the final data.

[0026] The sample distribution module includes: Injection volume adjustment: According to the properties of the sample to be analyzed (viscosity, solubility, and complexity of components) and concentration, the injection volume is automatically adjusted to ensure that the sample injection volume is in the optimal range to avoid sample overload or underload and ensure stability and separation effect during the analysis process; Injection mode control: According to the processing capacity of the chromatographic column, the injection mode is automatically selected, including manual injection, automatic injection, and online injection, to ensure uniform distribution of samples and avoid sample overload or uneven distribution, thereby improving separation effect and analysis accuracy; Through the above content, accurate sample distribution can be achieved according to the different properties of the samples and the processing capacity of the chromatographic column. The automatic adjustment of the injection volume ensures that the sample will not be overloaded or insufficient, thereby maintaining the stability of the analysis process and optimizing the separation effect. The intelligent selection of the injection method effectively avoids the uneven distribution of the sample, further improving the separation efficiency and analysis accuracy. It not only improves the degree of automation of the system, but also significantly improves the reliability and accuracy of the analysis results, providing solid technical support for efficient clinical analysis.

[0027] Injection volume adjustment includes: Sample property analysis: Viscosity of the sample is measured by a viscometer sensor, solubility is measured by a refractive index sensor, and the spectral response of the sample is analyzed by a multispectral sensor to evaluate its compositional complexity (diversity of ingredients); Sample concentration calculation: Using the sample concentration and the standard requirements of chromatographic analysis, combined with the properties of the sample (viscosity , solubility , ingredient complexity ), calculate the injection volume , expressed as: ; in, For automatically adjusted injection volume, is the sample concentration, is the sample solubility, is the sample composition complexity, indicating the diversity of sample components. is the viscosity of the sample, is the experience correction factor; Injection volume adjustment: calculated injection volume , adjust the injection volume of the injection system or pump to ensure that the sample injection volume is in the optimal range to avoid sample overload or underload and ensure the stability of the analysis and separation effect; Through the above content, the injection volume is automatically adjusted to ensure that the sample injection is in the optimal range. The precise adjustment method can effectively avoid sample overload or underload, ensure the stability of the analysis process, optimize the separation effect, and thus improve the accuracy and reliability of the overall analysis. By intelligently adjusting the injection volume according to the dynamic characteristics of the sample, the module can adapt to the needs of different samples, improve the automation level and adaptability of the system, and provide technical support for efficient and accurate analysis.

[0028] Injection mode control includes: Chromatographic column processing capacity evaluation: by real-time monitoring of the working status of the chromatographic column (pressure, flow rate, temperature), the processing capacity of the chromatographic column is evaluated and the current load capacity of the chromatographic column is calculated. , expressed as: ; in, is the current working pressure of the chromatographic column, is the current flow rate of the column, is the operating temperature of the chromatographic column; Injection method selection: by the current loading capacity of the column With load threshold lower limit and upper load threshold Compare and automatically select the injection method. When you select manual injection, When you select automatic injection, When selecting online injection; Load lower threshold and upper load threshold The settings include: Collect historical data: Collect historical data, including the performance of the column under different operating conditions, including different pressures, flow rates and temperatures, and calculate the corresponding current load capacity of the column ; Calculate the statistical value of processing capacity: Based on the collected historical data, calculate the statistical value of the processing capacity of the chromatographic column, including the mean and standard deviation, expressed as: ; ; in, is the number of samples of historical data, is the mean processing capacity, is the standard deviation of processing capacity; Set threshold: Set the lower limit of the load threshold based on the statistical value of the calculated column processing capacity and upper load threshold , expressed as: ; ; in, is the coefficient, set between 1 and 2, is the coefficient, set between 1 and 2; Through the above content, the best injection method can be automatically selected intelligently and in real time according to the load condition of the chromatographic column. By dynamically adjusting the injection method, such as manual injection, automatic injection or online injection, analysis errors caused by overload or uneven injection are avoided, ensuring the stability and analysis accuracy of chromatographic separation, which not only improves the efficiency of sample processing, but also avoids equipment damage or performance degradation.

[0029] The separation effect prediction module includes: Multimodal data fusion: real-time acquisition of operating parameters in the chromatography system, including flow rate, temperature and pressure, and integration of the operating parameters into comprehensive parameters using multimodal data fusion technology; Separation effect prediction and condition adjustment: Based on the integrated parameters after fusion, the chromatographic separation effect is predicted in real time. According to the prediction results, combined with the properties of the sample (viscosity, solubility, component complexity) and separation requirements, the chromatographic separation conditions (mobile phase composition, gradient change and temperature setting) are automatically adjusted to optimize the separation process to achieve the best separation effect and the highest resolution. Through the above content, multiple operating parameters in the chromatographic system can be acquired and accurately analyzed in real time, ensuring accurate prediction of separation effects under different operating conditions. Based on the real-time prediction of separation effects, the chromatographic separation conditions can be dynamically adjusted to optimize the separation process and improve separation efficiency and resolution. This not only reduces human intervention and improves the level of automation of operations, but also greatly improves the stability and reliability of the separation process, ensuring that each analysis can achieve the best results, thereby greatly improving experimental efficiency and data accuracy.

[0030] Multimodal data fusion includes: Operation parameter acquisition: real-time acquisition of flow rate, temperature and pressure in the chromatography system through sensors; Data fusion: Use weighted algorithms to fuse the collected operating parameters into comprehensive parameters , expressed as: ; in, are the weight coefficients of flow rate, temperature and pressure respectively, is the flow rate, is the temperature, For pressure; Through the above content, it is possible to flexibly adapt to different experimental conditions and sample characteristics, improve the prediction accuracy of the separation effect, not only improve the automation and intelligence level of the separation process, but also ensure the real-time optimization of the separation conditions, and ultimately improve the accuracy of the analysis results and the separation efficiency.

[0031] Separation effect prediction and condition adjustment include: Separation effect prediction: using integrated parameters after fusion The properties of the sample (viscosity, solubility, composition complexity) are input into the linear regression model to predict the chromatographic separation effect in real time. , expressed as: ; in, To predict the separation effect, is the comprehensive parameter after fusion, is the viscosity of the sample, is the solubility of the sample, is the composition complexity of the sample, is the coefficient to be optimized, is the bias term; Optimizing separation conditions: Predicting results based on separation performance , combined with the sample properties, the chromatographic separation conditions are adjusted using an optimization algorithm to maximize the separation effect, expressed as: ; in, The optimized mobile phase composition is To predict the separation effect, is the viscosity of the sample, is the solubility of the sample, is the coefficient to be optimized; ; in, is the gradient change (mobile phase gradient change), To predict the separation effect, is the composition complexity of the sample, is the coefficient to be optimized; ; in, For the optimized temperature setting, To predict the separation effect, is the viscosity of the sample, is the coefficient to be optimized; Through the above content, the separation effect can be accurately predicted based on the real-time collected chromatographic operating parameters and sample characteristics, and the chromatographic separation conditions (such as mobile phase composition, gradient changes and temperature settings) can be automatically adjusted. This not only improves the separation efficiency and accuracy, but also reduces the dependence on human intervention, and achieves a high degree of automation and intelligence. By continuously optimizing the separation conditions, the separation effect can be maximized, adapting to the complexity and changes of different samples, greatly improving the repeatability and reliability of the experiment, and providing more accurate quantitative results for clinical analysis.

[0032] The mass spectrometry detection module includes: Mass spectrometry analysis: According to the adjusted chromatographic separation conditions, the sample components after chromatographic separation are received in real time, and the separated sample components are detected by mass spectrometry analysis technology; Mass spectrometry data acquisition: Based on the detection results of mass spectrometry analysis technology, the mass information of the sample components is collected in real time, including the mass and concentration of the target molecule and the mass and concentration of the internal standard substance; Through the above content, not only the accuracy and real-time performance of sample analysis are improved, but also the interference and loss in the sample processing process can be effectively avoided. Through close integration with chromatographic separation conditions, the quality characteristics of each component can be accurately captured, providing high-resolution quality data.

[0033] Data analysis modules include: Analyze the relative relationship between the sample and the coexisting substances: Based on the mass spectrometry data and the mass and concentration of the coexisting substances (impurities or metabolites) in the sample, the peak area ratio method is used to analyze the relative concentration and mass ratio between the target molecule and the coexisting substances, expressed as: ; in, is the relative concentration of the target molecule and the internal standard substance, and are the mass spectrum peak areas of the target molecule and the internal standard substance, is the concentration of the internal standard substance with known concentration, is the concentration of the target molecule to be quantified; Calculate the quantitative results: By analyzing the mass ratio and concentration ratio between the target molecule and the coexisting substances, interference is removed and the final quantitative results are optimized, which can be expressed as: in, is the optimized target molecule concentration, It is The mass spectrum peak area of ​​the coexisting substances (impurities or metabolites), is the mass spectrum peak area of ​​the target molecule (substance to be analyzed); Through the above content, the interference of coexisting substances on the concentration of target molecules can be accurately removed, thereby improving the accuracy of the analysis results. By using the peak area ratio method, the relative concentration of the target molecule and the internal standard substance is calculated to ensure the reliability and consistency of the quantitative results, which can improve the efficiency of sample separation and detection and reduce the impact of human errors.

[0034] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0035] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A high performance liquid chromatography system for clinical mass spectrometry, characterized in that: It includes a sample processing module, a sample distribution module, a separation effect prediction module, a mass spectrometry detection module and a data analysis module, wherein; The sample processing module processes the sample to be analyzed and removes impurities in the sample; The sample distribution module automatically adjusts the injection volume and injection mode according to the nature and concentration of the sample and matches it with the processing capacity of the chromatographic column; The separation effect prediction module uses multimodal data fusion technology to analyze multiple operating parameter data from the chromatographic system in real time, including flow rate, temperature, and pressure, to predict the chromatographic separation effect, and based on the predicted results of the chromatographic separation effect, adjust the chromatographic separation conditions in combination with the properties of the sample and the separation requirements, including the composition of the mobile phase, gradient change, and temperature setting; The mass spectrometry detection module detects the separated sample components based on the adjusted chromatographic separation conditions and obtains the quality information of the sample in real time; The data analysis module analyzes the relative relationship between the sample and the coexisting substances based on the acquired mass information of the sample, and generates a final quantitative result.

2. The high performance liquid chromatography system for clinical mass spectrometry according to claim 1, characterized in that: The sample processing module comprises: Sample pretreatment: Pre-treat the sample to be analyzed by removing large particle impurities, suspended matter and insoluble matter in the sample by centrifugation; Impurity removal: Remove dissolved impurities and tiny particles in the sample by selective ultrafiltration.

3. The high performance liquid chromatography system for clinical mass spectrometry according to claim 1, characterized in that: The sample distribution module comprises: Injection volume adjustment: Automatically adjust the injection volume according to the properties and concentration of the sample to be analyzed; Injection mode control: According to the processing capacity of the chromatographic column, the injection mode is automatically selected, including manual injection, automatic injection, and online injection.

4. The high performance liquid chromatography system for clinical mass spectrometry according to claim 3, characterized in that: The injection volume adjustment includes: Sample property analysis: Viscosity of the sample is measured by a viscometer sensor, solubility is measured by a refractive index sensor, and the spectral response of the sample is analyzed by a multi-spectral sensor to evaluate its compositional complexity; Sample concentration calculation: Calculate the injection volume based on the sample concentration and the standard requirements of chromatographic analysis combined with the properties of the sample. ; Injection volume adjustment: calculated injection volume , adjust the injection volume of the injection system or pump.

5. The high performance liquid chromatography system for clinical mass spectrometry according to claim 4, characterized in that: The injection mode control includes: Chromatographic column processing capacity evaluation: by real-time monitoring of the working status of the chromatographic column, the processing capacity of the chromatographic column is evaluated and the current load capacity of the chromatographic column is calculated. ; Injection method selection: by the current loading capacity of the column With load threshold lower limit and upper load threshold Compare and automatically select the injection method. When you select manual injection, When you select automatic injection, , select Online Injection.

6. The high performance liquid chromatography system for clinical mass spectrometry according to claim 5, characterized in that: The separation effect prediction module comprises: Multimodal data fusion: real-time acquisition of operating parameters in the chromatography system, including flow rate, temperature and pressure, and integration of the operating parameters into comprehensive parameters using multimodal data fusion technology; Separation effect prediction and condition adjustment: Based on the integrated parameters after fusion, the chromatographic separation effect is predicted in real time. According to the prediction results, combined with the properties of the sample and the separation requirements, the chromatographic separation conditions are automatically adjusted to optimize the separation process.

7. The high performance liquid chromatography system for clinical mass spectrometry according to claim 6, characterized in that: The multimodal data fusion includes: Operation parameter acquisition: real-time acquisition of flow rate, temperature and pressure in the chromatography system through sensors; Data fusion: Use weighted algorithms to fuse the collected operating parameters into comprehensive parameters .

8. The high performance liquid chromatography system for clinical mass spectrometry according to claim 7, characterized in that: The separation effect prediction and condition adjustment include: Separation effect prediction: using integrated parameters after fusion The properties of the sample are input into the linear regression model to predict the chromatographic separation effect in real time. ; Optimizing separation conditions: Predicting results based on separation performance , combined with the sample properties, the chromatographic separation conditions are adjusted using an optimization algorithm to maximize the separation effect.

9. The high performance liquid chromatography system for clinical mass spectrometry according to claim 1, characterized in that: The mass spectrometry detection module comprises: Mass spectrometry analysis: According to the adjusted chromatographic separation conditions, the sample components after chromatographic separation are received in real time, and the separated sample components are detected by mass spectrometry analysis technology; Mass spectrometry data acquisition: Based on the detection results of mass spectrometry analysis technology, the mass information of the sample components is collected in real time, including the mass and concentration of the target molecule and the mass and concentration of the internal standard substance.

10. The high performance liquid chromatography system for clinical mass spectrometry according to claim 9, characterized in that: The data analysis module includes: Analyze the relative relationship between the sample and the coexisting substances: Based on the mass spectrometry data and the mass and concentration of the coexisting substances in the sample, use the peak area ratio method to analyze the relative concentration and mass ratio between the target molecule and the coexisting substances; Calculate quantitative results: By analyzing the mass ratio and concentration ratio between the target molecule and the coexisting substances, interference is removed and the final quantitative results are optimized.

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