Multi-mode medicine component detection method and system

Abstract

The invention discloses a multi-mode medicine component detection method and system, and relates to the technical field of medicine component detection. Comprising the following steps: acquiring an initial attribute: dividing a medicine needing to be detected into at least two medicine samples, selecting one of the medicine samples, putting the selected medicine sample into a first detection instrument, and acquiring an initial environment attribute of the medicine sample in a detection starting stage to obtain a first starting attribute; and attribute grade division: dividing the environment attribute into at least two grades, and performing grade division on the first startup attribute to obtain a first sample attribute item. When multi-mode detection is carried out, the temperature is high during follow-up detection, the temperature is reduced through the temperature control system, the temperature is low, the temperature is increased through the temperature control system, the number of dust particles is large, the dust particles are sucked out through the suction equipment, the number of the dust particles is small, and external dust particles are sprayed into a drug sample through the spraying equipment; and the consistency of detection results of different detection instruments is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of drug component detection, and in particular to a multimodal drug component detection method and system. Background Art

[0002] Drug ingredient testing is a crucial part of the drug research and development and production process. Testing drug ingredients can identify potential harmful substances, ensure the safety of drugs for patients, and avoid adverse reactions. In addition, through ingredient testing, it can be confirmed whether the active ingredients of the drug meet expectations, thereby ensuring its therapeutic effect. In the drug production process, ingredient testing helps to monitor product quality and ensure the consistency and stability of each batch of drugs. Common drug ingredient testing methods include: high performance liquid chromatography is used to separate, identify and quantify drug ingredients, which is suitable for the analysis of complex samples; gas chromatography is suitable for the analysis of volatile and semi-volatile compounds, and is often used in conjunction with mass spectrometry to improve detection sensitivity and accuracy; biosensors use the specific binding of biomolecules to drug ingredients for detection, which is suitable for rapid, on-site detection.

[0003] Patent publication number CN116825382A is a method and device for detecting the effectiveness of epilepsy drugs based on multimodal fusion. First, clinical data of patients with tuberous sclerosis are collected; the clinical data include: clinical characteristics, MRI characteristics, CT characteristics, EEG characteristics, and gene characteristics, realizing multimodal fusion of clinical data to solve the problem of small sample size of TSC patients. Then, the clinical data is preprocessed to obtain standard clinical data. Next, samples are randomly selected from the processed clinical data and a small sample map is created as input features to obtain a training feature matrix. By creating a small sample map, the flexibility of the model is enhanced, thereby reducing the computational burden.

[0004] When the above-mentioned and similar technical solutions are used to detect drug components in a multimodal manner, a variety of detection methods and detection equipment will be used. During the use of different detection methods, it is necessary to divide the drug components into multiple parts, and each part is detected using different detection methods and detection equipment. In the detection process, different detection methods will cause changes in the temperature of the detection environment. During nuclear magnetic resonance detection, the radio frequency pulse will apply energy to the sample, which will cause the local temperature of the sample to rise. Compared with other detection methods, the temperature increase will have a certain impact on the detection results, resulting in non-uniform temperature of the sample during multimodal detection. Summary of the invention

[0005] The object of the present invention is to provide a multimodal drug component detection method and system to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a multimodal drug component detection method and system, comprising:

[0007] Initial attribute acquisition: the drug to be tested is divided into at least two drug samples, and one of the drug samples is selected and placed in the first testing device, and the initial environmental attributes of the drug sample at the beginning of the test are obtained to obtain the first startup attribute;

[0008] Attribute level division: divide the environmental attributes into at least two levels, and divide the first startup attribute into levels to obtain a first sample attribute item;

[0009] Acquiring detection attributes: acquiring detection environment attributes of the target drug sample during the detection process, obtaining the first startup continuation attribute, and classifying the first startup continuation attribute to obtain the first sample detection attribute item;

[0010] Testing environment adjustment: Based on the test attribute items of the first sample, the environmental attributes of subsequent drug samples are adjusted through adjustment methods. During the entire multimodal testing process, the environmental attributes of the drug samples caused by each testing instrument are kept consistent, and the environmental attributes of the drug samples are also kept consistent, thereby enhancing the accuracy of the integration of multimodal testing results;

[0011] The adjustment method comprises:

[0012] Step 1: establishing a benchmark attribute, based on the first sample attribute item and the first sample detection attribute item as benchmark attributes, respectively, to obtain a first benchmark attribute item and a second benchmark attribute item;

[0013] Step 2: First adjustment, obtaining the initial environmental properties of the drug sample that needs to be adjusted for the initial environmental properties when it is placed in the testing device, obtaining the first adjustment property, and classifying the first adjustment property to obtain the first adjustment item, obtaining the first difference item based on the difference between the first adjustment item and the first benchmarking property item, and changing the initial environmental properties based on the first difference item;

[0014] Step three: second adjustment, obtaining the detection environment attributes of the drug sample that needs to be adjusted for the detection environment attributes when the detection device is tested, obtaining the second adjustment continuation attributes, and classifying the second adjustment continuation attributes to obtain the second adjustment continuation item, obtaining the second difference item based on the difference between the second adjustment continuation item and the second benchmark attribute item, and changing the detection environment attributes based on the second difference item.

[0015] Furthermore, the initial environment attribute includes a temperature attribute, and the method for obtaining the first power-on attribute includes:

[0016] S1: first device selection, selecting a temperature detection device as a first target device, and setting at least one temperature detection device;

[0017] S2: Acquiring temperature data, based on the first target device, acquiring temperature data of the target drug sample detection start stage, and obtaining a first startup attribute.

[0018] Furthermore, the detection environment attributes include temperature attributes, and the method for obtaining the first power-on continuation attribute includes: setting a first detection interval, setting the first detection interval, obtaining a first detection interval item, and based on the first detection interval item and the first target device, obtaining temperature data of the target drug sample during the detection process to obtain a detection temperature set, the detection temperature set includes at least one detection temperature item, and then obtaining the first power-on continuation attribute.

[0019] Furthermore, the initial environment attribute and the detected environment attribute include temperature attributes, and the first adjustment and the second adjustment methods include:

[0020] N1: positive and negative judgment, based on the first difference item and the second difference item, a positive and negative judgment is performed to obtain a first adjustment direction item and a second adjustment direction item;

[0021] N2: numerical judgment, performing numerical judgment based on the first difference item and the second difference item to obtain a first adjustment data item and a second adjustment data item;

[0022] N3: Temperature adjustment, based on the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, adjustment is performed by a temperature control device.

[0023] Furthermore, the second adjustment method also includes: based on the first detection interval item, continuously acquiring the second adjustment continuation item, thereby obtaining at least one second adjustment direction item and at least one second adjustment data item, and performing adjustment through the temperature control device.

[0024] Furthermore, the initial environmental attribute includes a dust particle attribute, and the method for acquiring the first power-on attribute includes:

[0025] M1: second device selection, selecting a high-definition image capturing device as the second target device, and setting at least one high-definition image capturing device;

[0026] M2: Image data acquisition, acquiring image data of the target drug sample detection start stage based on the second target device, and obtaining the number of dust particles based on the image data, and then obtaining the first startup attribute.

[0027] Furthermore, the detection environment attributes include dust particle attributes, and the method for obtaining the first power-on continuation attribute includes: setting a second detection interval, setting the second detection interval, obtaining a second detection interval item, and based on the second detection interval item and the second target device, obtaining image data of the target drug sample during the detection process to obtain a detection image set, the detection image set includes at least one detection image item, and then obtaining the first power-on continuation attribute.

[0028] Furthermore, the initial environmental attributes and the detected environmental attributes include dust particle attributes, and the first adjustment and second adjustment methods also include: particle quantity adjustment, based on the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, through a suction device and a spraying device.

[0029] Furthermore, the second adjustment method also includes: based on the second detection interval item, continuously acquiring the second adjustment continuation item, thereby obtaining at least one second adjustment direction item and at least one second adjustment data item, and performing adjustment through a suction device and a spraying device.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The multimodal drug component detection method and system obtains the initial environmental properties of the first drug sample to be tested in the first detection device, and adjusts the initial environmental properties of the drug samples to be tested subsequently according to the initial environmental properties obtained by the detection, so that the initial environmental properties of the drug samples to be tested subsequently remain consistent when entering the detection device. Since the environmental properties include temperature and dust particles, when the temperature is high, the temperature is lowered by the temperature control system, and when the temperature is low, the temperature is raised by the temperature control system. When the number of dust particles is large, the dust particles are sucked out by the suction device, and when the number of dust particles is small, the external dust particles are sprayed into the drug sample by the spraying device, thereby greatly improving the consistency of the detection results of different detection devices and improving the accuracy of the integrated detection results.

[0032] At the same time, during the process of drug sample testing, the detection environment attributes within the first testing device are continuously acquired, so as to obtain the attributes of the first drug sample to be tested that are affected by the detection environment of the testing device during the testing process, and adjust the detection environment attributes of subsequent drug samples during the testing process, so as to always keep the environmental attributes of each device consistent throughout the entire multimodal testing process, thereby enhancing the accuracy of the integrated data. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1It is a schematic diagram of the relationship among initial attribute acquisition, attribute level division, detection attribute acquisition and detection environment adjustment of the present invention;

[0034] Figure 2 It is a schematic flow chart of the adjustment method of the present invention;

[0035] Figure 3 It is a schematic diagram of the quantity division of the drug samples of the present invention;

[0036] Figure 4 It is a schematic diagram of the first sample attribute item and the first sample detection attribute item of the present invention;

[0037] Figure 5 It is a schematic diagram of the first adjustment item and the second adjustment continuation item of the present invention;

[0038] Figure 6 It is a schematic diagram of the change of the initial environment attribute of the present invention;

[0039] Figure 7 It is a schematic diagram of the detection environment attribute change of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Since different detection instruments and detection methods will cause different environmental attribute effects on the samples in the detection instruments, and multimodal detection requires the integration of the detection results of different instruments and different methods, when the environmental attributes are inconsistent, it is easy to affect the integration results, resulting in inaccurate detection and integration results. The technical solution provided by the present application first obtains the initial environmental attributes of the first drug sample to be detected in the first detection instrument during the detection process using different detection instruments, and adjusts the environmental attributes of the drug samples to be subsequently detected according to the initial environmental attributes obtained during the detection, so that the environmental attributes of the drug samples to be subsequently detected are consistent when entering the detection instrument, thereby greatly improving the consistency of the detection results of different detection instruments and improving the accuracy of the integrated detection results. In the process of drug sample detection, the detection environment attributes in the first detection instrument are continuously obtained, so as to obtain the attributes of the first drug sample to be detected that are affected by the detection environment of the detection instrument during the detection process, and adjust the detection environment attributes of the drug samples to be subsequently detected during the detection process, so as to always keep the environmental attributes of each instrument consistent during the entire multimodal detection process and enhance the accuracy of the integrated data.

[0042] like Figure 1-Figure 7As shown, the present invention provides a technical solution: a multimodal drug component detection method and system, including: initial attribute acquisition: dividing the drug to be detected into at least two drug samples, and selecting one of the drug samples to be placed in a first detection device, obtaining the initial environmental attributes of the drug sample at the beginning of the detection, and obtaining a first startup attribute; attribute level division: dividing the environmental attributes into at least two levels, and dividing the first startup attribute into levels to obtain a first sample attribute item; detection attribute acquisition: obtaining the detection environment attributes of the target drug sample during the detection process, obtaining a first startup continuation attribute, and dividing the first startup continuation attribute into levels to obtain a first sample detection attribute item; detection environment adjustment: based on the first sample detection attribute item, adjusting the environmental attributes of subsequent drug samples through an adjustment method, in the entire multimodal detection process, keeping the environmental attributes of the drug samples caused by each detection device consistent, and the environmental attribute influence on the drug samples also consistent, Enhance the accuracy of the integration of multimodal detection results; the adjustment method includes: step one: benchmark attribute establishment, based on the first sample attribute item and the first sample detection attribute item as the benchmark attribute respectively, to obtain the first benchmark attribute item and the second benchmark attribute item; step two: first adjustment, obtain the initial environmental attribute of the drug sample that needs to be adjusted for the initial environmental attribute when it is placed in the detection device, obtain the first adjustment attribute, and grade the first adjustment attribute to obtain the first adjustment item, based on the difference between the first adjustment item and the first benchmark attribute item, obtain the first difference item, and based on the first difference item, change the initial environmental attribute; step three: second adjustment, obtain the detection environmental attribute of the drug sample that needs to be adjusted for the detection environmental attribute when the detection device is used, obtain the second adjustment continuation attribute, and grade the second adjustment continuation attribute to obtain the second adjustment continuation item, based on the difference between the second adjustment continuation item and the second benchmark attribute item, obtain the second difference item, and based on the second difference item, change the detection environmental attribute.

[0043] It should be noted that in the process of multimodal detection, the drugs need to be divided into multiple drug samples according to the number of detection devices. When the first drug sample is selected for detection and placed in the first detection device, the initial environmental attribute impact of environmental factors on the drug sample is first obtained to obtain the first startup attribute, and the environmental attributes are divided into three levels, namely low, medium and high. The initial environmental attributes of the obtained target drug samples are divided into levels to obtain the first sample attribute item. Since the environmental attributes include temperature and particulate impurities in the air, the division standard is: low-level temperature is ≤±1°C, and low-level particulate impurities are particles ≤10; medium temperature is >±1°C, ≤±2°C, medium-level particulate impurities are particles >10, ≤20; high-level temperature is >±2°C, and high-level particulate impurities are particles >20.

[0044] In the specific implementation process, a drug sample needs to undergo multimodal testing. One portion of the drug to be tested is divided into six portions. At this time, the temperature of the six portions is 15°C, and the number of dust particles is 0. Then one of the drug samples is placed in a nuclear magnetic resonance device for testing. When the test is about to be performed, the initial environmental properties of the drug sample are obtained: the temperature is 16.5°C, the number of dust particles is 13, and the initial environmental property level of the target is intermediate.

[0045] It should be noted that when the initial environmental attribute level of the target drug sample is obtained, the detection environment attribute of the target drug sample also needs to be obtained during the detection process to obtain the first power-on continuation attribute, and at the same time, the level is divided to obtain the first sample detection attribute item.

[0046] In the specific implementation process, when one of the drug samples was placed in the nuclear magnetic resonance device for testing, during the testing process, the testing environment attributes of the drug sample were obtained as follows: the temperature was 17.5°C, the number of dust particles was 24, and the testing environment attribute level of the target was advanced.

[0047] It should be noted that when the first sample attribute item and the first sample detection attribute item of the target drug sample are obtained, when subsequent drug samples are detected, the environmental attributes of the subsequent drug samples are adjusted according to the first sample attribute item and the first sample detection attribute item.

[0048] In the specific implementation process, a drug sample needs to be tested by multimodal detection. One portion of the drug to be tested is divided into six portions. At this time, the temperature of the six portions is 15°C and the number of dust particles is 0. When one of the drug samples is placed in the nuclear magnetic resonance device for detection, when the detection is about to be performed, the initial environmental attributes of the drug sample are obtained: the temperature is 16.5°C, the number of dust particles is 13, and the initial environmental attribute level of the target is intermediate, that is, the first benchmark attribute item is intermediate. During the detection process, the detection environmental attributes of the drug sample are obtained: the temperature is 17.5°C, the number of dust particles is 24, and the detection environmental attribute level of the target is advanced, that is, the second benchmark attribute item is advanced. When the drug is injected into the HPLC system for high-performance liquid chromatography detection, at the beginning of the detection, the initial environmental properties of the drug sample are obtained as follows: temperature is 15.5°C, the number of dust particles is 9, and the initial environmental property level of the target sample is low, that is, the first adjustment item is low. During the detection process, the detection environmental properties of the drug sample are obtained as follows: temperature is 16.5°C, the number of dust particles is 15, and the detection environmental property level of the target is medium, that is, the second adjustment continuation item is high. The environmental properties of the drug at the beginning of the detection and during the detection process are adjusted according to the first difference item obtained by the difference between the first adjustment item and the first benchmark attribute item and the second difference item obtained by the difference between the second adjustment continuation item and the second benchmark attribute item.

[0049] The initial environmental attributes include temperature attributes, and the method for obtaining the first startup attribute includes: S1: first device selection, selecting a temperature detection device as the first target device, and setting at least one temperature detection device; S2: temperature data acquisition, based on the first target device, acquiring the temperature data of the target drug sample detection start stage, to obtain the first startup attribute.

[0050] It should be noted that the temperature detection device is an infrared thermometer, and two infrared thermometers are set to detect the temperature of the drug sample before the detection begins to obtain the first startup attribute.

[0051] The detection environment attributes include temperature attributes, and the method for obtaining the first power-on continuation attribute includes: setting the first detection interval, setting the first detection interval, obtaining the first detection interval item, and based on the first detection interval item and the first target device, obtaining the temperature data of the target drug sample during the detection process to obtain a detection temperature set, the detection temperature set includes at least one detection temperature item, and then obtaining the first power-on continuation attribute.

[0052] It should be noted that during the detection process, the first detection interval is set to 10 seconds, and the temperature of the drug sample needs to be detected every 10 seconds using an infrared thermometer according to the set detection interval.

[0053] The initial environmental attributes and the detected environmental attributes include temperature attributes, and the first adjustment and second adjustment methods include: N1: positive and negative judgment, based on the first difference item and the second difference item, a positive and negative judgment is performed to obtain a first adjustment direction item and a second adjustment direction item; N2: numerical judgment, based on the first difference item and the second difference item, a numerical judgment is performed to obtain a first adjustment data item and a second adjustment data item; N3: temperature adjustment, based on the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, adjustment is performed through a temperature control device.

[0054] It should be noted that the temperature control device is a temperature control system, which determines the direction and magnitude of control based on the first difference item and the second difference item, and makes adjustments based on the judgment result.

[0055] The second adjustment method also includes: based on the first detection interval item, continuously acquiring the second adjustment continuation item, thereby obtaining at least one second adjustment direction item and at least one second adjustment data item, and performing adjustment through the temperature control device.

[0056] It should be noted that during the detection process, since the first detection interval is set to 10 seconds, the second adjustment continuation item will be obtained through temperature detection every 10 seconds, and the temperature of the drug sample will be adjusted through the temperature control system.

[0057] The initial environmental attributes include dust particle attributes, and the method for obtaining the first power-on attribute includes: M1: second device selection, selecting a high-definition image capture device as the second target device, and setting at least one high-definition image capture device; M2: image data acquisition, acquiring image data of the initial stage of target drug sample detection based on the second target device, and obtaining the number of dust particles based on the image data, and then obtaining the first power-on attribute.

[0058] It should be noted that the second target device is a high-definition camera. Two high-definition cameras are set to photograph the drug samples. The number of dust particles is obtained based on the captured image data, and then the first power-on attribute is obtained.

[0059] The detection environment attributes include dust particle attributes, and the method for obtaining the first power-on continuation attribute includes: setting a second detection interval, setting the second detection interval, obtaining a second detection interval item, and obtaining image data of the target drug sample during the detection process based on the second detection interval item and the second target device to obtain a detection image set, wherein the detection image set includes at least one detection image item, and then obtaining the first power-on continuation attribute.

[0060] It should be noted that the second detection interval is set to 20 seconds. Every 20 seconds, the drug sample is imaged by a high-definition camera, and the number of dust particles is determined to obtain the first power-on continuation attribute.

[0061] The initial environmental attributes and the detected environmental attributes include dust particle attributes. The first adjustment and second adjustment methods also include: particle quantity adjustment, based on the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, through the suction device and the spraying device.

[0062] It should be noted that, according to the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, in order to ensure the balance of the number of dust particles in the drug sample, when the number of dust particles is too large, the dust particles are sucked out by the suction device, and when the number of dust particles is small, the external dust particles are sprayed into the drug sample by the spraying device.

[0063] The second adjustment method also includes: based on the second detection interval item, continuously acquiring the second adjustment continuation item, thereby obtaining at least one second adjustment direction item and at least one second adjustment data item, and performing adjustment through the suction device and the spraying device.

[0064] It should be noted that during the detection process, since the second detection interval is set to 20 seconds, the second adjustment continuation item will be obtained through the high-definition camera every 20 seconds, and the temperature of the drug sample will be adjusted through the suction device and the spraying device.

[0065] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. A multimodal drug component detection method, characterized in that: include: Initial attribute acquisition: the drug to be tested is divided into at least two drug samples, and one of the drug samples is selected and placed in the first testing device, and the initial environmental attributes of the drug sample at the beginning of the test are obtained to obtain the first startup attribute; Attribute level division: divide the environmental attributes into at least two levels, and divide the first startup attribute into levels to obtain a first sample attribute item; Acquiring detection attributes: acquiring detection environment attributes of the target drug sample during the detection process, obtaining the first startup continuation attribute, and classifying the first startup continuation attribute to obtain the first sample detection attribute item; Testing environment adjustment: Based on the test attribute item of the first sample, the test environment attributes of subsequent drug samples are adjusted through the adjustment method. During the entire multimodal testing process, the test environment attributes of each testing instrument on the drug sample are kept consistent, and the impact of the test environment attributes on the drug sample is also kept consistent, thereby enhancing the accuracy of the integration of multimodal testing results; The adjustment method comprises: Step 1: establishing a benchmark attribute, based on the first sample attribute item and the first sample detection attribute item as benchmark attributes, respectively, to obtain a first benchmark attribute item and a second benchmark attribute item; Step 2: First adjustment, obtaining the initial environmental properties of the drug sample that needs to be adjusted for the initial environmental properties when it is placed in the testing device, obtaining the first adjustment property, and classifying the first adjustment property to obtain the first adjustment item, obtaining the first difference item based on the difference between the first adjustment item and the first benchmarking property item, and changing the initial environmental properties based on the first difference item; Step three: second adjustment, obtaining the detection environment attributes of the drug sample that needs to be adjusted for the detection environment attributes when the detection device is tested, obtaining the second adjustment continuation attributes, and classifying the second adjustment continuation attributes to obtain the second adjustment continuation item, obtaining the second difference item based on the difference between the second adjustment continuation item and the second benchmark attribute item, and changing the detection environment attributes based on the second difference item.

2. A multimodal drug component detection method according to claim 1, characterized in that: The initial environment attribute includes a temperature attribute, and the method for obtaining the first startup attribute includes: S1: first device selection, selecting a temperature detection device as a first target device, and setting at least one temperature detection device; S2: Acquiring temperature data, based on the first target device, acquiring temperature data of the target drug sample detection start stage, and obtaining a first startup attribute.

3. A multimodal drug component detection method according to claim 2, characterized in that: The detection environment attributes include temperature attributes, and the method for obtaining the first power-on continuation attribute includes: setting a first detection interval, setting the first detection interval, obtaining a first detection interval item, and based on the first detection interval item and the first target device, obtaining temperature data of the target drug sample during the detection process to obtain a detection temperature set, the detection temperature set includes at least one detection temperature item, and then obtaining the first power-on continuation attribute.

4. A multimodal drug component detection method according to claim 1, characterized in that: The initial environment attribute and the detected environment attribute include temperature attributes, and the first adjustment and the second adjustment methods include: N1: positive and negative judgment, based on the first difference item and the second difference item, a positive and negative judgment is performed to obtain a first adjustment direction item and a second adjustment direction item; N2: numerical judgment, performing numerical judgment based on the first difference item and the second difference item to obtain a first adjustment data item and a second adjustment data item; N3: Temperature adjustment, based on the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, adjustment is performed by a temperature control device.

5. A multimodal drug component detection method according to claim 4, characterized in that: The second adjustment method also includes: based on the first detection interval item, continuously acquiring the second adjustment continuation item, thereby obtaining at least one second adjustment direction item and at least one second adjustment data item, and performing adjustment through the temperature control device.

6. A multimodal drug component detection method according to claim 1, characterized in that: The initial environmental attribute includes a dust particle attribute, and the method for acquiring the first power-on attribute includes: M1: second device selection, selecting a high-definition image capturing device as the second target device, and setting at least one high-definition image capturing device; M2: Image data acquisition, acquiring image data of the target drug sample detection start stage based on the second target device, and obtaining the number of dust particles based on the image data, and then obtaining the first startup attribute.

7. A multimodal drug component detection method according to claim 6, characterized in that: The detection environment attributes include dust particle attributes, and the method for obtaining the first power-on continuation attribute includes: setting a second detection interval, setting the second detection interval, obtaining a second detection interval item, and obtaining image data of the target drug sample during the detection process based on the second detection interval item and the second target device to obtain a detection image set, wherein the detection image set includes at least one detection image item, and then obtaining the first power-on continuation attribute.

8. A multimodal drug component detection method according to claim 4, characterized in that: The initial environmental attributes and the detected environmental attributes include dust particle attributes, and the first adjustment and second adjustment methods also include: particle quantity adjustment, based on the first adjustment direction item, the second adjustment direction item, the first adjustment data item and the second adjustment data item, through the suction device and the spraying device.

9. A multimodal drug component detection method according to claim 7, characterized in that: The second adjustment method also includes: based on the second detection interval item, continuously acquiring the second adjustment continuation item, thereby obtaining at least one second adjustment direction item and at least one second adjustment data item, and performing adjustment through a suction device and a spraying device.

10. A multimodal drug component detection system, characterized in that: A multimodal drug component detection method as described in any one of claims 1-9 is used.

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