Clinical test intelligent monitoring system based on big data analysis

Abstract

The invention relates to the technical field of medical data processing, in particular to a clinical test intelligent monitoring system based on big data analysis, and the system comprises a test data collection module, a test risk assessment module, a risk early warning feedback module and a clinical test database. The test object visiting risk, the test progress abnormal risk and the test object compliance are incorporated into an overall evaluation system of the clinical test, and the transparency and credibility of the clinical test can be enhanced through the comprehensive evaluation system. The credibility of the public on clinical tests is improved, smooth development of the clinical tests and wide acceptance of results are promoted, resource allocation is optimized, and the research efficiency is improved. According to the method, progress delay possibly occurring in the test process is recognized and processed in time, so that a researcher can ensure that the test is carried out according to a plan, and resource waste and cost increase caused by the progress delay are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data processing, and in particular to an intelligent monitoring system for clinical trials based on big data analysis. Background Art

[0002] Clinical trial data is an important basis for decision-making in the medical field, such as new drug development and medical device evaluation. Its authenticity, integrity and reliability are directly related to public health and life safety. Therefore, effective monitoring of clinical trial data to ensure the scientificity and credibility of the data is an important part of protecting the public interest.

[0003] For example, the invention patent with publication number: CN116487066A is a clinical trial data monitoring method, system and electronic equipment, which relates to the field of computer technology, including receiving the original clinical trial data of the test subject, the original clinical data is the original clinical trial data that cannot be tampered with but can be traced, and the original clinical trial data includes personal vital signs data and basic test data, so as to avoid the qualitative difference of the input basic test data and ensure the authenticity of the data; by obtaining the personal vital signs data of the test subject in real time, judging whether the test subject has an abnormal reaction through the abnormal reaction analysis model, and determining whether to terminate the current clinical trial according to the abnormal level of the abnormal reaction, so as to timely discover and deal with the abnormal reaction time; by inputting the personal vital signs data and the basic test data into the progress monitoring model, the test progress of the current clinical trial is monitored, saving manpower, material resources and time costs.

[0004] For example, the invention patent with publication number: CN118366591A is a safety detection method for clinical trial data, including: continuously collecting clinical trial data of patients at various times over multiple days, performing periodic analysis and volatility analysis to extract periodic characteristic values ​​and volatility characteristic values ​​of the daily clinical trial data, combining the volatility characteristic values ​​and periodic characteristic values ​​to obtain the initial period number, and adjusting the initial period number according to the noise level of the clinical trial data, effectively reducing the impact of noise on the prediction results, improving the prediction accuracy, and realizing adaptive adjustment of the period number, using the adjusted initial period number to construct a moving average prediction model, predicting the clinical trial data after the day, and performing safety detection based on the deviation between the predicted value and the true value. It can monitor the clinical trial data in real time and accurately, effectively prevent and identify potential safety risks, and provide a certain safety guarantee for clinical trial data management.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it was found that the above technology has at least the following technical problems: the current clinical trial monitoring system pays more attention to the processing of clinical data after collection, and there are deficiencies in the analysis of the test subjects. The data quality of clinical trials is more easily affected by the behavior of the test subjects, and there is a greater data quality risk. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides an intelligent clinical trial monitoring system based on big data analysis, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention provides an intelligent clinical trial monitoring system based on big data analysis, including: a test data acquisition module, a test risk assessment module and a risk warning feedback module.

[0008] Among them, the test data collection module is used to collect test data within a preset clinical trial cycle, including basic information data of test subjects, test subject compliance data and clinical trial progress data.

[0009] The trial risk assessment module is used to obtain the trial subject loss risk assessment index based on the trial subject basic information data, obtain the trial subject compliance assessment index based on the trial subject compliance data, obtain the trial progress abnormality risk assessment index based on the trial subject compliance assessment index and clinical trial progress data, and obtain the clinical trial risk assessment index through comprehensive analysis.

[0010] The risk warning feedback module is used to perform risk assessment on the clinical trial according to the clinical trial risk assessment indicators, obtain the assessment results and provide feedback.

[0011] As a further method, the basic information data of the test subjects specifically includes: the number of disease records, the number of allergies and the number of surgeries of each test subject.

[0012] The test subject compliance assessment index specifically includes: the time of each medication of each test subject and the amount of medication of each test subject.

[0013] The clinical trial progress data specifically include: the total number of initial trial participants, the cumulative number of lost participants, and the duration of each trial phase.

[0014] As a further method, the processing obtains the test subject loss follow-up risk assessment index, and the specific process is: extracting the critical disease record times, critical allergy times and critical surgery times from the clinical trial database, and based on the basic information data of the test subjects, comprehensively analyzing to obtain the test subject loss follow-up risk assessment index. The test subject loss follow-up risk assessment index is used to quantitatively assess the degree of loss follow-up risk of clinical trial subjects, and provide a data basis for risk assessment of clinical trials.

[0015] As a further method, the processing to obtain the test subject compliance evaluation index specifically involves the following process: extracting each planned medication time, each planned medication amount, critical deviation medication time and allowable deviation medication amount of each test subject from the clinical trial database, extracting each deviation medication time of each test subject, and obtaining the test subject compliance evaluation index through comprehensive analysis based on the test subject compliance data.

[0016] As a further method, the abnormal trial progress risk assessment index is obtained through processing, and the specific process is: according to the test subject compliance assessment index and the clinical trial progress data, the estimated duration of each test stage is collected, and the allowable deviation duration is extracted from the clinical trial database, and the abnormal trial progress risk assessment index is obtained through comprehensive analysis.

[0017] As a further method, the subject compliance assessment index is a quantitative assessment data obtained by comprehensively analyzing the medication time and medication dosage of each subject, which is used to quantitatively assess the degree of compliance of the subject during the clinical trial and provide a data basis for risk assessment of the clinical trial.

[0018] As a further method, the abnormal trial progress risk assessment index is a quantitative assessment data obtained by comprehensively analyzing the test subject compliance assessment index, the total number of initial trial subjects, the cumulative number of lost follow-up subjects and the duration of each trial stage. It is used to quantitatively assess the degree of abnormal progress of clinical trials and provide a data basis for risk assessment of clinical trials.

[0019] As a further method, the comprehensive analysis obtains clinical trial risk assessment indicators. The specific analysis process is: based on the trial subject loss risk assessment index, the trial progress abnormal risk assessment index and the trial subject compliance assessment index, a comprehensive analysis is performed to obtain the clinical trial risk assessment index. The clinical trial risk assessment index is used to quantitatively assess the risk level of the clinical trial.

[0020] As a further method, the risk assessment of the clinical trial is performed according to the clinical trial risk assessment indicators. The specific assessment process is: extracting the clinical trial risk assessment indicator threshold from the clinical trial database, comparing the clinical trial risk assessment indicator with the clinical trial risk assessment indicator threshold, if the clinical trial risk assessment indicator is lower than or equal to the clinical trial risk assessment indicator threshold, then the clinical trial risk is assessed as qualified; if the clinical trial risk assessment indicator is higher than the clinical trial risk assessment indicator threshold, then the clinical trial risk is assessed as unqualified, and the reasons for the unqualified clinical trial are analyzed.

[0021] As a further method, the clinical trial risk assessment index has a specific numerical expression as follows: ; in, represents the clinical trial risk assessment index, It represents the risk assessment index of lost follow-up of trial subjects. Indicates the risk assessment index of abnormal test progress. represents the test subject compliance assessment index, It indicates the clinical trial risk impact factor corresponding to the preset trial subject loss risk assessment index. Indicates the clinical trial risk impact factor corresponding to the preset trial progress abnormal risk assessment index. Represents the clinical trial risk impact factor corresponding to the preset trial subject compliance assessment index.

[0022] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides an intelligent clinical trial monitoring system based on big data analysis, which incorporates the risk of trial subject loss, the risk of abnormal trial progress and trial subject compliance into the overall evaluation system of clinical trials, which helps to improve the success rate of clinical trials. A comprehensive evaluation system can enhance the transparency and credibility of clinical trials. This helps to enhance the public's trust in clinical trials, promote the smooth implementation of clinical trials and the wide acceptance of results, and also helps to optimize resource allocation, improve research efficiency and reduce research costs.

[0023] (2) This invention helps to identify potential risks and reduce the loss of subjects due to health problems by evaluating the subjects' medical history, allergy history and other factors, thereby reducing the probability of trial failure. It also helps researchers to more accurately judge the possible effects of the trial drugs on the subjects, thereby formulating more reasonable trial plans and safety measures.

[0024] (3) This invention evaluates the progress delays that may occur during the experiment. By timely identifying and handling them, researchers can ensure that the experiment proceeds as planned and avoid waste of resources and increased costs caused by progress delays. At the same time, it also helps to improve the integrity and reliability of the experimental data, providing strong support for subsequent statistical analysis and result interpretation. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0026] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0027] Figure 2 It is a schematic diagram of the functional relationship between the test subject compliance evaluation index and the clinical trial risk evaluation index involved in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] Reference Figure 1 As shown, the present invention provides an intelligent clinical trial monitoring system based on big data analysis, including: a trial data acquisition module, a trial risk assessment module and a risk warning feedback module.

[0030] Among them, the test data collection module is used to collect test data within a preset clinical trial cycle, including basic information data of the test subjects, test progress data and test subject compliance data.

[0031] Specifically, the basic information data of the test subjects specifically include: the number of disease records, the number of allergies and the number of surgeries of each test subject.

[0032] The test subject compliance assessment index specifically includes: the time of each medication of each test subject and the amount of medication of each test subject.

[0033] The clinical trial progress data specifically include: the total number of initial trial participants, the cumulative number of lost participants, and the duration of each trial phase.

[0034] It should be explained that the number of disease records, allergy times and surgery times of the test subjects in this embodiment can be obtained through detailed questionnaires or interviews, and the test subjects may be required to provide past medical records or medical records for review if necessary. The trial stage can be directly obtained based on the trial design documents and schedule. The compliance assessment index of each test subject is tracked and recorded in real time by the research team, and the start and end time of each stage is recorded. The time of each medication of each test subject and the amount of medication of each test subject are guided by the research nurse or researcher according to the trial protocol, and the time and dosage of each medication are recorded in detail. The cumulative number of lost visits and the duration of each trial stage can be obtained by visiting the clinical trial registration website, querying the regulatory agency database and using statistical analysis and data processing software.

[0035] The trial risk assessment module is used to obtain the trial subject loss risk assessment index based on the trial subject basic information data, obtain the trial progress abnormality risk assessment index based on the trial progress data, obtain the trial subject compliance assessment index based on the trial subject compliance data, and obtain the clinical trial risk assessment index through comprehensive analysis.

[0036] Specifically, the subject loss follow-up risk assessment index is obtained through processing, and the specific process is: extracting the critical number of disease records, the critical number of allergies and the critical number of surgeries from the clinical trial database, and based on the basic information data of the subject, comprehensively analyzing to obtain the subject loss follow-up risk assessment index. The subject loss follow-up risk assessment index is used to quantitatively assess the degree of loss follow-up risk of clinical trial subjects, and provide a data basis for risk assessment of clinical trials.

[0037] In a specific embodiment, the numerical expression of the test subject loss risk assessment index is: ; in, represents the risk assessment index of lost follow-up of the trial subjects, n represents the number of each trial subject, , m represents the total number of test subjects, represents the number of disease records for the nth test subject, represents the number of allergies of the nth test subject, represents the number of surgeries for the nth test subject, represents the number of critical disease records, Indicates the critical allergy number, represents the critical number of surgeries, Indicates the risk factor of lost follow-up of the test subject corresponding to the preset number of disease records, It indicates the risk factor of loss to follow-up of the test subject corresponding to the preset number of allergies. It represents the risk influencing factor of loss to follow-up of the trial subjects corresponding to the preset number of surgeries.

[0038] It should be understood that, from the above embodiments, it can be concluded that when the number of disease records, allergies and surgeries of the test subject is greater, the corresponding test subject loss risk assessment index will be greater, indicating that the risk of loss of the test subject is greater and the impact on the test is greater.

[0039] It should be explained that in this embodiment The risk influencing factor of lost follow-up of the trial subjects corresponding to the preset number of disease records, The risk influencing factor of loss to follow-up of the test subject corresponding to the preset number of allergies, The risk factors for lost visits of test subjects corresponding to the preset number of surgeries respectively represent the numerical values ​​of the degree of influence of the unit values ​​of the number of disease records, the number of allergies and the number of surgeries on the risk for lost visits of test subjects. When used, the risk factors for lost visits of test subjects corresponding to the number of disease records, the risk factors for lost visits of test subjects corresponding to the number of allergies and the risk factors for lost visits of test subjects corresponding to the number of surgeries can be directly obtained from the clinical trial database. The corresponding relationship can be a preset mapping relationship. For example, the number of disease records, the number of allergies and the number of surgeries of the test subject are respectively mapped with the risk factors for lost visits of test subjects corresponding to the preset number of disease records, the number of allergies and the number of surgeries in the clinical trial database to form a mapping set. The real-time number of disease records, the number of allergies and the number of surgeries of the test subject are input into the mapping set to obtain the risk factors for lost visits of test subjects corresponding to the number of disease records, the risk factors for lost visits of test subjects corresponding to the number of allergies and the risk factors for lost visits of test subjects corresponding to the number of surgeries. The mapping relationship can be one-to-one or many-to-one.

[0040] It should be explained that the above impact factors are extracted from the clinical trial database, and the value range is between 0 and 1.

[0041] Table 1 Data example of the risk assessment index for loss of trial subjects serial number Number of disease records (times) Allergy frequency (times) Number of surgeries (times) The risk assessment index for loss of trial subjects 1 4 2 1 0.76 2 1 0 0 0.32 3 10 6 3 1.06 4 2 4 1 0.77 5 3 1 0 0.57 It should be explained that, in a specific embodiment, the test subject loss risk assessment index takes one test subject as an example.

[0042] It should be explained that, in this embodiment, the critical number of disease records is set to 5, the critical number of allergies is set to 3, the critical number of surgeries is set to 2, the impact factor corresponding to the number of disease records is set to 0.7, the impact factor corresponding to the number of allergies is set to 0.5, and the impact factor corresponding to the number of surgeries is set to 0.8.

[0043] It should be explained that this embodiment helps to identify potential risks and reduce the loss of subjects due to health problems of the subjects by evaluating the previous medical history, allergy history and other factors of the test subjects, thereby reducing the probability of trial failure. It also helps researchers to more accurately judge the possible impact of the test drug on the subjects, so as to formulate more reasonable test plans and safety measures.

[0044] Furthermore, the processing to obtain the test subject compliance evaluation index specifically involves the following process: extracting each planned medication time, each planned medication amount, critical deviation medication time and allowable deviation medication amount of each test subject from the clinical trial database, extracting each deviation medication time of each test subject, and obtaining the test subject compliance evaluation index through comprehensive analysis based on the test subject compliance data.

[0045] It should be explained that the deviation medication time of each test subject in this embodiment refers to the time deviation value between each medication time of each test subject and each planned medication time.

[0046] It should be understood that the subject compliance assessment index is a quantitative assessment data obtained by comprehensively analyzing the medication time and medication dosage of each subject, and is used to quantitatively assess the degree of compliance of the subject during the clinical trial and provide a data basis for risk assessment of the clinical trial.

[0047] In a specific embodiment, the numerical expression of the test subject compliance assessment index is: ; in, represents the test subject compliance assessment index, e represents the natural constant, r represents the number of each medication, , s represents the total number of times the medication is taken, represents the deviation of the medication time of the nth test subject at the rth medication time, represents the dosage of the nth test subject at the rth time of taking the drug, represents the planned dosage of the nth test subject at the rth time, Indicates critical deviation medication time, Indicates the allowable deviation dosage. Indicates the test subject compliance influencing factor corresponding to the preset test subject medication time, It indicates the subject compliance influencing factor corresponding to the preset subject medication dosage.

[0048] It should be understood that, from the above embodiments, when the deviation value of the test subject's medication time and the deviation value of the test subject's medication amount are larger, the corresponding test subject compliance evaluation index is smaller, indicating that the degree of compliance of the test subject during the clinical trial is lower.

[0049] It should be explained that in this embodiment The compliance influencing factor of the test subject corresponding to the preset medication time of the test subject, The test subject compliance influencing factors corresponding to the preset test subject medication dosage respectively represent the numerical values ​​of the degree of influence of the test subject medication time and the test subject medication dosage unit values ​​on the test subject compliance. When used, the test subject compliance influencing factors corresponding to the test subject medication time and the test subject compliance influencing factors corresponding to the test subject medication dosage can be directly obtained from the clinical trial database. The corresponding relationship can be a pre-set mapping relationship. For example, the test subject medication time and the test subject medication dosage respectively form a mapping set with the test subject compliance influencing factors corresponding to the test subject medication time and the test subject medication dosage preset in the clinical trial database. The real-time test subject medication time and the test subject medication dosage are input into the mapping set to obtain the test subject compliance influencing factors corresponding to the test subject medication time and the test subject compliance influencing factors corresponding to the test subject medication dosage. The mapping relationship can be one-to-one or many-to-one. The above-mentioned influencing factors are all extracted from the clinical trial database, and the value range is between 0 and 1.

[0050] Furthermore, the subject compliance assessment index threshold is extracted from the clinical trial database, and the subject compliance assessment index is compared with the subject compliance assessment index threshold; if the subject compliance assessment index is higher than or equal to the subject compliance assessment index threshold, the clinical trial subject compliance is assessed as qualified; if the subject compliance assessment index is lower than the subject compliance assessment index threshold, the clinical trial subject compliance is assessed as unqualified, and the reasons for the unqualified subject compliance are analyzed.

[0051] It should be explained that in this embodiment, the reasons for the unqualified compliance of the test subjects specifically include that the test subjects do not take the medicine at the prescribed time and dosage. The fixed medication time helps the subjects to develop good medication habits and improve the compliance of the subjects. The compliance of the subjects is crucial for the smooth progress of clinical trials and the reliability of the results. Inaccurate medication time may become an important source of experimental errors. By strictly controlling the medication time, the impact of this error on the test results can be reduced. The appropriate dosage can ensure the effective concentration of the drug in the body, so as to give full play to the efficacy of the drug. Reasonable dosage can also reduce the risk of adverse drug reactions. Overdose may increase the incidence of adverse reactions, while insufficient dosage may not achieve the expected therapeutic effect. By strictly controlling the dosage, the safety of the subjects during the trial can be ensured. Avoid serious adverse reactions caused by overdose or treatment failure caused by insufficient dosage.

[0052] Specifically, based on the results of the above analysis of the compliance of the trial personnel, researchers can provide detailed compliance education to the subjects before the start of the trial, so that they understand the importance, purpose, methods and precautions of the trial. Education can also be carried out through lectures, brochures, videos and other forms to improve the compliance and cooperation of the subjects. At the same time, on the premise of meeting the requirements of the trial, simplify the trial process as much as possible to reduce the burden and inconvenience of the subjects. Use convenient follow-up methods, such as telephone follow-up and online follow-up, to improve follow-up efficiency and compliance. Strengthen the care and attention of the subjects and promptly solve the problems and difficulties they encounter during the trial. In addition, timely intervention and guidance are carried out for subjects with poor compliance to help them improve compliance. Incentive measures can also be used to improve the enthusiasm and cooperation of the subjects to ensure the smooth progress of the trial. Expand the scope of subject recruitment and use multiple channels for recruitment, such as social media, hospital bulletin boards, patient organizations, etc. Strengthen communication and exchanges with subjects, improve their understanding and participation in the trial, and help reduce the loss rate of subjects.

[0053] Furthermore, the abnormal trial progress risk assessment index is obtained through processing, and the specific process is: according to the test subject compliance assessment index and the clinical trial progress data, the estimated duration of each test stage is collected, and the allowable deviation duration is extracted from the clinical trial database, and the abnormal trial progress risk assessment index is obtained through comprehensive analysis.

[0054] It should be understood that the trial progress abnormality risk assessment index is a quantitative assessment data obtained by comprehensively analyzing the trial subject compliance assessment index, the total number of initial trial subjects, the cumulative number of lost follow-up subjects and the duration of each trial stage. It is used to quantitatively assess the degree of abnormal progress of clinical trials and provide a data basis for risk assessment of clinical trials.

[0055] In a specific embodiment, the numerical expression of the test progress abnormal risk assessment index is: ; in, Indicates the test progress abnormal risk assessment index, represents the test subject compliance assessment index, t represents the number of each test stage, , h represents the total number of trial stages, Indicates the cumulative number of lost follow-up at the current time point, represents the duration of the t-th trial phase, represents the estimated duration of the tth trial phase, Indicates the duration of the allowed deviation during the test phase. represents the total number of people at the beginning of the experiment, It indicates the risk influencing factor of abnormal test progress corresponding to the preset test subject compliance assessment index. It indicates the risk influencing factor of abnormal test progress corresponding to the preset test subject loss rate. Indicates the test progress abnormal risk impact factor corresponding to the preset test phase duration.

[0056] It should be explained that the duration of the trial phase in the above embodiment represents the cumulative time of the historical trial phases before the current trial phase, and the cumulative number of lost follow-up refers to the cumulative number of lost follow-up in the clinical trial at the current time point.

[0057] It should be understood that, from the above embodiments, the smaller the test subject compliance assessment index is, the larger the deviation value of the total number of cumulative lost follow-up and the duration of the test phase is, the larger the corresponding test progress abnormality risk assessment index is, indicating that the degree of abnormality in the clinical trial progress is higher.

[0058] It should be explained that in this embodiment The risk influencing factor of abnormal test progress corresponding to the preset test subject compliance assessment index, is the risk influencing factor of abnormal trial progress corresponding to the preset trial subject loss rate, The test progress abnormal risk influencing factors corresponding to the preset test phase duration respectively represent the numerical values ​​of the influence degree of the test subject compliance assessment index, the test subject loss rate and the test phase duration unit numerical values ​​on the test progress abnormal risk. When used, the test progress abnormal risk influencing factors corresponding to the test subject compliance assessment index, the test subject loss rate and the test phase duration can be directly obtained from the clinical trial database, and the corresponding relationship can be a preset mapping relationship. For example, the test subject compliance assessment index, the test subject loss rate and the test phase duration are respectively mapped with the test progress abnormal risk influencing factors corresponding to the test subject compliance assessment index, the test subject loss rate and the test phase duration preset in the clinical trial database to form a mapping set, and the real-time test subject compliance assessment index, the test subject loss rate and the test phase duration are input into the mapping set to obtain the test progress abnormal risk influencing factors corresponding to the test subject compliance assessment index, the test subject loss rate and the test phase duration, and the mapping relationship can be one-to-one or a many-to-one relationship. The above impact factors are extracted from the clinical trial database, and the value range is between 0 and 1.

[0059] Furthermore, a trial progress abnormality risk assessment index threshold is extracted from the clinical trial database, and the trial progress abnormality risk assessment index is compared with the trial progress abnormality risk assessment index threshold; if the trial progress abnormality risk assessment index is lower than or equal to the trial progress abnormality risk assessment index threshold, the clinical trial progress abnormality is assessed as qualified; if the trial progress abnormality risk assessment index is higher than the trial progress abnormality risk assessment index threshold, the clinical trial progress abnormality is assessed as unqualified, and the reasons for the unqualified clinical trial progress abnormality are analyzed.

[0060] It should be explained that the reasons for abnormal clinical trial progress failure include low compliance of trial subjects and high loss of follow-up rate of trial subjects, which leads to longer trial phase time. When the compliance of subjects is low, researchers may need to spend more time and energy to correct the behavior of subjects to ensure that they follow the trial protocol. This may lead to an extension of the trial cycle and affect the overall progress of the trial. Low compliance may also lead to the need for additional monitoring and intervention measures during the trial, such as increasing the number of follow-up visits and providing additional guidance, thereby increasing the cost of the trial. During the trial, researchers may need to spend a certain amount of time and energy to track and contact lost subjects to minimize the impact of loss of follow-up on the trial results. This may extend the trial cycle and affect the overall progress of the trial. The more people who are lost to follow-up, the less valid data can be provided, which may lead to increased deviation or uncertainty in the research results. Especially in Phase III and Phase IV clinical trials that require large sample sizes, the increase in the cumulative number of lost to follow-up may seriously affect the statistical power of the trial. Lost patients need to be re-recruited or supplemented, which will consume additional time and resources, thereby delaying the overall progress of the trial. If the loss of follow-up rate is too high, it may even lead to the trial not being completed on time or having to be terminated early.

[0061] It needs to be explained that a reasonable trial schedule can ensure a comprehensive and adequate evaluation of the safety, efficacy and tolerability of the drug. Trials at different stages require different times to accumulate sufficient data to support subsequent decisions and judgments. A trial phase that is too short may not fully expose the potential risks or efficacy of the drug, increasing the uncertainty of the trial results. An appropriate duration can reduce this uncertainty and improve the reliability of the trial results. A reasonable trial schedule can also help optimize resource allocation and avoid unnecessary waste. A trial phase that is too long may increase trial costs and time costs, while a trial phase that is too short may require re-trials due to insufficient data.

[0062] Specifically, the comprehensive analysis obtains clinical trial risk assessment indicators, and the specific analysis process is: based on the trial subject loss risk assessment index, the trial progress abnormal risk assessment index and the trial subject compliance assessment index, a comprehensive analysis is performed to obtain the clinical trial risk assessment index, and the clinical trial risk assessment index is used to quantitatively assess the risk level of the clinical trial.

[0063] In a specific embodiment, the numerical expression of the clinical trial risk assessment index is: ; in, represents the clinical trial risk assessment index, It represents the risk assessment index of lost follow-up of trial subjects. Indicates the risk assessment index of abnormal test progress. represents the test subject compliance assessment index, It indicates the clinical trial risk impact factor corresponding to the preset trial subject loss risk assessment index. Indicates the clinical trial risk impact factor corresponding to the preset trial progress abnormal risk assessment index. Represents the clinical trial risk impact factor corresponding to the preset trial subject compliance assessment index.

[0064] It should be understood that, from the above embodiments, the larger the risk assessment index of trial subject loss and the risk assessment index of abnormal trial progress, and the smaller the trial subject compliance assessment index, the larger the corresponding clinical trial risk assessment index, indicating that the risk level of the clinical trial is greater.

[0065] It should be explained that in this embodiment The clinical trial risk impact factor corresponding to the preset trial subject loss risk assessment index, The clinical trial risk impact factor corresponding to the preset abnormal trial progress risk assessment index, The clinical trial risk impact factors corresponding to the preset subject compliance assessment index respectively represent the numerical values ​​of the degree of influence of the subject loss risk assessment index, the trial progress abnormality risk assessment index and the subject compliance assessment index unit values ​​on the clinical trial risk. When used, the clinical trial risk impact factors corresponding to the subject loss risk assessment index, the clinical trial risk impact factors corresponding to the trial progress abnormality risk assessment index and the clinical trial risk impact factors corresponding to the subject compliance assessment index can be directly obtained from the clinical trial database. The corresponding relationship can be a preset mapping relationship, for example, the subject loss risk assessment index, the trial progress abnormality risk assessment index The number and the test subject compliance assessment index are respectively mapped with the test subject loss risk assessment index, the test progress abnormality risk assessment index and the test subject compliance assessment index preset in the clinical trial database to form a mapping set of clinical trial risk impact factors corresponding to the test subject loss risk assessment index, the test progress abnormality risk assessment index and the test subject compliance assessment index. The real-time test subject loss risk assessment index, the test progress abnormality risk assessment index and the test subject compliance assessment index are input into the mapping set to obtain the clinical trial risk impact factor corresponding to the test subject loss risk assessment index, the clinical trial risk impact factor corresponding to the test progress abnormality risk assessment index and the clinical trial risk impact factor corresponding to the test subject compliance assessment index, wherein the mapping relationship can be one-to-one or many-to-one. The above impact factors are all extracted from the clinical trial database, and the value range is between 0 and 1.

[0066] It should be understood that if Figure 2As shown, curve a represents the relationship between the corresponding test subject compliance assessment index and the clinical trial risk assessment index when the output test subject loss risk assessment index is 0.11 and the test progress abnormal risk assessment index is 0.45. Curve b represents the relationship between the corresponding test subject compliance assessment index and the clinical trial risk assessment index when the output test subject loss risk assessment index is 0.23 and the test progress abnormal risk assessment index is 0.51. Curve c represents the relationship between the corresponding test subject compliance assessment index and the clinical trial risk assessment index when the output test subject loss risk assessment index is 0.91 and the test progress abnormal risk assessment index is 0.97.

[0067] It should be explained that, in this embodiment, the clinical trial risk impact factor corresponding to the trial subject loss risk assessment index is set to 0.8, the clinical trial risk impact factor corresponding to the trial progress abnormality risk assessment index is set to 0.5, and the clinical trial risk impact factor corresponding to the trial subject compliance assessment index is set to 1.0.

[0068] It should be explained that in this embodiment, by evaluating the past medical history, allergy history and other factors of the test subject, it is helpful to identify potential risks. Reduce the risk of trial failure or adverse events caused by health problems of the subject. At the same time, it also helps researchers to more accurately judge the possible impact of the test drug on the subject, so as to formulate more reasonable test plans and safety measures. Clinical risk assessment also helps researchers understand the efficacy and safety of the test drug, and provides an important basis for subsequent research and drug development. By evaluating abnormal conditions such as progress delays and missing data that may occur during the trial. By identifying and handling these abnormal conditions in a timely manner, researchers can ensure that the trial proceeds as planned and avoid waste of resources and increased costs caused by progress delays. At the same time, it also helps to improve the integrity and reliability of the test data and provide strong support for subsequent statistical analysis and interpretation of results. Incorporating the risk assessment index of the test subject's loss of follow-up, the risk assessment index of abnormal test progress and the test subject's compliance assessment index into the overall evaluation system of clinical trials will help improve the success rate of clinical trials. At the same time, by comprehensively evaluating various risk indexes, researchers can promptly discover potential risk points and allocate resources accordingly, such as increasing the monitoring frequency and adjusting the test plan. This helps to optimize resource allocation, improve research efficiency and reduce research costs.

[0069] The risk warning feedback module is used to perform risk assessment on the clinical trial according to the clinical trial risk assessment indicators, obtain the assessment results and provide feedback.

[0070] Specifically, the risk assessment of the clinical trial is performed according to the clinical trial risk assessment indicators, and the specific assessment process is: extracting the clinical trial risk assessment indicator threshold from the clinical trial database, comparing the clinical trial risk assessment indicator with the clinical trial risk assessment indicator threshold, if the clinical trial risk assessment indicator is lower than or equal to the clinical trial risk assessment indicator threshold, then the clinical trial risk is assessed as qualified; if the clinical trial risk assessment indicator is higher than the clinical trial risk assessment indicator threshold, then the clinical trial risk is assessed as unqualified, and the reasons for the unqualified clinical trial are analyzed.

[0071] Further, the process of analyzing the reasons for unqualified clinical trials is as follows: first, clarify which risk assessment indicators are used for evaluation and what are the specific thresholds of these indicators. These indicators may include safety issues such as adverse event rates, effectiveness indicators such as primary endpoint achievement rates, data integrity such as data missing rates, etc. Check whether the trial design is reasonable, including sample size calculation, inclusion criteria, exclusion criteria, randomization methods, blind design, etc. Unreasonable design may lead to biased results, thereby affecting risk assessment. Then evaluate whether the execution of the trial is strictly in accordance with the protocol, including trial subject management, drug / treatment management, data collection and recording, etc. Any operation that deviates from the protocol may affect the accuracy and reliability of the results. Then check the integrity, accuracy and consistency of the data. Missing data, incorrect records or inconsistencies may lead to biased risk assessment results. Furthermore, analyze the adverse events that occurred in the trial in detail, especially serious adverse events, and evaluate their incidence, severity and causal relationship with the trial drug / treatment. Finally, consider whether external events that may affect the results occurred during the trial, such as epidemics, natural disasters, etc. On the basis of the above analysis, various factors are combined to form a comprehensive understanding of the reasons for unqualified clinical trials. Propose suggestions for improvement, including how to adjust the trial design, strengthen data management and compliance measures, etc., to reduce the occurrence of similar problems in the future. Write a detailed analysis report, recording the above analysis process, problems found and suggestions. Submit the report to relevant agencies such as regulatory agencies and sponsors, and make necessary adjustments and improvements based on feedback.

[0072] In a specific embodiment, the clinical trial database is used to store relevant data in the clinical trial risk assessment process, specifically including the number of critical disease records, the number of critical allergies and the number of critical surgeries, the abnormal risk influencing factors of the trial progress corresponding to the test subject compliance assessment index and the clinical trial risk assessment indicator threshold value, as well as the data extracted from the above embodiments. The data in the clinical trial database can be obtained through the results and data of clinical experimental research regularly published in various academic journals.

[0073] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. The intelligent monitoring system for clinical trials based on big data analysis is characterized by: include: Test data collection module, test risk assessment module and risk warning feedback module; The test data collection module is used to collect test data within a preset clinical trial cycle, including basic information data of test subjects, test subject compliance data and clinical trial progress data; The trial risk assessment module is used to obtain the trial subject loss risk assessment index through processing based on the trial subject basic information data, obtain the trial subject compliance assessment index through processing based on the trial subject compliance assessment index and the clinical trial progress data, and obtain the trial progress abnormality risk assessment index through comprehensive analysis; The risk warning feedback module is used to perform risk assessment on the clinical trial according to the clinical trial risk assessment indicators, obtain the assessment results and provide feedback.

2. The clinical trial intelligent monitoring system based on big data analysis according to claim 1 is characterized by: The basic information data of the test subjects specifically include: the number of disease records, allergy records and surgery records of each test subject; The test subject compliance assessment index specifically includes: the time of each medication of each test subject and the amount of medication of each test subject; The clinical trial progress data specifically include: the total number of initial trial participants, the cumulative number of lost participants, and the duration of each trial phase.

3. The clinical trial intelligent monitoring system based on big data analysis according to claim 1 is characterized by: The processing to obtain the test subject loss risk assessment index is as follows: The critical number of disease records, critical number of allergies and critical number of surgeries were extracted from the clinical trial database, and based on the basic information data of the trial subjects, a comprehensive analysis was performed to obtain the trial subject loss risk assessment index, which is used to quantitatively assess the degree of loss risk of clinical trial subjects, and provide a data basis for risk assessment of clinical trials.

4. The clinical trial intelligent monitoring system based on big data analysis according to claim 1 is characterized by: The test subject compliance assessment index is obtained through processing, and the specific process is: The planned medication time, planned medication dosage, critical deviation medication time and allowable deviation medication dosage of each subject were extracted from the clinical trial database, and the deviation medication time of each subject was extracted. Based on the subject compliance data, a comprehensive analysis was performed to obtain the subject compliance assessment index.

5. The clinical trial intelligent monitoring system based on big data analysis according to claim 1 is characterized by: The test progress abnormal risk assessment index is obtained through processing, and the specific process is: According to the subject compliance assessment index and clinical trial progress data, the estimated duration of each trial stage is collected, and the allowable deviation duration is extracted from the clinical trial database. A comprehensive analysis is conducted to obtain the abnormal risk assessment index for trial progress.

6. The clinical trial intelligent monitoring system based on big data analysis according to claim 4 is characterized by: The test subject compliance assessment index is a quantitative assessment data obtained by comprehensively analyzing the medication time and medication dosage of each test subject, and is used to quantitatively assess the degree of compliance of the test subjects during the clinical trial and provide a data basis for risk assessment of the clinical trial.

7. The clinical trial intelligent monitoring system based on big data analysis according to claim 5 is characterized by: The abnormal trial progress risk assessment index is a quantitative assessment data obtained by comprehensively analyzing the test subject compliance assessment index, the total number of initial trial subjects, the cumulative number of lost follow-up subjects and the duration of each trial stage. It is used to quantitatively assess the degree of abnormal progress of clinical trials and provide a data basis for risk assessment of clinical trials.

8. The clinical trial intelligent monitoring system based on big data analysis according to claim 7 is characterized by: The comprehensive analysis obtains the clinical trial risk assessment index, and the specific analysis process is as follows: Based on the trial subject loss risk assessment index, the trial progress abnormal risk assessment index and the trial subject compliance assessment index, a comprehensive analysis is conducted to obtain the clinical trial risk assessment index, which is used to quantitatively assess the risk level of the clinical trial.

9. The clinical trial intelligent monitoring system based on big data analysis according to claim 8 is characterized by: The risk assessment of clinical trials is carried out according to the clinical trial risk assessment indicators, and the specific assessment process is as follows: The clinical trial risk assessment indicator threshold is extracted from the clinical trial database, and the clinical trial risk assessment indicator is compared with the clinical trial risk assessment indicator threshold. If the clinical trial risk assessment indicator is lower than or equal to the clinical trial risk assessment indicator threshold, the clinical trial risk assessment is qualified; if the clinical trial risk assessment indicator is higher than the clinical trial risk assessment indicator threshold, the clinical trial risk assessment is unqualified, and the reasons for the unqualified clinical trials are analyzed.

10. The clinical trial intelligent monitoring system based on big data analysis according to claim 8 is characterized by: The specific numerical expression of the clinical trial risk assessment index is: ； in, represents the clinical trial risk assessment index, It represents the risk assessment index of lost follow-up of trial subjects. Indicates the risk assessment index of abnormal test progress. represents the test subject compliance assessment index, It indicates the clinical trial risk impact factor corresponding to the preset trial subject loss risk assessment index. Indicates the clinical trial risk impact factor corresponding to the preset trial progress abnormal risk assessment index. Represents the clinical trial risk impact factor corresponding to the preset trial subject compliance assessment index.

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