Clinical test scheme design optimization method and system

Abstract

The invention discloses a clinical test scheme design optimization method and system, and relates to the field of design data processing, and the method comprises the following steps: receiving verification data submitted by a physician end, carrying out the analysis based on a scheme template database, obtaining a clinical test scheme template, receiving volunteer medical record information sent by a volunteer database, and carrying out the verification of the verification data. The method comprises the steps that a clinical test scheme template is established, a data monitoring group set is obtained according to the clinical test scheme template, and a control group volunteer data set and a standard group volunteer data set serve as the data monitoring group set to be sent to a disease index database. Through dynamic cross validation, interference of volunteer individual differences on drug effects is effectively eliminated, accuracy and reliability of test data are improved, and result deviation caused by individual factors is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the medical field, in particular to a clinical trial scheme design optimization method, system and device. BACKGROUND

[0002] With the rapid development of precision medicine and personalized treatment, the role of clinical trials in drug development, treatment optimization and other fields is increasingly prominent. Traditional clinical trials rely on manual design of schemes, which is time-consuming and labor-intensive and is easily affected by subjective factors, making it difficult to efficiently cope with complex disease characteristics and individual differences. In recent years, the integration of artificial intelligence and big data technology has brought new opportunities for clinical trial design, and through intelligent system optimization of trial processes and improvement of data accuracy has become the focus of the industry. However, clinical trials involve multiple challenges such as ethical compliance, data security, dynamic adjustment, and the like, and there is an urgent need for a standardized and automated scheme optimization method to improve trial efficiency and reduce risks.

[0003] Currently, clinical trial scheme design mainly relies on the combination of physician experience and standardized templates. Physicians need to manually screen volunteers, set up control groups and standard groups, regularly collect data and compare and analyze.

[0004] In the current process of medical research and drug development, clinical trials play a crucial role. However, traditional clinical trial design methods have many limitations and challenges, such as improper selection of subjects, unreasonable setting of control groups, and unclear effect indicators, which may lead to inaccurate trial results and unreliable conclusions, thereby affecting the scientific nature of new drug marketing and clinical decision-making. SUMMARY

[0005] The present application provides a clinical trial scheme design optimization method and system for solving the technical problems of existing individual difference interference and lack of dynamic optimization.

[0006] In view of the above problems, the present application provides a clinical trial scheme design optimization method and system.

[0007] The first aspect of the application provides a set of clinical trial scheme optimization method, the method is applied to a clinical trial scheme design optimization system, the method comprises the following steps: receiving verification data submitted by a physician end, analyzing based on a scheme template database, obtaining a clinical trial scheme template, receiving volunteer medical record information issued by a volunteer database, obtaining a data monitoring group set according to the clinical trial scheme template, sending the control group volunteer data set and the standard group volunteer data set to the disease index database as the data monitoring group set, obtaining standard index information, receiving the clinical volunteer index information set issued by the physician end according to the data monitoring group set combined with the feedback time index, obtaining the volunteer clinical information combined with the standard index information, and the volunteer clinical information includes the control group clinical data set and the standard group clinical data set.

[0008] The second aspect of the application provides a clinical trial scheme design optimization system, comprising a physician end, which is used to provide an interactive platform for physicians, authenticate the physician identity, and upload opinion data by the physician to assist in scheme development, a scheme template database, which is used to store template data through a scheme template index database, store pre-made templates, a disease index database, which is used to store index data of various diseases to provide benchmark support for scheme development, a data scheduling center, which is used to process and schedule data, and a clinical project database, which is used to store recorded clinical project data.

[0009] The third aspect of the application provides an optimization system, comprising: a processor coupled with a memory, the memory being used to store a program, when the program is executed by the processor, the system is made to execute the functions of the system as described in the first aspect with efficiency.

[0010] The fourth aspect of the application provides a clinical trial scheme design optimization method and system, the memory stores a computer program, and the computer program is executed by the processor to realize the functions of the system as described in the first aspect.

[0011] The one or more technical solutions provided in the application have at least the following technical effects or advantages:

[0012] The system in the embodiment of the application constructs by cross-detection group, combines the medication parameters and clinical data of the control group and the standard group (such as the combination of qualified medication of the standard group and qualified data of the control group), forms first and second cross-detection sets, effectively eliminates the interference of individual differences of volunteers on the effect of the drug through dynamic cross-validation, improves the accuracy and reliability of the test data, and reduces the result deviation caused by individual factors.

[0013] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the following specific embodiments of the present application can be implemented according to the content of the description, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application will be described. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0015] Figure 1 The method flowchart provided by the present application is shown in the following figure:

[0016] Figure 2 The system structure schematic diagram provided by the present application is shown in the following figure:

[0017] Figure 3 The structure schematic diagram of the electronic device provided by the present application is shown in the following figure.

[0018] In the figure: 300, electronic device; 301, memory; 302, processor; 303, communication interface; 304, bus architecture. DETAILED DESCRIPTION

[0019] The present application provides a clinical trial design optimization method and system, which is used to solve the technical problems of existing individual difference interference and lack of dynamic optimization.

[0020] In order to solve the above technical problems, the technical scheme provided by the present application is as follows:

[0021] The system of the present application builds a cross detection group, and cross combines the medication parameters and clinical data of the control group and the standard group (such as combining the qualified medication of the standard group with the qualified data of the control group), forms a first and second cross detection set, and effectively eliminates the interference of individual differences of volunteers on the effect of the drug through dynamic cross validation, improves the accuracy and reliability of the test data, and reduces the result deviation caused by individual factors.

[0022] After introducing the basic principles of this application, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0023] Example 1

[0024] like Figure 1 As shown, this application provides a method for optimizing clinical trial protocols, characterized in that it is applied to a clinical trial protocol design optimization system, the method comprising:

[0025] S100: Receives verification data submitted by physicians, analyzes it based on the protocol template database, and obtains clinical trial protocol templates;

[0026] In this embodiment of the application, before the formal design of the clinical trial protocol, the physician's identity needs to be verified. The safety and compliance of the clinical trial are judged based on the physician's information. Then, the physician sends a request, and the corresponding template data in the protocol template database is retrieved based on this information. For example, if physician A has taken over a medical trial project that requires a clinical trial and has already filed for record, then his access to the system will not be restricted. Then, the physician guides physician A to operate and send a template retrieval request. The system retrieves the corresponding database based on this request and returns the results.

[0027] The information entered by the physician should include physician information, the physician's selected template preferences, etc., and the system will receive instructions to retrieve the corresponding template.

[0028] Step S100 in the method provided in this application embodiment includes:

[0029] S110: Receives the authentication request submitted by the physician and sends the authentication request to the clinical project database for security authentication;

[0030] S120: Receive the security authentication request response returned by the clinical project database after receiving the security authentication, and send the security authentication request response to the protocol template database for template selection response;

[0031] The security authentication request response falls into two categories: if the authentication passes, the subsequent steps are executed; if the authentication fails, the subsequent steps are refused, and the physician resubmits the authentication request.

[0032] S130: Receive the template selection response result returned by the template database after receiving the security authentication response, and send the template response result to the physician terminal;

[0033] S140: The clinical trial protocol template returned by the receiving physician after receiving the template response result. The clinical trial protocol template includes baseline data of the control group, baseline data of the standard group, number information of the control group, number information of the standard group, feedback time indicators, and a set of drug information used.

[0034] In this embodiment, the system prioritizes security authentication of physicians to ensure the safety of the entire clinical trial. If secure, the clinical project database returns template data based on the information provided by the physician. Conversely, if security verification fails, no further steps are taken, and the physician must resubmit the verification request. Specifically, after identity security authentication on the physician's end, this authentication not only carries the security authentication request but also the template retrieval request entered by Physician A on the physician's end. The data continues to be sent to the clinical project database, and the system sends the request content submitted by the physician to the clinical project database. For example, if Physician A submits an identity verification request, the system prioritizes security verification of Physician A's information carried in the request in conjunction with the clinical project database. If verification is successful, the data continues to be transmitted to the clinical project database, and the corresponding template data is retrieved and returned.

[0035] S200: Receives volunteer medical record information from the volunteer database and obtains the data monitoring group set according to the clinical trial protocol template;

[0036] In this embodiment of the application, after confirming the template data, the template content needs to be filled in. Volunteer information is received from the volunteer database, and then volunteers are screened in conjunction with the clinical trial protocol template to obtain a data monitoring group set. For example, after determining the protocol, the volunteer database is connected to screen volunteers, those who meet the conditions are selected, and the information of these volunteers is output as the data monitoring group set.

[0037] The selected users were categorized based on baseline data from the control group and the standard group. The number of volunteers collected was controlled based on the number of volunteers in the control group and the standard group.

[0038] Step S200 in the method provided in this application embodiment includes:

[0039] S210: Receive volunteer medical record information and obtain the control group volunteer data set based on the control group baseline data by combining the volunteer medical record information with the control group baseline data;

[0040] S220: receiving the volunteer medical record information, and obtaining a standard group volunteer data set based on the standard group benchmark data according to the volunteer medical record information combined with the standard group benchmark data;

[0041] The control group volunteer data set and the standard group volunteer data set are taken as a data monitoring group set.

[0042] In the embodiment of the application, after the screening is completed, the system analyzes the volunteers, obtains a volunteer medical report, and performs secondary division on the volunteers combined with the control group benchmark data and the standard group benchmark data to obtain a control group volunteer data set and a standard group volunteer data set. Specifically, the control group volunteer data set and the standard group volunteer data set are segmented by a certain number. For example, a control group volunteer data set has a plurality of data, and the system segments the plurality of data according to an n-group method to obtain a plurality of sets, which are monitored separately to increase the accuracy of clinical data.

[0043] S300: sending the control group volunteer data set and the standard group volunteer data set as a data monitoring group set to a disease index database to obtain standard index information;

[0044] In the embodiment of the application, the disease index data is selected according to the information of the patients in the control group volunteer data set and the standard group volunteer data set, and the disease index database returns the standard index information according to the information. Specifically, the control group volunteer data set and the standard group volunteer data set contain data information of the user, including disease type, user body index and grouping information. For example, after the division of the volunteer data set and the standard group volunteer data set is completed, the data is sent to the disease index database, and different standard index information is returned according to the parameters of the data set.

[0045] Optionally, the standard index information can also be set to a preset fixed value. In actual clinical practice, by comparing the numerical change, the reference comparison effect can also be achieved.

[0046] S400: receiving a clinical volunteer index information set issued by a physician end according to the data monitoring group set combined with a feedback time index, obtaining volunteer clinical information combined with the standard index information, wherein the volunteer clinical information includes a control group clinical data set and a standard group clinical data set;

[0047] In the embodiments of the present application, there is a feedback time index in the system, and the data is periodically collected and recovered according to the feedback time index, and then is compared and referred. Specifically, when the feedback time index is reached, the volunteer data is collected by the physician according to the data set of the control group volunteers in the data monitoring group and the data set of the standard group volunteers, and is uploaded through the physician terminal. According to the uploaded data, the change of the index of the volunteer in the clinic can be judged to assist the physician. For example, the feedback time index set by the system is one month. When one month is reached, the system receives the user data information uploaded by the physician terminal. After one month of clinical medication, the index information set of the clinical volunteers is changed obviously. The system selects the drug with good practice data according to the change.

[0048] S500: receiving the standard group index qualified clinical medication parameter set and the control group index qualified clinical medication parameter set, and obtaining a cross detection group by combining the control group clinical data set;

[0049] Because the influence of individual physical factors cannot be excluded in the applied clinical trial, cross detection is needed;

[0050] The step S500 in the method provided by the embodiments of the present application includes:

[0051] S510: the control group clinical data set includes an index qualified control group clinical data set and an index unqualified control group clinical data set, the standard group clinical data set includes an index qualified standard group clinical data set and an index unqualified standard group clinical data set, the control group clinical data set is sent to the scheme template database to obtain a medication parameter set, and the medication parameter set includes the standard group index qualified clinical medication parameter set, the control group index qualified clinical medication parameter set, the standard group index unqualified clinical medication parameter set, and the control group index unqualified clinical medication parameter;

[0052] S520: the standard group index qualified clinical medication parameter set is combined with the index qualified control group clinical data set as a first cross detection set, the control group index qualified clinical medication parameter set is combined with the qualified standard group clinical data set as a second cross detection set, and the first cross detection set and the second cross detection set are output as a cross detection group set;

[0053] The medication information of each comparison group in the clinical data is obtained by the system. These information is re-bound with the users in the reference group to obtain the first cross detection set and the second cross detection set. In this way, the influence of individual factors on the drug can be excluded, so as to ensure the accuracy of the experimental data results.

[0054] S600: The receiving physician sends the cross-indicator set based on the cross-test group and the feedback time index to the disease index database for optimization and verification, and obtains the optimized clinical information set as the new volunteer clinical information to repeat the above steps.

[0055] The optimization and verification of the above structure mainly involves a feedback time indicator after the cross-test group is constructed and output. The physician uploads new volunteer clinical information, and the system re-evaluates the cross-test group data based on the new volunteer clinical information and disease indicator data, and repeats the above steps.

[0056] S610: Receive the optimization response result returned by the disease indicator database after receiving the optimization verification. The optimization response result has the following two results: if the optimization response is qualified, obtain the optimized clinical information; if the optimization response is unqualified, output the adjustment opinion and send the adjustment opinion to the physician for modification of the response.

[0057] The S600 also includes:

[0058] S620: Set termination conditions, combine the set of cross-indicators with the termination conditions to obtain the final clinical results, and send the final clinical results to the physician for modification response;

[0059] S700: The receiving physician receives the adjustment opinions and the adjustment data returned by the final clinical results. It combines the adjustment data with the clinical trial protocol template to obtain the reference protocol template, analyzes the reference protocol template, constructs a new clinical trial protocol template, and sends the new clinical trial protocol template to the protocol template database for storage.

[0060] In this embodiment, after receiving the adjustment suggestions, the physician will select the data to be adjusted based on their experience, overwrite the data group that was not qualified in the original output, and at the same time, overwrite the data in the template with this adjustment suggestion. Specifically, the scope of the adjustment suggestions includes user data and their medication data.

[0061] Example 2

[0062] Based on the same inventive concept as the clinical trial protocol design optimization method and system in the foregoing embodiments, such as Figure 2 As shown, this application provides a method and system for optimizing clinical trial protocol design, wherein the method and system for optimizing clinical trial protocol design includes:

[0063] The physician side provides an interactive platform for physicians, authenticating their identities and allowing them to upload opinions and data to assist in the development of treatment plans.

[0064] The scheme template database is used to store template data and prefabricated templates through the scheme template indicator database.

[0065] a disease index database for storing index data of various diseases to provide benchmark support for scheme making;

[0066] a data scheduling center for processing and scheduling data.

[0067] Embodiment Three

[0068] Based on the same inventive concept as the clinical trial scheme design optimization method and system in the foregoing embodiments, the present application further provides a clinical trial scheme design optimization method and system computer readable memory, the memory having a computer program stored thereon, the computer program being executed by a processor to implement the method in Embodiment One.

[0069] Exemplary electronic device

[0070] The electronic device of the present application will be described below with reference to Figure 3

[0071] Based on the same inventive concept as the clinical trial scheme design optimization method and system in the foregoing embodiments, the present application further provides an optimization system, comprising: a processor coupled with a memory, the memory being used to store a program, when the program is executed by the processor, the system is caused to execute the steps of the method in Embodiment One.

[0072] The electronic device 300 comprises a processor 302, a communication interface 303, and a memory 301. Optionally, the electronic device 300 can further comprise a bus architecture 304. The communication interface 303, the processor 302, and the memory 301 can be connected to each other through the bus architecture 304; the bus architecture 304 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus architecture 304 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 In the figure, only one thick line is used to represent the bus architecture 304, but it does not mean that there is only one bus or one type of bus for data transmission based on the video stream line.

[0073] ​The processor 302 can be a CPU, a microprocessor, a SIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0074] The communication interface 303, using any transceiver-like device, is used to communicate with other devices or computer networks, such as an Ethernet network, a radio access network (RAN), a wireless local area network (WLAN), a wired access network, etc.

[0075] The memory 301 can be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium capable of storing desired program code in the form of instructions or data structures and that can be accessed by a computer, but not limited to. The memory can exist independently, connected to the processor through the bus architecture 304. The memory can also be integrated with the processor.

[0076] The memory 301 is used to store computer execution instructions for executing the program of the present application, and the processor 302 is used to control the execution. The processor 302 is used to execute the computer execution instructions stored in the memory 301, thereby realizing the SIC provided by the above-mentioned embodiments of the present application.

[0077] Those skilled in the art can understand that various numbers such as first, second, etc. involved in the present application are only for the convenience of description and do not limit the scope of the present application, nor indicate the order of sequence. The association relationship of "and / or" describing the associated objects indicates that there can be three relationships, for example, A and / or B can represent the three cases of A existing alone, A and B existing together, and B existing alone. The character " / " generally represents the "or" relationship of the associated objects before and after it. "At least one" means one or more. At least two means two or more. "At least one", "any one" or the like means any combination of these items, including any combination of single item or multiple items. For example, at least one (one, kind) of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0078] In the above embodiments, all or part can be realized by software, hardware, firmware, or any combination thereof. When realized by software, all or part can be realized in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, the computer program instructions produce all or part of the processes or functions described in the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be executed on a single computer, or distributed on multiple computers. The computer instructions can be stored in a computer readable storage medium, or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. integrated with one or more available media. The available medium can be a magnetic medium (for example, floppy disk, hard disk, magnetic tape), optical medium (for example, DVD), or semiconductor medium (for example, solid state disk (SSD)) and the like.

[0079] The computer instructions can be stored in a computer readable storage medium, or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. integrated with one or more available media. The available medium can be a magnetic medium (for example, floppy disk, hard disk, magnetic tape), optical medium (for example, DVD), or semiconductor medium (for example, solid state disk (SSD)) and the like.

[0080] The various illustrative logical blocks, modules, and circuits described in connection with the application can be implemented or performed with a general purpose processor, a digital signal processor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor can be a microprocessor, but, in the alternative, the general purpose processor can be any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, e.g., a combination of a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other such configuration.

[0081] The steps of a method or algorithm described in connection with the present disclosure can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium can be coupled to the processor, such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a terminal. In the alternative, the processor and the storage medium can reside as discrete components in a terminal. The steps of a method or algorithm can be embodied in a software module that can be executed by either a processor, or a computer. The software module can cause a computer or other programmable apparatus to perform a series of operations to produce computer-implemented processing, such that the instructions which execute the software module provide processes for implementing the functions described herein. Figure 1 The flow or flows and / or blocks Figure 1 The steps of a method or algorithm can be embodied in a software module that can be executed by either a processor, or a computer. The software module can cause a computer or other programmable apparatus to perform a series of operations to produce computer-implemented processing, such that the instructions which execute the software module provide processes for implementing the functions described herein.

[0082] While the application has been described in connection with specific features thereof, it will be evident that many modifications, and the like, can be made thereto without departing from the spirit and scope of the application. Accordingly, it is intended that all such modifications, changes, and equivalents come within the scope of the following claims. It will be obvious, however, to those having ordinarily skill in the art that with the advance of technological ages, many changes and modifications can be made.

Claims

1. A method for optimizing a clinical trial protocol design, comprising a set of methods for optimizing a clinical trial protocol, which are applied to a system for optimizing a clinical trial protocol design, characterized in that, The method comprises the following steps: S100: receiving verification data submitted by a physician end, analyzing based on a scheme template database, and obtaining a clinical trial scheme template; S200: receiving volunteer medical record information sent by a volunteer database, and obtaining a data monitoring group set according to the clinical experiment scheme template; S300: sending the control group volunteer data set and the standard group volunteer data set to a disease index database as the data monitoring group set, and obtaining standard index information; S400: receiving a clinical volunteer index information set sent by the physician end according to the data monitoring group set in combination with a feedback time index, obtaining volunteer clinical information in combination with the standard index information, wherein the volunteer clinical information comprises a control group clinical data set and a standard group clinical data set; S500: receiving a standard group index qualified clinical medication parameter set and a control group index qualified clinical medication parameter set, and obtaining a cross detection group in combination with the control group clinical data set; S600: receiving a cross index set sent by the physician end according to the cross detection group in combination with the feedback time index, sending the cross index set to the disease index database for optimization verification, and obtaining an optimized clinical information set as new volunteer clinical information to re-execute the above steps; S610: receiving an optimization response result returned by the disease index database after optimization verification, wherein the optimization response result has the following two results: the optimization response is qualified, the optimized clinical information is obtained, the optimization response is unqualified, and adjustment suggestions are outputted and sent to the physician end for; S700: receiving adjustment data returned by the physician end after receiving the adjustment suggestions, obtaining a reference scheme template in combination with the clinical trial scheme template, analyzing the reference scheme template, constructing a new clinical trial scheme template, and sending the new clinical trial scheme template to the scheme template database for storage.

2. The method of optimizing a clinical trial protocol according to claim 1, wherein, The S100 comprises: S110: receiving an identity verification request submitted by the physician end, and sending the identity verification request to a clinical project database for security authentication; S120: receiving a security authentication request response returned by the clinical project database after receiving the security authentication, and sending the security authentication request response to the scheme template database for template selection response; The security authentication request response is divided into two cases: if the verification is passed, the subsequent steps are continued to be executed; if the verification fails, the subsequent steps are refused to be executed, and the physician end re-submits the identity verification request; S130: receiving a template selection response result returned by the template database after receiving the security authentication response, and sending the template response result to the physician end; S140: receiving a clinical trial scheme template returned by the physician end after receiving the template response result, wherein the clinical trial scheme template comprises control group benchmark data, standard group benchmark data, control group quantity information, standard group quantity information, a feedback time index, and a drug information set.

3. The method of optimizing a clinical trial protocol according to claim 1, wherein, The S200 comprises: S210: receiving volunteer medical record information, obtaining a control group volunteer data set in combination with control group benchmark data based on the volunteer medical record information and the control group benchmark data; S220: receiving the volunteer medical record information, and obtaining a standard group volunteer data set based on the standard group benchmark data according to the volunteer medical record information combined with the standard group benchmark data; The control group volunteer data set and the standard group volunteer data set are taken as a data monitoring group set.

4. The method of designing a clinical trial protocol according to claim 1, wherein, The S500 includes: S510: the control group clinical data set includes an index qualified control group clinical data set and an index unqualified control group clinical data set, the standard group clinical data set includes an index qualified standard group clinical data set and an index unqualified standard group clinical data set, and the control group clinical data set is sent to a scheme template database to obtain a drug use parameter set, the drug use parameter set includes a standard group index qualified clinical drug use parameter set, a control group index qualified clinical drug use parameter set, a standard group index unqualified clinical drug use parameter set, and a control group index unqualified clinical drug use parameter set.

5. The method of optimizing a clinical trial protocol according to claim 4, wherein, The S500 further includes: S520: the standard group index qualified clinical drug use parameter set is combined with the index qualified control group clinical data set as a first cross-detection set, the control group index qualified clinical drug use parameter set is combined with the qualified standard group clinical data set as a second cross-detection set, and the first cross-detection set and the second cross-detection set are combined as a cross-detection group and output.

6. The method of designing a clinical trial protocol according to claim 1, wherein, The clinical trial scheme design optimization system includes: A physician end for providing an interactive platform for physicians, authenticating the physician identity, and uploading opinion data by the physician to assist in scheme development; A scheme template database for storing template data through a scheme template index database and storing prefabricated templates; A disease index database for storing index data of various diseases to provide benchmark support for scheme development; A data scheduling center for processing and scheduling data.

7. An optimization system, comprising: It includes: A processor coupled with a memory, the memory being used to store a program, when the program is executed by the processor, the system executes the steps of the system as claimed in any one of claims 1 to 6.

8. A computer readable memory characterized by: The memory stores a computer program, and the computer program is executed by the processor to realize the steps of the system as claimed in any one of claims 1 to 6.

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