Method, device and equipment for generating clinical trial plan based on BOPII design decision

Abstract

The present application relates to the field of clinical trials, and in particular to a method, device and equipment for generating clinical trial plans based on Bayesian Optimal Phase II (BOPII) design decisions. First, basic data for generating clinical trial plans based on BOPII design decisions are obtained; then, basic elements of clinical trial plans based on BOPII design decisions are formulated; based on the basic elements, a basic element flow chart and report of clinical trial plans based on BOPII design decisions are formulated; based on the flow chart and report, a database structure description file of clinical trial plans based on BOPII design decisions is formulated; based on the database structure description file, a database of clinical trial plans based on BOPII design decisions is formulated; finally, based on the database, a clinical trial plan based on BOPII design decisions is generated. The present invention can automatically generate clinical trial plans based on BOPII design decisions, avoiding manual production of clinical trial plans based on BOPII design decisions, thereby shortening the time of clinical trial development and reducing clinical trial costs.

Description

Technical Field

[0001] The present application relates to the technical field of clinical trials, and in particular to a method, device and equipment for designing and deciding clinical trial plans based on Bayesian Optimal Phase II (BOPII). Background Art

[0002] Clinical trials are systematic trials that aim to discover or verify the clinical medicine, pharmacology, and other pharmacodynamic effects, adverse reactions, or absorption, distribution, metabolism, and excretion of an investigational drug in order to determine the efficacy and safety of the drug.

[0003] A clinical trial protocol is a document that describes the purpose, design, methodology, statistical considerations, and organization and implementation of a clinical trial. A trial protocol usually also includes the background and theoretical basis of the clinical trial, which can be given in other reference documents. The trial protocol describes in detail how a clinical trial should be implemented, such as what type of patients should be enrolled, what the design and purpose of the trial is, how to use the trial drugs, how to process data, how to deal with adverse events, etc.

[0004] The current BOPII design can handle the following Phase II designs: binary efficacy endpoints, nested efficacy endpoints, common multiple efficacy endpoints, and joint monitoring of efficacy and toxicity endpoints. The BOPII design has more advantages, including: providing a more flexible framework to monitor multiple events simultaneously, including nested or common primary endpoints; precisely controlling the type I error rate and optimizing a specific objective function, thereby bridging the gap between Bayesian design and frequency design, making the proposed Bayesian optimization design easier for a wide range of users and regulators to use; allowing the critical value of the termination rule to change with the mid-term sample size, thereby improving the design's test power.

[0005] However, current clinical trial plans based on BOPII design decisions are mostly generated manually, which is not only time-consuming and slow, but also increases the human cost of clinical trials. Summary of the invention

[0006] In order to solve the above problems, the present application provides a method, device and apparatus for designing and deciding clinical trial plans based on Bayesian Optimal Phase II (BOPII). The present application is implemented through the following technical solutions:

[0007] In a first aspect, the present application provides a method for designing a clinical trial plan based on BOPII, comprising:

[0008] Obtain basic data for generating clinical trial protocols based on BOPII design decisions;

[0009] Formulate and save the basic elements of the clinical trial plan based on BOPII design decisions based on the basic data obtained;

[0010] Formulate and save the basic elements flow chart and report form of the clinical trial plan based on BOPII design decision-making according to the basic elements;

[0011] Formulate and save the database structure description document of the clinical trial plan based on BOPII design decision according to the basic element flow chart and report form;

[0012] Develop and save a database of clinical trial plans based on BOPII design decisions according to the database structure description document;

[0013] Generate clinical trial plans based on BOPII design decisions according to the database.

[0014] Furthermore, the method is characterized in that the basic data includes:

[0015] Population data, intervention data, control group selection data, response variable data, statistical analysis method data, bias reduction method data, study purpose data, study type data, data source data, and BOPII design calculation algorithm data.

[0016] Furthermore, the method is characterized in that the data standards followed by the basic data include:

[0017] International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use standards and / or US Food and Drug Administration standards and / or National Drug Administration Center for Drug Evaluation standards.

[0018] Furthermore, the method described is characterized in that the basic elements include: clinical trial data of similar drugs and preclinical data of the drug.

[0019] Furthermore, the method is characterized in that the data of the basic elements contain variables and variable labels, and the variable labels are composed of character strings.

[0020] Furthermore, the method is characterized in that, after obtaining the basic data, the method further comprises:

[0021] Get and set the project environment, project information, various file storage locations and test data reading cycle;

[0022] The project environment and the project information are set according to the clinical trial project.

[0023] In a second aspect, the present application provides a device for generating a clinical trial plan based on BOPII design decision-making, characterized by comprising: an electronic data acquisition module, a data storage module, a central data integration module and a generation module;

[0024] The electronic data acquisition module is used to collect all basic data involved in the clinical trial plan based on BOPII design decision;

[0025] The data storage module is used to store the basic data;

[0026] The central data integration module is used to generate an intermediate file based on the basic data;

[0027] The generation module is used to integrate the intermediate files and generate a clinical trial plan based on BOPII design decisions.

[0028] In a third aspect, the present application provides a device for generating a clinical trial plan based on BOPII design decision-making, characterized in that it includes a processor and a memory connected to the processor;

[0029] The memory is used to store a program, and the program is used to implement at least one of the methods for generating a clinical trial plan based on BOPII design decision in the above embodiments;

[0030] The processor is used to call and execute the program stored in the memory.

[0031] The present application provides a computer-readable storage medium, characterized in that executable instructions are stored thereon, which, when executed by a processor, enable the processor to implement the method described in any one of the above embodiments.

[0032] The present invention adopts the above technical solution, and the beneficial effects that can be achieved include:

[0033] The present invention provides a method, device, equipment and readable storage medium for designing and deciding clinical trial plans based on BOPII. The present invention solves the problem that existing algorithms cannot meet the needs of clinical trial design. All basic data involved in the clinical trial plans based on BOPII are collected through an electronic data collection module. Then, according to the collected basic data, basic elements of the clinical trial plans based on BOPII are formulated; a flow chart and a report table of basic elements of the clinical trial plans based on BOPII are formulated according to the basic elements; a database structure description file of the clinical trial plans based on BOPII is formulated according to the flow chart and the report table; a database of the clinical trial plans based on BOPII is formulated according to the database structure description file; and a clinical trial plans based on BOPII are generated according to the database. The present invention can automatically generate clinical trial plans based on BOPII, avoid manually making clinical trial plans based on BOPII, thereby shortening the time of clinical trial development and reducing clinical trial costs.

[0034] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0036] Figure 1 A schematic diagram of the steps for designing a clinical trial protocol based on BOPII;

[0037] Figure 2 A schematic diagram of the generation module for clinical trial plan design based on BOPII;

[0038] Figure 3 Schematic diagram of the apparatus for the generation of clinical trial protocols for BOPII-based design decisions. DETAILED DESCRIPTION

[0039] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. 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 implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0040] A method for designing a clinical trial plan based on Bayesian optimal phase II (BOPII) design, characterized by comprising:

[0041] S11. Obtain basic data for generating clinical trial plans based on BOPII design decisions;

[0042] The Bayesian optimal phase II design is referred to as BOPII design.

[0043] In practical applications, the basic data can be collected through an electronic data collection system. The electronic data collection system contains a basic element data module for formulating a clinical trial plan based on BOPII design decisions, which is used to collect all relevant data involved in the clinical trial plan based on BOPII design decisions. Each data can be automatically collected through the electronic data collection system or can be edited and filled in by personnel to realize the collection of basic element data.

[0044] S12. Formulate and save the basic elements of the clinical trial plan based on BOPII design decision-making according to the basic data obtained;

[0045] S13. Develop and save the basic elements flow chart and report form of the clinical trial design plan based on BOPII design decision-making;

[0046] S14. Prepare and save the database structure description document of the clinical trial plan based on BOPII design decision according to the basic element flow chart and report form;

[0047] S15. Formulate and save a database for clinical trial plans based on BOPII design decisions according to the database structure description document;

[0048] S16. Generate a clinical trial plan based on BOPII design decisions according to the database.

[0049] In practical applications, basic data for generating clinical trial plans based on BOPII design decisions are first obtained; then basic elements of clinical trial plans based on BOPII design decisions are formulated; based on the basic elements, flow charts and reports of clinical trial plans based on BOPII design decisions are formulated; based on the flow charts and reports, database structure description documents of clinical trial plans based on BOPII design decisions are formulated; based on the database structure description documents, a database of clinical trial plans based on BOPII design decisions is formulated; finally, based on the database, a clinical trial plan based on BOPII design decisions is generated. Through the above methods, clinical trial plans based on BOPII design decisions can be automatically generated, avoiding manual preparation of clinical trial plans based on BOPII design decisions, thereby shortening the time of clinical trial development and reducing clinical trial costs.

[0050] Furthermore, the method is characterized in that the basic data includes:

[0051] Population data, intervention data, control group selection data, response variable data, statistical analysis method data, bias reduction method data, study purpose data, study type data, data source data, and BOPII design calculation algorithm data.

[0052] In the above specific embodiments, the population data includes: The research population should be selected to support the purpose of the study and defined by the inclusion and exclusion criteria of the study;

[0053] The intervention data included: various treatments;

[0054] The control group selection data includes: the drug efficacy of the study may be the efficacy compared with not receiving drug treatment or with receiving other treatments. Preferably, the control group data source may come from inside or outside the study;

[0055] The response variable data include: response variables are subject-level attributes of interest that may be affected by the drug, response variables may involve pharmacokinetics, pharmacodynamics, effectiveness, safety, or use of the drug after approval, including measures consistent with risk minimization, and study endpoints are response variables selected to evaluate the effect of the drug;

[0056] The bias reduction method data include: the research design should address the bias sources that may undermine the reliability of the results. Although different types of studies are affected by different bias sources, the present invention describes the more common sources. ICH E9 mainly discusses the principles of controlling and reducing bias in the context of interventional studies;

[0057] The research purpose data include: the statistical analysis of the research includes the important factors necessary to achieve the research objectives, and the research plan should include a statistical methods section that is appropriate to the objectives and research design;

[0058] The data source data include: Research data can be roughly divided into two categories: (1) data generated specifically for this research; (2) data obtained from outside this research;

[0059] The BOPII design calculation algorithm data includes: the algorithm summarized historically, and all data calculated by all BOPII design algorithms are included in this section.

[0060] Furthermore, the method is characterized in that the data standards followed by the basic data include:

[0061] International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use standards and / or US Food and Drug Administration standards and / or National Drug Administration Center for Drug Evaluation standards.

[0062] In the above specific embodiments, data collection in the process of formulating the basic elements of the clinical trial plan based on BOPII design decision-making has strict regulatory requirements and standardized content, and mainly refers to the relevant laws and regulations issued by the International Council for Harmonization of Technical Registration of Pharmaceuticals for Human Use, the U.S. Food and Drug Administration, and the Drug Review Center of the National Medical Products Administration as guiding principles and implementation standards.

[0063] Preferably, the collection of basic data elements of clinical trial protocols based on BOPII design decisions is based on the requirements of the quality management standards for review reports from the U.S. Food and Drug Administration and the Center for Drug Evaluation of the National Medical Products Administration.

[0064] Furthermore, the method described is characterized in that the basic elements include: clinical trial data of similar drugs and preclinical data of the drug.

[0065] Furthermore, the method is characterized in that the data of the basic elements contain variables and variable labels, and the variable labels are composed of character strings.

[0066] Furthermore, the method is characterized in that, after obtaining the basic data, it also includes setting the project environment, project information, various file storage locations and test data reading cycle;

[0067] The project environment and the project information are set according to the clinical trial project.

[0068] Through the above technical scheme, the present invention formulates a clinical trial plan data module based on BOPII design decisions based on professional experience, domestic and international industry regulations, and obtains a high-quality, complete, accurate and error-free clinical trial plan based on BOPII design decisions by collecting clinical trial plan data based on BOPII design decisions and integrating the clinical trial plan data based on BOPII design decisions, thereby being able to automatically generate a clinical trial plan based on BOPII design decisions, so as to guide the design, execution, analysis, reporting and interpretation of clinical trials, and ensure the accurate and efficient completion of the design, execution, analysis, reporting and interpretation of clinical trials.

[0069] Good clinical trial planning and conduct stems from attention to established principles of clinical research, which include protection of the rights, safety, and well-being of research subjects and scientific standards, such as: the need for clear, predetermined study objectives to address the primary scientific question; selection of appropriate subjects with the disease, condition, or molecular / genetic profile being studied; use of methods that minimize bias, such as randomization, blinding or masking, and / or control for confounding; and endpoints that are clear and measurable, and methods for assessing those endpoints that are accurate and can be implemented with minimal reporting or measurement bias.

[0070] The purpose of Phase II clinical trials is to evaluate the preliminary efficacy of new treatments and determine whether such treatments have the potential for large-scale Phase III randomized controlled clinical studies. The basic design features of Phase IIa clinical trials are early ineffective termination and mid-term go / no-go decisions to prevent too many patients from being exposed to potentially ineffective treatments. There have been many frequency designs and Bayesian designs applied to Phase IIa clinical trials at home and abroad. At present, the famous frequency design Simon two-stage design is the most widely used in domestic clinical research. Under the null hypothesis that the treatment is ineffective, given the type I and type II error rates, it can minimize the expected sample size or maximum sample size. If you want to do more mid-term observations, statisticians can also refer to other related studies including Fleming's multi-stage test, Ensign's optimal three-stage design and Chen's optimal three-stage design.

[0071] On the other hand, from the perspective of Bayesian design, one way of ineffective monitoring is to make go / no-go decisions based on the posterior probability of the event of interest. Based on this idea, Thall and Simon proposed a Bayesian Phase IIa design. If the interim data show that the remission rate of the treatment is highly likely to be less than the pre-specified critical value, the trial will be terminated; otherwise, the next interim observation will be entered. The principle of this method is intuitive and has been widely used in cancer centers such as MD Anderson in the United States. Based on the posterior probability, Heitjan proposed to use "persuasive probability" to determine whether a new therapy has research and development prospects. Tan and Machin proposed two Bayesian two-stage designs, which simulated the multi-stage design of the frequentist school. Cai, Liu and Yuan proposed that delayed efficacy outcomes can be handled by using multiple imputation methods. Lee and Liu also proposed another Bayesian Phase IIa design based on predicted probability, which can predict the final data based on the interim data at any time and calculate the probability of the final trial success. However, most of the above designs, whether based on posterior probability or predicted probability, focus on a binary efficacy endpoint, such as tumor response rate. But with the emergence of new molecular targeted drugs and immunotherapy, the primary endpoint has become more complex and can be ordered or multivariate.

[0072] The following are four common Phase II trials with different types of endpoints. The BOPII design will use a unified model to handle the following Phase II designs.

[0073] Example 1: Binary efficacy endpoint: A Phase II clinical trial to evaluate the efficacy of metformin in patients with recurrent small cell lung cancer. The primary endpoint is the objective response rate (ORR) of ASO-treated patients with recurrent small cell lung cancer (SCLC) (defined using RECIST version 1.1 for solid tumor evaluation criteria). Based on historical data, the null hypothesis of ORR 5% is considered ineffective if it holds, and the alternative hypothesis of ORR 20% is considered promising for research and development. This example is used to illustrate a standard situation with a binary efficacy endpoint.

[0074] Example 2: Nested efficacy endpoints: A phase II clinical trial was designed to evaluate the efficacy of a novel humanized monoclonal antibody in patients with Hodgkin lymphoma who had failed autologous stem cell transplantation. The effectiveness of lymphoma treatment was defined using the revised International Working Group on Malignant Lymphoma criteria, with one of four reduced levels of classification selected, including: complete remission (CR), defined as the disappearance of all evidence of disease; partial remission (PR), defined as regression of measurable lesions without new lesions; stable disease (SD), defined as failure to meet the criteria for CR, PR, or progressive disease (PD); progressive disease (PD), defined as any evidence of new lesions or a 50% increase in lesion volume from the lowest point of the previously affected site. In this trial, although both CR and PR were considered favorable efficacy responses, CR was actually preferred. The null hypothesis was Pr(CR+PR) 30% and Pr(CR) 15%, if established, the treatment was considered ineffective. The alternative hypothesis is Pr(CR+PR)50% or Pr(CR)25%. If it is established, the therapy is considered to have research and development prospects, where the endpoint of the second condition is nested in the endpoint of the first condition.

[0075] Example 3: Common multiple efficacy endpoints: A phase II clinical trial, the protocol is called GOG 0229E, the main purpose of which is to study the efficacy of bevacizumab in patients with recurrent or persistent endometrial cancer. The trial has two common primary efficacy endpoints: objective response rate (ORR) and the probability of 6-month disease progression (or death)-free survival (PFS6). The objective response rate is defined using the Solid Tumor Evaluation Criteria (RECIST) 1.1. Progression-free survival (PFS) is defined as the time from the start of treatment to the occurrence of disease progression or death from any cause. The original hypothesis is ORR 10% and PFS6 15%. If it is established, the treatment is considered ineffective. The difference in clinically significant improvement of the two indicators is 20%, so the alternative hypothesis is ORR ≥ 30% or PFS6 ≥ 35%. If it is established, the therapy is considered to have research and development prospects.

[0076] Example 4: Joint monitoring of efficacy and toxicity endpoints: A phase II clinical trial, the main purpose of which is to evaluate the efficacy of low-dose clofarabine and cytarabine combined treatment of patients with high-risk myelodysplastic syndrome who have relapsed or are insensitive to hypomethylating drugs. The primary efficacy endpoint is the CR rate defined by the 2006 revised International Working Group criteria combined with monitoring the safety of treatment, with the rate of grade 3 toxicity related to the study drug as a joint endpoint. If the CR rate is >20% and the toxicity rate is <30%, the therapy is considered promising for development.

[0077] Heng Zhou et al. proposed a flexible Bayesian optimal phase II (BOPII) design in 2017 that can handle the above trial scenarios. The BOPII design uses a Dirichlet polynomial model to include different types of endpoints. At each interim stage, a go / no-go decision is made by evaluating the posterior probability of the event. The BOPII design can accurately control the type I error rate and is optimal in a sense, including optimizing the test power under the alternative hypothesis of a fixed sample size or minimizing the expected sample size under the null hypothesis. Thall and colleagues proposed a Bayesian sequential monitoring design for multiple primary endpoints (e.g., toxicity and efficacy). Compared with these designs, the BOPII design has more advantages, including:

[0078] (i) It provides a more flexible framework to monitor multiple events simultaneously, including nested or co-primary endpoints; (ii) It precisely controls the type I error rate and optimizes a specific objective function, thus bridging the gap between Bayesian and frequentist designs, making the proposed Bayesian optimization design more accessible to a wide range of users and regulators;

[0079] (iii) Simulation studies show that allowing the critical value of the stopping rule to vary with the mid-term sample size improves the test power of the design.

[0080] See also Figure 2 , the present invention also provides a device for generating a clinical trial plan based on BOPII design decision, characterized in that it comprises: an electronic data acquisition module (1), a data storage module (2), a central data integration module (3) and a generation module (4);

[0081] The electronic data acquisition module (1) is used to acquire all basic data involved in designing and deciding clinical trial plans based on BOPII;

[0082] The data storage module (2) is used to store the basic data;

[0083] The central data integration module (3) is used to generate an intermediate file based on the basic data;

[0084] The generation module (4) is used to integrate the intermediate files and generate a clinical trial plan based on BOPII design decision.

[0085] In the above embodiment, the electronic data collection module (1) is used to collect all relevant data involved in the clinical trial plan based on BOPII design decision, specifically including population, intervention, control group selection, response variable, statistical analysis method, bias reduction method, research purpose, research type, data source and BOPII design calculation algorithm.

[0086] Preferably, the data storage module (2) is not only used to store basic data, but also capable of storing intermediate files.

[0087] The central data integration module can formulate and save the basic elements of the clinical trial plan based on BOPII design decision according to the basic data obtained; formulate and save the basic elements of the clinical trial plan based on BOPII design decision according to the basic elements; formulate and save the database structure description file of the clinical trial plan based on BOPII design decision according to the basic elements flowchart and report table; formulate and save the database of the clinical trial plan based on BOPII design decision according to the database structure description file. Finally, the generation module generates the clinical trial plan based on BOPII design decision.

[0088] See also Figure 3 The present application provides a device for generating a clinical trial plan based on BOPII design decision, characterized in that it comprises a processor (12) and a memory (11) connected to the processor;

[0089] The memory (11) is used to store a program, and the program is used to implement at least one of the clinical trial protocol generation methods in the above embodiments;

[0090] The processor (12) is used for calling and executing the program stored in the memory.

[0091] The above embodiment can automatically generate a clinical trial plan based on BOPII design decisions. The processor (12) is a computing device that executes programs stored in a memory. The processor (12) implements various functions of the electronic device by executing applications. The memory is a RAM that is a volatile storage element that temporarily stores applications executed by the processor and data used when executing the applications.

[0092] Preferably, the automatic generation device also includes a hard disk (13), which can be a large-capacity and non-volatile storage device such as a mechanical hard disk (HDD) or a flash hard disk (SSD). The hard disk is used for long-term storage of data used by the processor when executing a program, as well as the program executed by the processor. A specific application example is that the program is read from the hard disk, loaded into the memory, and executed by the processor, thereby realizing various functions of the electronic device.

[0093] The automatic generation device also includes an input interface (14), which is an interface connected to an input device such as a keyboard and a mouse and receives input from an administrator. It also includes an output interface, which is an interface connected to a display and outputs results in a form that can be viewed by the administrator. The input interface and output interface of the electronic device are only used by the administrator to install and operate the application program of the electronic device. Other users use the input device and output device provided by the terminal connected to the electronic device via the network interface (16) to operate the system.

[0094] The application program executed by the processor of the automatic generation device is provided to the electronic device via a network and stored in the hard disk.

[0095] The automatic generation device is a computer system constructed on one or more physical computers, and can also run on a virtual computer constructed on multiple physical computer resources.

[0096] In addition, the present invention also provides a computer-readable storage medium on which a program product capable of implementing the above method of this specification is stored. In some possible embodiments, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal, the program code is used to enable the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the above embodiment section of this specification.

[0097] According to an embodiment of the present invention, a program product for implementing the above-mentioned method for automatically generating a clinical trial plan based on BOPII design decision can be implemented in a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In the present application, a readable storage medium can be a tangible medium that is recognized to contain or store a program, and the program can be used by or in combination with an instruction execution system, an apparatus or a device.

[0098] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), a pluggable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0099] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0100] The program code contained on the readable medium may be transmitted using any appropriate medium including but not limited to wireless, wired, optical cable, radio frequency, etc., or any suitable combination of the foregoing.

[0101] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0102] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0103] It should be noted that, in the description of this application, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0104] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0105] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0106] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0107] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0108] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0109] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0110] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for generating a clinical trial plan based on BOPII design decision, characterized in that: include: Obtain basic data for generating clinical trial protocols based on BOPII design decisions; Construct and save the basic elements of the clinical trial plan based on BOPII design decision according to the basic data; According to the basic elements, a basic element flow chart and a report table of the clinical trial plan designed and decided based on BOPII are constructed and saved; Construct and save a database structure description file of a clinical trial plan based on BOPII design decision according to the basic element flow chart and report table; Constructing and saving a database for clinical trial plans based on BOPII design decisions according to the database structure description file; A clinical trial plan based on BOPII design decision is generated according to the database.

2. The method according to claim 1, characterized in that The basic data include: Population data, intervention data, control group selection data, response variable data, statistical analysis method data, bias reduction method data, study purpose data, study type data, data source data, and BOPII design calculation algorithm data.

3. The method according to claim 1, characterized in that The data standards followed by the basic data include: International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use standards and / or US Food and Drug Administration standards and / or National Drug Administration Center for Drug Evaluation standards.

4. The method according to claim 1, characterized in that: The basic elements include: clinical trial data of similar drugs and preclinical data of this drug.

5. The method according to claim 4, characterized in that The data of the basic elements include variables and variable labels, and the variable labels are composed of character strings.

6. The method according to claim 1, characterized in that After obtaining the basic data, the method further includes: Get and set the project environment, project information, file storage location and test data reading cycle; The project environment and the project information are set according to the clinical trial project.

7. A device for generating a clinical trial plan based on BOPII design decision, characterized in that: include: Electronic data collection module, data storage module, central data integration module and generation module; The electronic data acquisition module is used to collect all basic data involved in the clinical trial plan based on BOPII design decision; The data storage module is used to store the basic data; The central data integration module is used to generate an intermediate file based on the basic data; The generation module is used to integrate the intermediate files and generate a clinical trial plan based on BOPII design decisions.

8. A device for generating a clinical trial plan based on BOPII design decision, characterized in that: comprising a processor and a memory connected to the processor; The memory is used to store a program, and the program is used to implement at least one of the methods for generating a clinical trial plan based on BOPII design decision-making as claimed in any one of claims 1 to 6; The processor is used to call and execute the program stored in the memory.

9. A computer-readable storage medium, characterized in that: Executable instructions are stored thereon, and when the instructions are executed by a processor, the processor implements the method according to any one of claims 1 to 6.

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