Interactive network-based drug management and subject randomization method and system

Abstract

The application discloses a medicine management and subject random allocation method and system based on an interactive network, belongs to the technical field of randomization allocation, and comprises the following steps: firstly, original subject baseline data is acquired, data preprocessing is conducted on the original subject baseline data, subject baseline data is obtained, and test scene information is obtained; then, based on the test scene information, subject randomization strategies are correspondingly selected from a randomization strategy library; the subject randomization strategies are utilized to generate a subject random allocation table, and the random allocation process and the random allocation table are subjected to encryption processing, so that subject random allocation results are obtained; finally, medicine management allocation instructions are generated according to the subject random allocation results. Through the interactive network, a full-process controllable randomization allocation strategy is formed, error rates in tests are reduced, test efficiency of clinical research is improved, and through the encryption processing on the random allocation process and the random allocation table, the reliability of test results is greatly improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of randomization deployment technology, and particularly relates to a drug management and subject randomization method and system based on an interactive network. BACKGROUND

[0002] In the field of clinical research, randomization is a key link to ensure the scientificity and fairness of the test. However, the traditional randomization mode has significant shortcomings in many aspects, which seriously restricts the quality and efficiency of clinical research.

[0003] In the traditional randomization mode, researchers need to manually complete a large amount of complex and time-consuming randomization work. From the packaging, marking of test objects, to the unpacking after grouping, a series of operations not only consume a lot of time and energy of researchers, but also greatly increase the probability of errors due to the characteristics of manual operation, thereby affecting the reliability of the entire test results. This inefficient and error-prone mode has become a bottleneck restricting the rapid advancement of clinical research.

[0004] In terms of data security and traceability, the traditional randomization mode is full of loopholes. Due to the lack of effective monitoring means, the risk of dark box operation is always lurking, which undoubtedly violates the basic principles of fairness and justice. At the same time, the incompleteness of data recording is also a big problem. Once problems occur during the test, due to the lack of complete data records, researchers have difficulty in quickly locating the root cause of the problem and making effective corrections, which not only delays the test progress, but also may result in a waste of a large amount of manpower, material resources and financial resources.

[0005] In the face of complex clinical research needs, the traditional randomization mode is even less capable. In a variety of randomization scenarios, the traditional mode often fails to provide effective solutions, and cannot meet the individualized needs of different tests. This limitation makes it difficult for many complex clinical research to proceed smoothly, limiting the depth and breadth of medical research.

[0006] In terms of operational simplicity, the traditional randomization mode is also unsatisfactory. Too many manual operation steps not only increase the error rate, but also require high professional skills of the operators. This makes it difficult for non-professionals to participate in the test process, further limiting the development of clinical research.

[0007] As described above, how to provide a drug management and subject randomization method and system based on an interactive network to reduce test error rate and improve the efficiency and reliability of clinical research has become a problem to be solved. SUMMARY

[0008] The present application aims to provide a drug management and subject randomization method based on an interactive network to solve the above problems in the prior art.

[0009] To achieve the above object, the present application adopts the following technical solutions:

[0010] In a first aspect, the present application provides a drug management and subject randomization method based on an interactive network, which comprises:

[0011] Obtaining original subject baseline data, performing integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtaining test scenario information according to the subject baseline data;

[0012] Obtaining a preset randomization strategy library, and correspondingly selecting a subject randomization strategy from the randomization strategy library based on the test scenario information;

[0013] Based on the interactive network, generating a subject randomization table based on the subject randomization strategy and the subject baseline data, and performing encryption processing on the randomization process and the subject randomization table using double-blind method to obtain a subject randomization result;

[0014] Generating a drug management allocation instruction according to the subject randomization result.

[0015] In a possible design, obtaining test scenario information and subject baseline data, and performing integrity and compliance verification on the test scenario information and the subject baseline data, comprises:

[0016] Obtaining original subject baseline data, and performing de-duplication processing on the original subject baseline data;

[0017] Obtaining a preset subject baseline data content format, performing integrity verification on the subject baseline data that has completed de-duplication processing according to the subject baseline data content format, and removing original subject baseline data that fails the integrity verification;

[0018] Obtaining a preset subject baseline data standard, performing compliance verification on the subject baseline data that has completed integrity verification according to the subject baseline data standard, and removing original subject baseline data that fails the compliance verification;

[0019] Taking the original subject baseline data that has completed compliance verification as the subject baseline data;

[0020] Obtaining a test type, a test scale, a number of test centers, and a test variable control relationship, and combining the test type, the test scale, the number of test centers, and the test variable control relationship with the subject baseline data as test scenario information.

[0021] In a possible design, a preset randomization strategy library is acquired, and a subject randomization strategy is selected from the randomization strategy library based on the trial scene information, including:

[0022] A preset randomization strategy library is acquired, and the randomization strategy library stores simple randomization strategies, stratified block randomization strategies, and minimization randomization strategies;

[0023] A corresponding randomization strategy is selected from the randomization strategy library as a subject randomization strategy based on the trial scene information, and randomization strategy parameters are correspondingly configured for the subject randomization strategy, where the randomization strategy parameters include stratification variable weights, block lengths, and minimization algorithm thresholds.

[0024] In a possible design, based on an interactive network, a subject random allocation table is generated based on the subject baseline data by using the subject randomization strategy, and a double-blind method is used to encrypt the random allocation process and the subject random allocation table to obtain a subject random allocation result, including:

[0025] Based on an interactive network, the subject baseline data is randomized by using the subject randomization strategy to obtain a random allocation table, where the random allocation table includes subject numbers, random groups, drug package numbers, and specific drug information;

[0026] A one-time encryption key is generated by using a double-blind method, where the one-time encryption key includes an allocation key and a package key:

[0027] The allocation key is independently and securely stored, and the package key is handed over to a third-party blind administrator for isolated storage;

[0028] The random groups in the random allocation table are encrypted by using the allocation key, the mapping relationship between the drug package numbers and the specific drugs in the random allocation table is encrypted by using the package key, and the random allocation table after encryption is taken as a random allocation result.

[0029] In a possible design, a drug management allocation instruction is generated according to the subject random allocation result, including:

[0030] According to the trial scene information, the subject random allocation result is sent to a trial center;

[0031] The one-time encryption key is distributed to the trial center, and the one-time encryption key is used to decrypt the subject random allocation result by the trial center to obtain the mapping relationship between the random groups and the drug package numbers and the specific drugs;

[0032] According to the mapping relationship between the random group and the drug package number and the specific drug, the drug management allocation instruction is generated by the test center.

[0033] In a possible design, before the drug management allocation instruction is generated by the test center according to the mapping relationship between the random group and the drug package number and the specific drug, the method further includes:

[0034] A preset drug allocation threshold is obtained.

[0035] The drug inventory in the test center is obtained, and it is determined whether the drug inventory in the test center is lower than the preset drug allocation threshold.

[0036] If yes, a drug replenishment request is sent, the drug replenishment request is sent to the nearest test center, the drug inventory in the nearest test center is obtained, and it is determined whether the drug inventory in the nearest test center is lower than the preset drug allocation threshold, until the result is no.

[0037] If no, the mapping relationship between the random group and the drug package number and the specific drug is sent to the corresponding test center.

[0038] In a possible design, after the drug management allocation instruction is generated according to the random allocation result of the subject, the method further includes:

[0039] The drug dispensing time, batch and expiration date are recorded in real time, and the dispensed drug is bound to the baseline data of the subject to generate a random allocation result and a drug allocation record.

[0040] According to the random allocation result and the drug allocation record, a randomized allocation three-dimensional perspective view is generated.

[0041] According to the randomized allocation three-dimensional perspective view, an abnormal allocation result is screened, and an abnormal warning information is sent.

[0042] In a second aspect, the present application provides a drug management and subject random allocation system based on an interactive network, which includes:

[0043] A data acquisition unit is configured to acquire original subject baseline data, perform integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtain test scene information according to the subject baseline data.

[0044] A strategy selection unit is configured to obtain a preset randomization strategy library, and select a subject randomization strategy from the randomization strategy library based on the test scene information.

[0045] a subject allocation unit configured to generate a subject random allocation result based on the baseline data of the subjects by using the subject randomization strategy based on the interactive network, and to encrypt the random allocation process by using a double-blind method;

[0046] a dispensing instruction generation unit configured to generate a drug management dispensing instruction based on the subject random allocation result by associating a multi-center drug library database.

[0047] In a third aspect, the present application provides an electronic device comprising a memory, a processor and a transceiver connected in sequence and in communication, wherein the memory is configured to store a computer program, the transceiver is configured to receive and send messages, and the processor is configured to read the computer program and execute the method for drug management and subject random allocation based on an interactive network according to the first aspect or any possible design of the first aspect.

[0048] In a fourth aspect, the present application provides a computer readable storage medium having instructions stored thereon, wherein the instructions, when executed on a computer, perform the method for drug management and subject random allocation based on an interactive network according to the first aspect or any possible design of the first aspect.

[0049] In a fifth aspect, the present application provides a computer program product comprising instructions, wherein the instructions, when executed on a computer, cause the computer to perform the method for drug management and subject random allocation based on an interactive network according to the first aspect or any possible design of the first aspect.

[0050] Beneficial effects: the present application provides a method and system for drug management and subject random allocation based on an interactive network, which comprises the following steps: firstly, obtaining original subject baseline data, performing integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtaining test scenario information based on the subject baseline data; then, obtaining a preset randomization strategy library, and correspondingly selecting a subject randomization strategy from the randomization strategy library based on the test scenario information; based on an interactive network, generating a subject random allocation table based on the subject baseline data by using the subject randomization strategy, and encrypting the random allocation process and the subject random allocation table by using a double-blind method to obtain a subject random allocation result; finally, generating a drug management dispensing instruction based on the subject random allocation result. Through the interactive network, a full-process controllable randomization dispensing strategy is formed, and through the processing of the subject baseline data and the intelligent selection of the subject randomization strategy, the error rate in the test is reduced; through the full-process data calculation and processing of the interactive network, the test efficiency of the clinical research is improved, and through the encryption processing of the random allocation process and the random allocation table, the reliability of the test result is greatly improved. Attached Figure Description

[0051] Figure 1 A flowchart illustrating the steps of an interactive network-based drug management and subject randomization method provided in an embodiment of the present invention;

[0052] Figure 2 A schematic diagram of the functional structure of an interactive network-based drug management and subject randomization system provided in an embodiment of the present invention;

[0053] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0055] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0056] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0057] Example:

[0058] like Figure 1 As shown, the first aspect of this embodiment provides a method for drug management and subject randomization based on an interactive network, including but not limited to the following steps S1-S4:

[0059] S1. Obtain original subject baseline data, perform integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtain trial scenario information according to the subject baseline data;

[0060] S2. Obtain a preset randomization strategy library, and correspondingly select a subject randomization strategy from the randomization strategy library based on the trial scenario information;

[0061] S3. Based on an interactive network, generate a subject random allocation table based on the subject baseline data using the subject randomization strategy, and encrypt the random allocation process and the subject random allocation table using a double-blind method to obtain a subject random allocation result;

[0062] S4. Generate a drug management allocation instruction according to the subject random allocation result.

[0063] It should be noted that through the interactive network, the random allocation process does not require human intervention, and the whole process is completed through the interactive network response to form a fully monitored randomization allocation strategy, avoiding unfair and unjust situations in the trial. Moreover, through the whole process of data calculation and processing of the interactive network, random grouping can be quickly performed, and random allocation results can be automatically recorded and generated, which greatly reduces the workload of the operator and significantly improves the efficiency of the clinical research trial. Through the processing of the subject baseline data and the intelligent selection of the subject randomization strategy, the error rate in the trial is reduced. Moreover, through the encryption of the random allocation process and the random allocation table using data encryption technology, the integrity and confidentiality of the data are ensured, the data of each link are recorded completely, and the data traceability is ensured, which enables researchers to design experiments and manage data with confidence, greatly improving the reliability of the trial results.

[0064] The central randomization system of the interactive network response is an interactive technology system. The currently popular implementation method internationally is to use computer telecom integration (CTI) technology to integrate computers, networks and telecommunications technologies to form a multi-center clinical trial subject random allocation and enrollment for clinical research in various ways such as network, telephone and mobile phone short message.

[0065] In one possible implementation, in step S1, the original subject baseline data is obtained, the integrity and compliance of the original subject baseline data are verified to obtain the subject baseline data, and the trial scenario information is obtained according to the subject baseline data. It can be but not limited to decomposed into steps S11-S15, including:

[0066] S11. Obtain original subject baseline data, and de-duplicate the original subject baseline data;

[0067] S12. Obtain a preset subject baseline data content format, perform integrity checking on the de-duplicated subject baseline data according to the subject baseline data content format, and remove original subject baseline data that fails the integrity checking;

[0068] S13. Obtain a preset subject baseline data standard, perform compliance checking on the subject baseline data that passes the integrity checking according to the subject baseline data standard, and remove original subject baseline data that fails the compliance checking;

[0069] S14. Take the original subject baseline data that passes the compliance checking as the subject baseline data;

[0070] S15. Obtain a trial type, a trial size, a number of trial centers, and a trial variable control relationship, and combine the trial type, the trial size, the number of trial centers, and the trial variable control relationship with the subject baseline data as trial scenario information.

[0071] It should be noted that the subject baseline data in the embodiment can include, but is not limited to, subject basic demographic data and subject medical history data, wherein the subject basic demographic data includes subject name (which can be anonymized), subject gender, subject date of birth, subject age, and subject nationality; and the subject medical history data includes subject disease diagnosis information, subject medical history record, subject basic physiological index, and subject past medication history. In addition, the compliance checking needs to obtain a preset compliance standard to verify whether the subject baseline data meets the trial preset inclusion criteria (such as an age range of 18-65 years old), and to check the subject baseline data according to a set special exclusion standard (such as pregnancy status and allergy history), and exclude the subject baseline data that does not meet the compliance.

[0072] In a possible implementation, in step S2, a preset randomization strategy library is obtained, and a subject randomization strategy is correspondingly selected from the randomization strategy library based on the trial scenario information, which can be but not limited to divided into steps S21-S22, including:

[0073] S21. Obtain a preset randomization strategy library, wherein the randomization strategy library stores a simple randomization strategy, a stratified block randomization strategy, and a minimization randomization strategy;

[0074] S22. Select a corresponding randomization strategy from the randomization strategy library as a subject randomization strategy based on the trial scenario information, and configure a randomization strategy parameter corresponding to the subject randomization strategy, wherein the randomization strategy parameter includes a stratification variable weight, a block length, and a minimization algorithm threshold.

[0075] It should be noted that when selecting various randomization strategies stored in the randomization strategy library, it needs to be implemented based on the trial scenario information. Specifically, when the trial scenario information is: small trial size, single-center trial, low covariate impact, and no need for complex balance, through interactive network response, a simple randomization strategy is preferentially selected and applied to subsequent subject randomization allocation; when the trial scenario information is: large trial size, multi-center trial, and need to control stratification variables, through interactive network response, a stratified block randomization strategy is preferentially selected and applied to subsequent subject randomization allocation; when the trial scenario information is: need to dynamically balance complex covariates, through interactive network response, a minimization randomization strategy is preferentially selected and applied to subsequent subject randomization allocation.

[0076] In a possible implementation, in step S3, based on the interactive network, a subject randomization allocation table is generated based on the subject baseline data by using the subject randomization strategy, and a double-blind method is used to encrypt the randomization allocation process and the subject randomization allocation table to obtain a subject randomization allocation result, which can be but not limited to decomposed into steps S31-S34, including:

[0077] S31. Based on the interactive network, the subject randomization strategy is used to perform randomization processing on the subject baseline data to obtain a random allocation table, wherein the random allocation table includes a subject number, a random group, a drug package number, and specific drug information;

[0078] S32. A one-time encryption key is generated by using a double-blind method, wherein the one-time encryption key includes an allocation key and a package key:

[0079] S33. The allocation key is independently and securely stored, and the package key is handed over to a third-party blind administrator for isolated storage;

[0080] S34. The random group in the random allocation table is encrypted by using the allocation key, and the mapping relationship between the drug package number and the specific drug in the random allocation table is encrypted by using the package key, and the random allocation table after encryption is taken as a random allocation result.

[0081] It should be noted that a double-blind method is adopted, and a one-time encryption key is generated by using a secure random number generator, the key is divided into two parts, wherein, the distribution key is used to encrypt the random group in the distribution table (such as A / B group), and the packaging key is used to encrypt the mapping relationship between the drug packaging number and the specific drug; preferably, the encryption of the random group can adopt the AES-256 algorithm; the independent secure storage of the distribution key can use the HSM (hardware security module).

[0082] In a possible implementation, in step S4, according to the random allocation result of the subject, a drug management allocation instruction is generated, which can but is not limited to be decomposed into steps S41-S44, comprising:

[0083] S41. According to the test scenario information, the random allocation result of the subject is sent to the test center;

[0084] S42. The one-time encryption key is distributed to the test center, and the one-time encryption key is used to decrypt the random allocation result of the subject by the test center to obtain the random group and the mapping relationship between the drug packaging number and the specific drug;

[0085] S43. According to the random group and the mapping relationship between the drug packaging number and the specific drug, a drug management allocation instruction is generated by the test center.

[0086] It should be noted that the encrypted random allocation table is output to the decryption end (each test center) as the random allocation result, which should only contain the subject information, the random number and the encrypted drug packaging number, and the decryption end can input the packaging key (the one-time encryption key is only available to the test center) through a secure interface to decrypt the drug packaging number, obtain the mapping relationship between the drug packaging number and the specific drug, obtain the specific drug actually needed to be distributed, and generate a drug management allocation instruction by the test center according to the specific drug actually needed to be distributed, so as to ensure the completion of drug allocation.

[0087] In a possible implementation, before step S43, according to the random group and the mapping relationship between the drug packaging number and the specific drug, a drug management allocation instruction is generated by the test center, it can but is not limited to include the following steps:

[0088] Obtaining a preset drug allocation threshold;

[0089] Obtaining the drug inventory in the test center, and judging whether the drug inventory in the test center is lower than the preset drug allocation threshold;

[0090] If yes, a drug replenishment request is sent, and the drug replenishment request is sent to the nearest test center, and the drug inventory in the nearest test center is obtained, and it is determined whether the drug inventory in the nearest test center is lower than the preset drug allocation threshold until the result is no;

[0091] If no, the mapping relationship between the random group and the drug package number and the specific drug is sent to each corresponding test center.

[0092] In a possible implementation, after step S4, the following steps S5-S7 can be included but are not limited to:

[0093] S5. Real-time record the drug dispensing time, batch and expiration date, and bind the dispensed drug with the subject baseline data to generate a random allocation result and a drug allocation record;

[0094] S6. According to the random allocation result and the drug allocation record, a randomized allocation three-dimensional perspective view is generated;

[0095] S7. According to the randomized allocation three-dimensional perspective view, the abnormal allocation result is screened, and an abnormal warning information is sent.

[0096] It should be noted that, in order to help the clinical trial researchers of the test center to more intuitively and conveniently view and manage the randomization allocation process of the subjects, the method of the embodiment further generates a randomized allocation three-dimensional perspective view, which can more vividly represent the process and result of drug management and subject randomization allocation. At the same time, when the subject appears an abnormal allocation result in the test process, resulting in conditions such as adverse reactions or termination of unblinding, the abnormal warning information can be sent in real time to remind the researchers and improve the safety of the test and the protection of the subjects.

[0097] As shown in Figure 2 The second aspect of the embodiment provides a hardware system for implementing the drug management and subject randomization allocation method based on interactive network in the first aspect of the embodiment, which comprises:

[0098] A data acquisition unit is configured to acquire original subject baseline data, perform integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtain test scene information according to the subject baseline data;

[0099] A strategy selection unit is configured to obtain a preset randomization strategy library, and select a subject randomization strategy from the randomization strategy library according to the test scene information;

[0100] A subject allocation unit is configured to generate a subject random allocation result based on the interactive network and the subject randomization strategy, and to encrypt the random allocation process using double-blind method based on the subject baseline data;

[0101] A dispensing instruction generation unit is configured to generate a drug management dispensing instruction based on the subject random allocation result and the multi-center drug library database.

[0102] The working process, working details and technical effects of the system provided by the embodiment can be referred to the first aspect of the embodiment, and will not be repeated here.

[0103] It should be noted that in possible embodiments, the system provided by the embodiment also integrates a drug management supply module, which cooperates with the dispensing instruction generation unit to track and monitor the drug inventory of each test center in the entire clinical trial process, timely perform drug distribution and management, ensure continuous drug delivery to subjects without interruption, and monitor the validity period of the drug. The interactive network and the drug management supply module are combined to form a complete system of randomization allocation and clinical trial drug supply management, which improves the efficiency and accuracy of drug distribution and subject drug delivery in the entire clinical trial, and can significantly improve the efficiency of clinical research.

[0104] As shown in Figure 3 The third aspect of the embodiment provides an electronic device, which comprises a memory, a processor and a transceiver connected in sequence, wherein the memory is configured to store a computer program, the transceiver is configured to receive and send messages, and the processor is configured to read the computer program and execute the drug management and subject random allocation method based on the interactive network as described in the first aspect of the embodiment.

[0105] Specifically, the memory can include, but is not limited to, random access memory (RAM), read only memory (ROM), flash memory, first input first output (FIFO) memory, first in last out (FILO) memory, and the like; specifically, the processor can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor can be implemented in at least one of the hardware forms of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array), and the processor can also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in a standby state.

[0106] In some embodiments, the processor can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content required to be displayed on the display screen. For example, the processor can be, but is not limited to, a microprocessor of the STM32F105 series, a RISC (reduced instruction set computer) microprocessor, an X86 architecture processor, or a processor integrated with an embedded neural network processing unit (NPU). The transceiver can be, but is not limited to, a WIFI wireless transceiver, a Bluetooth wireless transceiver, a GPRS (General Packet Radio Service) wireless transceiver, a ZigBee wireless transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver, and the like. In addition, the device can also include, but is not limited to, a power module, a display screen, and other necessary components.

[0107] The working process, working details, and technical effects of the electronic device provided in the embodiment can be referred to the first aspect of the embodiment, and will not be repeated here.

[0108] The fourth aspect of the embodiment provides a storage medium storing instructions of the interactive network-based medicine management and subject random allocation method in the first aspect of the embodiment, that is, the storage medium stores the instructions, and when the instructions are run on a computer, the interactive network-based medicine management and subject random allocation method in the first aspect of the embodiment is executed.

[0109] The storage medium refers to a carrier for storing data, which can include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash disk, a Memory Stick and the like, and the computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices.

[0110] The working process, working details and technical effects of the storage medium provided by the embodiment can be referred to the first aspect of the embodiment, and will not be described here.

[0111] The fifth aspect of the embodiment provides a computer program product containing instructions, which, when run on a computer, causes the computer to execute the interactive network-based medicine management and subject random allocation method in the first aspect of the embodiment, wherein the computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices.

[0112] Finally, it should be noted that: the above only describes the preferred embodiments of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for drug management and subject randomization based on an interactive network, characterized in that, include: Obtain the original subject baseline data, verify the integrity and compliance of the original subject baseline data to obtain the subject baseline data, and obtain the trial scenario information based on the subject baseline data; Obtain a preset randomization strategy library, and select the corresponding randomization strategy for the test subject from the randomization strategy library based on the test scenario information; Based on the interactive network, using the subject randomization strategy, a subject randomization table is generated based on the subject baseline data, and a double-blinding method is used to encrypt the randomization process and the subject randomization table to obtain the subject randomization results. Based on the random allocation results of the subjects, a drug administration and dispensing instruction is generated; Acquire trial scenario information and subject baseline data, and verify the completeness and compliance of the trial scenario information and subject baseline data, including: Obtain the original baseline data of the subjects and perform deduplication on the original baseline data of the subjects; Obtain a preset subject baseline data content format, perform integrity verification on the subject baseline data after deduplication according to the subject baseline data content format, and remove the original subject baseline data that fails the integrity verification; Obtain a preset baseline data standard for subjects; perform compliance verification on the baseline data of subjects that have completed the integrity verification according to the baseline data standard; and remove the original baseline data of subjects that fail the compliance verification. The original subject baseline data after compliance verification will be used as the subject baseline data; The trial type, trial size, number of trial centers, and control relationships of trial variables are obtained, and these are combined with the baseline data of the subjects to serve as trial scenario information.

2. The method for drug management and subject randomization based on interactive networks according to claim 1, characterized in that, Obtain a preset randomization strategy library, and based on the experimental scenario information, select the corresponding randomization strategy for the test subjects from the randomization strategy library, including: Obtain a preset randomization strategy library, wherein the randomization strategy library stores simple randomization strategy, hierarchical block randomization strategy and minimization randomization strategy; Based on the experimental scenario information, a corresponding randomization strategy is selected from the randomization strategy library as the subject randomization strategy, and randomization strategy parameters are configured accordingly for the subject randomization strategy. The randomization strategy parameters include stratified variable weights, block lengths, and minimization algorithm thresholds.

3. The method for drug management and subject randomization based on interactive networks according to claim 1, characterized in that, Based on an interactive network and utilizing the aforementioned subject randomization strategy, a subject randomization table is generated based on the subject baseline data. A double-blinding method is then employed to encrypt the randomization process and the subject randomization table to obtain the subject randomization results, including: Based on an interactive network, the baseline data of the subjects are randomized using the subject randomization strategy to obtain a random assignment table, wherein the random assignment table includes subject number, random group, drug packaging number and specific drug information; A double-blind method is used to generate a one-time encryption key, wherein the one-time encryption key includes an allocation key and a packaging key: The allocation key is stored independently and securely, and the packaging key is entrusted to a third-party blind administrator for isolated safekeeping. The random groups in the random allocation table are encrypted using the allocation key, and the mapping relationship between the drug packaging number and the specific drug in the random allocation table is encrypted using the packaging key. The encrypted random allocation table is then used as the random allocation result.

4. The method for drug management and subject randomization based on interactive networks according to claim 3, characterized in that, Based on the randomization results of the subjects, a drug administration and dispensing instruction is generated, including: According to the experimental scenario information, the random allocation results of the subjects will be sent to the experimental center; The one-time encryption key is distributed to the test center, and the test center uses the one-time encryption key to decrypt the random assignment results of the subjects to obtain the mapping relationship between the random group and the drug packaging number and the specific drug. Based on the mapping relationship between random groups and drug packaging numbers and specific drugs, drug management and dispensing instructions are generated through the testing center.

5. The method for drug management and subject randomization based on interactive networks according to claim 4, characterized in that, Before generating drug administration and dispensing instructions through the testing center based on the mapping relationship between random groups and drug packaging numbers and specific drugs, the process also includes: Obtain the preset drug dispensing threshold; Obtain the drug inventory in the test center and determine whether the drug inventory in the test center is lower than the preset drug dispensing threshold; If so, a drug replenishment request is issued and sent to the nearest testing center. The drug inventory in the nearest testing center is obtained, and it is determined whether the drug inventory in the nearest testing center is lower than the preset drug dispensing threshold, until the result is no. If not, the mapping relationship between the random group and the drug packaging number and the specific drug will be sent to the corresponding trial centers.

6. The method for drug management and subject randomization based on interactive networks according to claim 1, characterized in that, After generating drug administration and dispensing instructions based on the random allocation results of the subjects, the process also includes: The system records the time, batch, and expiration date of drug dispensing in real time, and links the dispensed drugs to the baseline data of the subjects to generate random allocation results and drug dispensing records. Based on the random allocation results and the drug dispensing records, a randomized three-dimensional perspective view of the dispensing is generated; Based on the randomized allocation of the three-dimensional perspective view, abnormal allocation results are screened and abnormal warning information is issued.

7. A drug management and subject randomization system based on an interactive network, characterized in that, The method for drug administration and subject randomization based on an interactive network, as described in any one of claims 1 to 6, includes: The data acquisition unit is used to acquire the original subject baseline data, verify the integrity and compliance of the original subject baseline data to obtain the subject baseline data, and obtain the test scenario information based on the subject baseline data; The strategy selection unit is used to obtain a preset randomization strategy library and select the corresponding randomization strategy for the test subject from the randomization strategy library based on the test scenario information. The subject allocation unit is used to generate subject randomization results from the subject baseline data based on the subject randomization strategy using an interactive network, and to encrypt the randomization process using a double-blinding method. The dispensing instruction generation unit is used to generate drug management dispensing instructions based on the random dispensing results of the subjects and by associating with a multi-center pharmacy database.

8. An electronic device, characterized in that, The device includes a memory, a processor, and a transceiver that are sequentially and communicatively connected. The memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the drug management and subject randomization method based on an interactive network as described in any one of claims 1 to 6.

9. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or the instructions are executed by the computer, they implement the drug management and subject randomization method based on an interactive network as described in any one of claims 1 to 6.

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