Drug management and subject random allocation method and system based on interactive network

Abstract

The invention discloses a drug management and subject random allocation method and system based on an interactive network, and belongs to the technical field of random allocation, and the method comprises the steps: firstly, obtaining original subject baseline data, carrying out the data preprocessing of the original subject baseline data, obtaining subject baseline data, and obtaining test scene information; then, correspondingly selecting a tested randomization strategy from a randomization strategy library based on the test scene information; generating a subject random allocation table by using a subject randomization strategy, and encrypting the random allocation process and the random allocation table to obtain a subject random allocation result; and finally, according to the random blending result of the subject, generating a medicine management blending instruction. Through the interactive network, a whole-course controllable randomized allocation strategy is formed, the error rate in a test is reduced, the test efficiency of clinical research is improved, and the reliability of a test result is greatly improved through encryption processing of a random allocation process and a random allocation table.

Description

Technical Field

[0001] The present invention belongs to the technical field of randomized dispensing, and in particular relates to a method and system for drug management and random dispensing of subjects based on an interactive network. Background Art

[0002] In clinical research, randomization is a key step in ensuring the scientificity and fairness of trials. However, traditional randomization models have significant shortcomings in many aspects, seriously restricting the quality and efficiency of clinical research.

[0003] In traditional randomization models, researchers must manually complete a large amount of complex and time-consuming randomization work. From packaging and labeling trial subjects to unpacking them after grouping, these operations not only consume a significant amount of researchers' time and energy, but also significantly increase the probability of errors due to manual operation, thereby compromising the reliability of the overall trial results. This inefficient and error-prone model has become a bottleneck hindering the rapid advancement of clinical research.

[0004] In terms of data security and traceability, traditional randomized models are riddled with vulnerabilities. The lack of effective, end-to-end monitoring creates the ever-present risk of manipulation, which undoubtedly violates fundamental principles of fairness and impartiality. Furthermore, incomplete data records are a persistent problem. If problems arise during a trial, the lack of complete data records makes it difficult for researchers to quickly identify the root cause and implement effective corrections. This not only delays the trial but can also lead to significant waste of manpower, material, and financial resources.

[0005] Faced with the complex demands of clinical research, traditional randomized models appear to be insufficient. In various randomized scenarios, traditional models often struggle to provide effective solutions and cannot meet the individual needs of different trials. This limitation makes it difficult to conduct many complex clinical studies smoothly, restricting the depth and breadth of medical research.

[0006] The traditional randomized model also leaves much to be desired in terms of ease of operation. Excessive manual intervention not only increases the error rate but also places high demands on the operator's professional skills. This makes it difficult for non-professionals to participate in the trial process, further limiting the development of clinical research.

[0007] As mentioned above, how to provide an interactive network-based drug management and subject randomization method and system that can reduce the experimental error rate and improve the efficiency and reliability of clinical research trials has become an urgent problem to be solved. Summary of the Invention

[0008] The purpose of the present invention is to provide an interactive network-based drug management and subject randomization method to solve the above-mentioned problems existing in the prior art.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] In a first aspect, the present invention provides an interactive network-based method for drug management and random allocation of subjects, comprising:

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

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

[0013] Based on the interactive network, the subject randomization strategy is used to generate a subject randomization table based on the subject baseline data, and the randomization process and the subject randomization table are encrypted using a double-blind method to obtain the subject randomization result;

[0014] Generate drug administration and dispensing instructions based on the random dispensing results of the subjects.

[0015] In a possible design, the trial scenario information and subject baseline data are obtained, and the integrity and compliance of the trial scenario information and the subject baseline data are verified, including:

[0016] Obtaining original subject baseline data and performing deduplication processing on the original subject baseline data;

[0017] Obtaining a preset subject baseline data content format, performing an integrity check on the subject baseline data that has completed the deduplication process according to the subject baseline data content format, and removing the original subject baseline data that fails the integrity check;

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

[0019] The original subject baseline data that has completed compliance verification will be used as the subject baseline data;

[0020] The trial type, trial scale, number of trial centers and trial variable control relationship are obtained, and the trial type, trial scale, number of trial centers and trial variable control relationship are combined with the subject baseline data as trial scenario information.

[0021] In a possible design, a preset randomization strategy library is obtained, and based on the experimental scenario information, a test randomization strategy is correspondingly selected from the randomization strategy library, including:

[0022] Obtaining 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;

[0023] 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 correspondingly configured for the subject randomization strategy, wherein the randomization strategy parameters include stratification variable weight, block length and minimization algorithm threshold.

[0024] In a possible design, based on an interactive network, the subject randomization strategy is used to generate a subject randomization table based on the subject baseline data, and the randomization process and the subject randomization table are encrypted using a double-blind method to obtain the subject randomization results, including:

[0025] Based on the interactive network, the subject randomization strategy is used to randomize the baseline data of the subject to obtain a random allocation table, wherein the random allocation table includes the subject number, random group, drug package number and specific drug information;

[0026] A double-blind method is used to generate a one-time encryption key, where the one-time encryption key includes a distribution key and a wrapping key:

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

[0028] The random groups in the random allocation table are encrypted using the allocation key, the mapping relationship between the drug package number and the specific drug in the random allocation table is encrypted using the packaging key, and the encrypted random allocation table is used as the random allocation result.

[0029] In a possible design, based on the randomized allocation results of the subjects, drug administration allocation instructions are generated, including:

[0030] According to the test scenario information, the random allocation results of the subjects are sent to the test center;

[0031] Distributing the one-time encryption key to the test center, and using the one-time encryption key to decrypt the random allocation result of the subject, to obtain a mapping relationship between the random group and the drug package number and the specific drug;

[0032] Based on the mapping relationship between random groups and drug packaging numbers and specific drugs, drug management and dispensing instructions are generated by the trial center.

[0033] In a possible design, before generating drug administration and dispensing instructions by the trial center based on the mapping relationship between the random group and the drug package number and the specific drug, the following is also included:

[0034] Get the preset drug dispensing threshold;

[0035] Obtaining the drug inventory in the test center, and determining whether the drug inventory in the test center is lower than the preset drug allocation threshold;

[0036] If so, a drug replenishment request is issued and 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 dispensing threshold, until the result is negative;

[0037] If not, the mapping relationship between the random group and the drug package number and the specific drug is sent to the corresponding test centers.

[0038] In a possible design, after generating a drug administration and dispensing instruction based on the random dispensing result of the subject, the following is further included:

[0039] Record drug dispensing time, batch, and expiration date in real time, and associate the dispensed drugs with the subject's baseline data to generate randomized allocation results and drug dispensing records;

[0040] generating a randomized dispensing three-dimensional perspective diagram based on the random allocation results and the drug dispensing record;

[0041] According to the randomized allocation three-dimensional perspective diagram, abnormal allocation results are screened and abnormal warning information is issued.

[0042] In a second aspect, the present invention provides an interactive network-based drug management and subject randomization system, comprising:

[0043] a data acquisition unit, 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 scenario information based on the subject baseline data;

[0044] A strategy selection unit is used to obtain a preset randomization strategy library and select a test randomization strategy from the randomization strategy library based on the test scenario information;

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

[0046] The dispensing instruction generating unit is used to associate the multi-center drug library database with the random dispensing results of the subjects to generate drug management dispensing instructions.

[0047] In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a transceiver that are communicatively connected in sequence, wherein 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 interactive network-based drug management and subject randomization method as described in the first aspect or any possible design of the first aspect.

[0048] In a fourth aspect, the present invention provides a computer-readable storage medium having instructions stored thereon, which, when executed on a computer, executes the interactive network-based drug management and subject randomization method described in the first aspect or any possible design of the first aspect.

[0049] In a fifth aspect, the present invention provides a computer program product comprising instructions, which, when executed on a computer, cause the computer to execute the interactive network-based drug management and subject randomization method as described in the first aspect or any possible design of the first aspect.

[0050] Beneficial effects: The present invention provides an interactive network-based drug management and subject random allocation method and system, which includes: first, 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 based on the test scenario information, correspondingly selecting a subject randomization strategy from the randomization strategy library; then, based on the interactive network, using the subject randomization strategy, generating a subject random allocation table based on the subject baseline data, and using a double-blind method to encrypt the random allocation process and the subject random allocation table to obtain a subject random allocation result; finally, generating a drug management allocation instruction based on the subject random allocation result. Through the interactive network, a fully controllable randomization allocation strategy was formed, and the error rate in the experiment was reduced by processing the baseline data of the subjects and intelligently selecting the randomization strategy for the subjects. The full-process data calculation and processing of this interactive network improved the efficiency of clinical research experiments, and the encryption of the randomization process and randomization table greatly improved the reliability of the experiment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic flow chart of the steps of the 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 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly introduced below in conjunction with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structure of the 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 work. It should be noted that the description of these embodiments is used to help 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 elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element can be referred to as a second element, and similarly, a second element can be referred to as a first element without departing from the scope of the exemplary embodiments of the present invention.

[0056] It should be understood that the term "and / or" that may appear in this document is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B may indicate three situations: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" that may appear in this document describes another type of association object relationship, indicating that two relationships may exist. For example, A / and B may indicate two situations: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0057] Example:

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

[0059] S1. Obtaining original subject baseline data, performing integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtaining trial scenario information based on the subject baseline data;

[0060] S2. Obtaining a preset randomization strategy library, and based on the experimental scenario information, selecting a corresponding randomization strategy for the subject from the randomization strategy library;

[0061] S3. Based on the interactive network, using the subject randomization strategy, generating a subject randomization table based on the subject baseline data, and encrypting the randomization process and the subject randomization table using a double-blind method to obtain the subject randomization results;

[0062] S4. Generate drug management and dispensing instructions based on the random dispensing results of the subjects.

[0063] It should be noted that, through the interactive network, the process of random allocation does not require human participation, and the entire process is completed through interactive network responses, so as to form a random allocation strategy that can be monitored throughout the process, avoiding unfairness and injustice in the experiment; and, through the full data calculation and processing of this interactive network, random grouping can be carried out quickly, and random allocation results can be automatically recorded and generated, which greatly reduces the operator's workload and significantly improves the trial efficiency of clinical research; through the processing of the subject's baseline data and the intelligent selection of the subject randomization strategy, the error rate in the experiment is reduced; and, through the use of data encryption technology, the random allocation process and the random allocation table are encrypted to ensure the integrity and confidentiality of the data, and the data of each link are fully recorded to ensure the traceability of the data, which enables researchers to carry out experimental design and data management with confidence, greatly improving the reliability of the trial results.

[0064] Among them, the central randomization system of interactive network response is an interactive technical system. The current popular implementation method internationally is to use computer telecomintegration (CTI) technology to integrate computer, network and telecommunication technologies to form a multi-center clinical trial random allocation and enrollment system for clinical research using multiple methods such as the Internet, telephone, and mobile phone text messages.

[0065] In one possible implementation, in step S1, original subject baseline data is obtained, integrity and compliance verification is performed on the original subject baseline data to obtain subject baseline data, and experimental scenario information is obtained based on the subject baseline data. This can be decomposed into, but is not limited to, the following steps S11-S15, including:

[0066] S11. Obtaining original subject baseline data and performing deduplication processing on the original subject baseline data;

[0067] S12. Obtaining a preset subject baseline data content format, performing an integrity check on the deduplicated subject baseline data according to the subject baseline data content format, and removing the original subject baseline data that fails the integrity check;

[0068] S13. Obtaining preset subject baseline data standards, performing compliance verification on the subject baseline data that has completed integrity verification according to the subject baseline data standards, and removing the original subject baseline data that has not passed the compliance verification;

[0069] S14. The original subject baseline data that has completed compliance verification shall be used as the subject baseline data;

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

[0071] It should be noted that the subject baseline data in this embodiment may include, but is not limited to: subject basic demographic data and subject medical history data, wherein the subject basic demographic data includes the subject's name (which can be anonymized), subject gender, subject date of birth, subject age and subject ethnicity; the subject medical history data includes the subject's disease diagnosis information, subject medical history records, subject basic physiological indicators, and subject previous medication history. In addition, compliance verification requires obtaining preset compliance standards to verify whether the subject baseline data meets the preset inclusion criteria of the trial (such as age range 18-65 years old), and verifies the subject baseline data according to the set special exclusion criteria (such as pregnancy status, allergy history), and excludes non-compliant subject baseline data.

[0072] In one possible implementation, in step S2, obtaining a preset randomization strategy library and selecting a test randomization strategy from the randomization strategy library based on the test scenario information may be decomposed into, but not limited to, the following steps S21-S22, including:

[0073] S21. Obtaining 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. Based on the experimental scenario information, select a corresponding randomization strategy from the randomization strategy library as the subject randomization strategy, and configure randomization strategy parameters corresponding to the subject randomization strategy, wherein the randomization strategy parameters include stratification variable weight, block group length, and minimization algorithm threshold.

[0075] It should be noted that the selection of various randomization strategies stored in the randomization strategy library needs to be based on the experimental scenario information. Specifically, when the experimental scenario information is: small trial scale, single-center trial, low covariate influence, and no need for complex balance, the simple randomization strategy is preferentially selected through interactive network response and applied to the subsequent random allocation of subjects; when the experimental scenario information is: large trial scale, multi-center trial, and the need to control stratified variables, the stratified block randomization strategy is preferentially selected through interactive network response and applied to the subsequent random allocation of subjects; when the experimental scenario information is: dynamic balance of complex covariates is required, the minimum randomization strategy is preferentially selected through interactive network response and applied to the subsequent random allocation of subjects.

[0076] In one possible embodiment, in step S3, based on the interactive network, the subject randomization strategy is used to generate a subject randomization table based on the subject baseline data, and the randomization process and the subject randomization table are encrypted using a double-blind method to obtain the subject randomization result. The process can be decomposed into, but is not limited to, the following steps S31-S34, including:

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

[0078] S32. Generate a one-time encryption key using a double-blind method, wherein the one-time encryption key includes a distribution key and a wrapping key:

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

[0080] S34. Use the distribution key to encrypt the random groups in the random allocation table, use the packaging key to encrypt the mapping relationship between the drug package number and the specific drug in the random allocation table, and use the encrypted random allocation table as the random allocation result.

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

[0082] In a possible embodiment, in step S4, generating a drug administration and dispensing instruction based on the random dispensing result of the subject may be decomposed into, but not limited to, the following steps S41-S44, including:

[0083] S41. Send the random allocation results of the subjects to the test center according to the test scenario information;

[0084] S42. 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 allocation result of the subject to obtain the mapping relationship between the random group and the drug package number and the specific drug;

[0085] S43. Based on the mapping relationship between the random group and drug packaging number and the specific drug, the trial center generates drug management and dispensing instructions.

[0086] It should be noted that the encrypted random allocation table is output to the decryption end (each trial center) as the random allocation result. This random allocation result should only contain the subject information, random number and encrypted drug package number. The decryption end can input the packaging key through the security interface (the one-time encryption key is only available to the trial center) to decrypt the drug package number, obtain the mapping relationship between the drug package number and the specific drug, obtain the specific drug that actually needs to be distributed, and generate drug management and allocation instructions through the trial center based on the specific drug that actually needs to be distributed to ensure the completion of drug allocation.

[0087] In a possible implementation, before generating the drug management and dispensing instructions by the test center based on the mapping relationship between the random group and the drug package number and the specific drug in step S43, the following steps may also be included but are not limited to:

[0088] Get the preset drug dispensing threshold;

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

[0090] If so, a drug replenishment request is issued and 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 dispensing threshold, until the result is negative;

[0091] If not, the mapping relationship between the random group and the drug package number and the specific drug is sent to the corresponding test centers.

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

[0093] S5. Record the drug dispensing time, batch, and expiration date in real time, and associate the dispensed drugs with the subject's baseline data to generate randomized allocation results and drug dispensing records;

[0094] S6. Generate a randomized three-dimensional perspective view of the drug preparation according to the random allocation results and the drug preparation records;

[0095] S7. Screen abnormal allocation results based on the randomized three-dimensional perspective view and issue abnormal warning information.

[0096] It should be noted that in order to help clinical trial researchers in the trial center to view and manage the subject randomization process more intuitively and conveniently, the method of this embodiment also generates a three-dimensional perspective view of randomization. The three-dimensional perspective view of randomization can more vividly express the process and results of drug management and subject randomization. At the same time, when abnormal allocation results occur during the trial, such as adverse reactions or termination of unblinding, abnormal warning information can be issued in real time to remind researchers, thereby improving the safety of the trial and the protection of the subjects.

[0097] like Figure 2 As shown, the second aspect of this embodiment provides a hardware system for implementing the interactive network-based drug management and subject randomization method described in the first aspect of the embodiment, including:

[0098] a data acquisition unit, 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 scenario information based on the subject baseline data;

[0099] A strategy selection unit is used to obtain a preset randomization strategy library and select a test randomization strategy from the randomization strategy library based on the test scenario information;

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

[0101] The dispensing instruction generating unit is used to associate the multi-center drug library database with the random dispensing results of the subjects to generate drug management dispensing instructions.

[0102] The working process, working details and technical effects of the system provided in this embodiment can be found in the first aspect of the embodiment and will not be described in detail here.

[0103] It should be noted that, in a possible implementation manner, the system provided in this embodiment also integrates a drug management and supply module. The drug management and supply module works in conjunction with the dispensing instruction generation unit to track and monitor the drug inventory status of each trial center throughout the clinical trial process, timely distribute and manage drugs, ensure that the subjects' drug dispensing is continuous and uninterrupted, and monitor the expiration date of drugs. The interactive network and the drug management and supply module are combined to form a complete system for randomized dispensing and clinical trial drug supply management, which improves the efficiency and accuracy of drug distribution and drug dispensing for subjects throughout the clinical trial and can significantly improve the efficiency of clinical research.

[0104] like Figure 3 As shown, the third aspect of this embodiment provides an electronic device, comprising: a memory, a processor and a transceiver that are communicatively connected in sequence, wherein the memory is used to store computer programs, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the interactive network-based drug management and subject randomization method as described in the first aspect of the embodiment.

[0105] For example, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in first-out memory (FIFO), and / or first-in last-out memory (FILO); specifically, the processor may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. The processor may be implemented in at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Furthermore, the processor may 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); and the coprocessor is a low-power processor for processing data in a standby state.

[0106] In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. For example, the processor may be, but is not limited to, a microprocessor of the STM32F105 series, a reduced instruction set computer (RISC) microprocessor, an X86 architecture processor, or a processor with an integrated embedded neural network processing unit (NPU); the transceiver may be, but is not limited to, a wireless fidelity (WIFI) wireless transceiver, a Bluetooth wireless transceiver, a general packet radio service technology (GPRS) wireless transceiver, a ZigBee protocol (a low-power local area network protocol based on the IEEE802.15.4 standard, ZigBee) wireless transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. In addition, the device may 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 this embodiment can be found in the first aspect of the embodiment and will not be described in detail here.

[0108] The fourth aspect of this embodiment provides a storage medium that stores instructions for the interactive network-based drug management and subject randomization method described in the first aspect of the embodiment, that is, the storage medium stores instructions, and when the instructions are run on a computer, the interactive network-based drug management and subject randomization method described in the first aspect of the embodiment is executed.

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

[0110] The working process, working details and technical effects of the storage medium provided in this embodiment can be found in the first aspect of the embodiment and will not be described in detail here.

[0111] The fifth aspect of this embodiment provides a computer program product comprising instructions, which, when executed on a computer, causes the computer to execute the interactive network-based drug management and subject randomization method as described in the first aspect of the embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0112] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A method for drug management and random allocation of subjects based on an interactive network, characterized in that: include: Obtaining original subject baseline data, performing integrity and compliance verification on the original subject baseline data to obtain subject baseline data, and obtaining trial scenario information based on the subject baseline data; Obtaining a preset randomization strategy library, and selecting a test randomization strategy from the randomization strategy library based on the test scenario information; Based on the interactive network, the subject randomization strategy is used to generate a subject randomization table based on the subject baseline data, and the randomization process and the subject randomization table are encrypted using a double-blind method to obtain the subject randomization result; Generate drug administration and dispensing instructions based on the random dispensing results of the subjects.

2. The interactive network-based drug management and subject randomization method according to claim 1, characterized in that: Obtaining trial scenario information and subject baseline data, and performing integrity and compliance verification on the trial scenario information and subject baseline data, including: Obtaining original subject baseline data and performing deduplication processing on the original subject baseline data; Obtaining a preset subject baseline data content format, performing an integrity check on the subject baseline data that has completed the deduplication process according to the subject baseline data content format, and removing the original subject baseline data that fails the integrity check; Obtaining preset subject baseline data standards, performing compliance verification on the subject baseline data that has completed integrity verification according to the subject baseline data standards, and removing original subject baseline data that has failed the compliance verification; The original subject baseline data that has completed compliance verification will be used as the subject baseline data; The trial type, trial scale, number of trial centers and trial variable control relationship are obtained, and the trial type, trial scale, number of trial centers and trial variable control relationship are combined with the subject baseline data as trial scenario information.

3. The interactive network-based drug management and subject randomization method according to claim 1, characterized in that: Obtaining a preset randomization strategy library, and based on the test scenario information, correspondingly selecting a test randomization strategy from the randomization strategy library, including: Obtaining 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; 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 correspondingly configured for the subject randomization strategy, wherein the randomization strategy parameters include stratification variable weight, block length and minimization algorithm threshold.

4. The interactive network-based drug management and subject randomization method according to claim 1, characterized in that: Based on the interactive network, the subject randomization strategy is used to generate a subject randomization table based on the subject baseline data, and the randomization process and the subject randomization table are encrypted using a double-blind method to obtain the subject randomization results, including: Based on the interactive network, the subject randomization strategy is used to randomize the baseline data of the subject to obtain a random allocation table, wherein the random allocation table includes the subject number, random group, drug package number and specific drug information; A double-blind method is used to generate a one-time encryption key, where the one-time encryption key includes a distribution key and a wrapping key: The distribution key is stored independently and securely, and the wrapping key is handed over to a third-party blind administrator for isolated custody; The random groups in the random allocation table are encrypted using the allocation key, the mapping relationship between the drug package number and the specific drug in the random allocation table is encrypted using the packaging key, and the encrypted random allocation table is used as the random allocation result.

5. The interactive network-based drug management and subject randomization method according to claim 4, characterized in that: Generate drug administration and dispensing instructions based on the random dispensing results of the subjects, including: According to the test scenario information, the random allocation results of the subjects are sent to the test center; Distributing the one-time encryption key to the test center, and using the one-time encryption key to decrypt the random allocation result of the subject, to obtain a mapping relationship between the random group and the drug package 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 by the trial center.

6. The interactive network-based drug management and subject randomization method according to claim 5, characterized in that: Before generating drug administration and dispensing instructions through the trial center based on the mapping relationship between the random group and the drug package number and the specific drug, the following is also included: Get the preset drug dispensing threshold; Obtaining the drug inventory in the test center, and determining whether the drug inventory in the test center is lower than the preset drug allocation threshold; If so, a drug replenishment request is issued and 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 dispensing threshold, until the result is negative; If not, the mapping relationship between the random group and the drug package number and the specific drug is sent to the corresponding test centers.

7. The interactive network-based drug management and subject randomization method according to claim 1, characterized in that: After generating a drug administration and dispensing instruction according to the random dispensing result of the subject, the method further includes: Record drug dispensing time, batch, and expiration date in real time, and associate the dispensed drugs with the subject's baseline data to generate randomized allocation results and drug dispensing records; generating a randomized dispensing three-dimensional perspective diagram based on the random allocation results and the drug dispensing record; According to the randomized allocation three-dimensional perspective diagram, abnormal allocation results are screened and abnormal warning information is issued.

8. An interactive network-based drug management and subject randomization system, characterized by: include: a data acquisition unit, 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 scenario information based on the subject baseline data; A strategy selection unit is used to obtain a preset randomization strategy library and select a test randomization strategy from the randomization strategy library based on the test scenario information; A subject allocation unit, configured to generate a subject randomization result for the subject baseline data using the subject randomization strategy based on an interactive network, and encrypt the random allocation process using a double-blind method; The dispensing instruction generating unit is used to associate the multi-center drug library database with the random dispensing results of the subjects to generate drug management dispensing instructions.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a transceiver which are communicatively connected in sequence, wherein 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 to execute the interactive network-based drug management and subject randomization method according to any one of claims 1 to 7.

10. A computer program product comprising a computer program or instructions, characterized in that When executed by a computer, the computer program or the instruction implements the interactive network-based drug management and subject randomization method according to any one of claims 1 to 7.

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