Blockchain storage method and system for small sample clinical trial data

Abstract

This invention discloses a blockchain-based evidence storage method and system for small-sample clinical trial data, belonging to the interdisciplinary field of pharmaceutical clinical trial data management and blockchain technology. The system includes a blockchain underlying platform, multiple business participation nodes, and regulatory audit nodes. The method achieves tamper-proof evidence storage and traceability across the entire chain, from trial design, subject recruitment, data collection to statistical analysis, through structured processing of data throughout the small-sample clinical trial process, multi-node consensus on-chain storage, and attribute-based encrypted access control. This invention addresses the core shortcomings of existing small-sample clinical trial data storage, such as susceptibility to tampering, lack of trust among multiple parties, difficulty in regulatory verification, and difficulty in protecting data value. It improves data immutability and regulatory verification efficiency, and is particularly suitable for small-sample clinical trial scenarios such as rare disease drugs, personalized medicine, and pediatric medications, providing technical support for pharmaceutical companies' compliant applications and efficient verification by regulatory agencies.

Description

Technical Field

[0001] This invention belongs to the field of pharmaceutical clinical trial data management and blockchain technology, specifically involving a blockchain-based evidence storage method and system for small-sample clinical trial data. Background Technology

[0002] With the continuous development of pharmaceutical research and development, small-sample clinical trials are playing an increasingly important role in areas such as rare disease drug development, personalized precision medicine, and pediatric drug development. Unlike large-sample clinical trials, small-sample clinical trials are characterized by a small number of participants, multiple data dimensions, high value of individual data points, short trial periods, and strict regulatory requirements. The authenticity, completeness, and traceability of the data directly affect the success or failure of drug approval and patient medication safety.

[0003] Currently, small-sample clinical trial data are generally stored in a centralized manner and managed by the sponsor or CRO, which has the following unavoidable core technical defects: 1. Centralized data storage allows for arbitrary modification by internal personnel without leaving any trace. In small-sample clinical trials, tampering with a single data point can distort the entire trial result, severely impacting the impartiality of drug approval.

[0004] 2. There is a lack of a unified and credible data platform among sponsors, CROs, clinical trial institutions, ethics committees, and regulatory agencies. Data needs to be repeatedly transmitted and verified among multiple parties, which is not only inefficient but also prone to inconsistencies.

[0005] 3. Regulatory agencies need to manually verify a large number of paper documents and electronic data when conducting drug approval reviews, which is time-consuming and costly. For small-sample clinical trials, the verification is even more difficult due to the small but dispersed amount of data.

[0006] 4. Small-sample clinical trial data contains a large amount of participants' private information and core R&D data from companies. Centralized storage makes it vulnerable to hacking attacks, leading to data leaks. Furthermore, the use and flow of this data cannot be effectively monitored, making it difficult to protect the company's intellectual property rights.

[0007] 5. Most existing general blockchain evidence storage solutions only store evidence for the final results and cannot cover the entire clinical trial process; at the same time, they do not take into account the characteristics of small-sample clinical trials and cannot meet the special compliance requirements of the pharmaceutical industry.

[0008] To address the aforementioned shortcomings of existing technologies, there is currently no dedicated blockchain-based evidence storage solution for small-sample clinical trials in the industry. Zhongshiyao Zhicheng (Shandong) Pharmaceutical Consulting Co., Ltd., as a professional pharmaceutical consulting service provider, has deeply understood the pain points of small-sample clinical trial data management through its long-term CRO services. Therefore, it developed this invention to solve the aforementioned technical problems. Summary of the Invention

[0009] In response to the problems raised in the background technology above, the purpose of this invention is to provide a blockchain-based evidence storage method and system for small-sample clinical trial data. This invention solves the core defects of existing small-sample clinical trial data, such as easy tampering in centralized storage, lack of trust among multiple parties, difficulty in regulatory verification, and difficulty in protecting data value. It improves the immutability of data and the efficiency of regulatory verification, and is particularly suitable for small-sample clinical trial scenarios such as rare disease drugs, personalized medicine, and pediatric drugs, providing technical support for pharmaceutical companies' compliant declarations and efficient verification by regulatory agencies.

[0010] To achieve the above-mentioned technical objectives, the technical solution adopted by the present invention is as follows: A blockchain-based method for storing evidence of small-sample clinical trial data includes the following steps: S1. Collect raw data from the entire process of small-sample clinical trials, standardize and structure the raw data, and generate trial data units with unique identifiers. S2. Send the test data unit to multiple consensus nodes in the blockchain network, complete the data authenticity verification through the preset consensus mechanism, and generate a verified block; S3. The verified test data units are encrypted using an attribute-based encryption algorithm. Decryption permissions are assigned according to the roles of different participants. The encrypted test data is then stored in the blockchain distributed ledger. S4. Establish the association mapping relationship between experimental data units and the entire process operation behavior, generate a unique traceability identifier and store it on the blockchain; S5. In response to regulatory audit requests, retrieve the corresponding full-process test data and operation records from the blockchain distributed ledger based on the traceability identifier, and generate an tamper-proof audit report.

[0011] Further specifying, step S1 specifically includes the following sub-steps: S11. Connect to the clinical trial electronic data acquisition system to synchronously collect raw data throughout the entire process; S12. Standardize and structure the raw data to generate structured data that conforms to pharmaceutical industry standards; S13. Generate a globally unique identifier for each structured data unit, containing the test number, timestamp, and hash value.

[0012] Further specifying, step S2 specifically includes the following sub-steps: S21. Broadcast the experimental data unit to all consensus nodes in the blockchain network; S22. Each consensus node independently verifies the authenticity and integrity of the data according to the preset verification rules. S23. When the preset consensus threshold is met, the verified test data units will be packaged to generate a new block and uploaded to the blockchain.

[0013] Further specifying, S3 specifically includes the following sub-steps: S31. Extract the role attributes, trial phase attributes, and data type attributes of each participant; S32. The test data units are encrypted using an attribute-based encryption algorithm; S33. Assign corresponding decryption permissions according to the attributes of the participants, generate permission control policies and put them on the blockchain.

[0014] Further specifying, step S4 specifically includes the following sub-steps: S41. Collect all operational behavior data related to the experimental data; S42. Associate and bind the hash value of the operation behavior data with the hash value of the corresponding test data unit; S43. Generate a unique traceability identifier that relates all data and operational behaviors throughout the entire process and store it on the blockchain; Further restrictions include the underlying blockchain platform, multiple business participation nodes, and regulatory audit nodes; All the business participation nodes and regulatory audit nodes are connected to the underlying blockchain platform and interact with data through the blockchain network. The business participation nodes include sponsor nodes, CRO service nodes, clinical trial institution nodes, and ethics committee nodes, which are used to collect, upload, and review trial data; The regulatory audit node is used to initiate audit requests, retrieve full-process test data, and generate audit reports. The underlying blockchain platform includes a data processing module, a consensus verification module, an encrypted storage module, and a traceability and auditing module. The output of the data processing module is electrically connected to the input of the consensus verification module, the output of the consensus verification module is electrically connected to the input of the encrypted storage module, and the traceability audit module is bidirectionally connected to the encrypted storage module and the regulatory audit node.

[0015] Further specifying, the data processing module includes a data acquisition unit, a data standardization unit, and a unique identifier generation unit; The data acquisition unit is used to interface with the clinical trial electronic data acquisition system to obtain raw trial data; the data standardization unit is used to convert the raw data into structured data that conforms to pharmaceutical industry standards; and the unique identifier generation unit is used to generate a unique identifier containing a hash value for each structured data unit.

[0016] Further specifying, the consensus verification module includes a node management unit, a verification rule configuration unit, and a block generation unit; The node management unit is used to manage all business participation nodes connected to the blockchain network; the verification rule configuration unit is used to preset data verification rules and consensus thresholds; and the block generation unit is used to package the verified test data into blocks and upload them to the chain.

[0017] Further specifying, the encrypted storage module includes an attribute encryption unit, an access control unit, and a distributed storage unit; The attribute encryption unit is used to encrypt the test data using an attribute-based encryption algorithm, the permission management unit is used to assign decryption permissions according to the role attributes of the participants, and the distributed storage unit is used to store the encrypted test data in the blockchain distributed ledger.

[0018] Further specifying, the source tracing and auditing module includes a source tracing identifier generation unit, a data retrieval unit, and an audit report generation unit; The traceability identifier generation unit is used to generate a unique traceability identifier that associates the entire process data with the operational behavior. The data retrieval unit is used to retrieve the corresponding data from the distributed ledger based on the traceability identifier. The audit report generation unit is used to automatically generate an unalterable audit report that meets the regulatory requirements of the National Medical Products Administration.

[0019] The beneficial effects of this invention are: This invention enables end-to-end data storage and verification for small-sample clinical trials, from protocol design to report submission. Once data is on the blockchain, it cannot be tampered with, fundamentally solving the problem of data falsification. This invention employs multi-node consensus verification, establishing a multi-party trust mechanism. Using an improved consensus mechanism, sponsors, CROs, clinical trial institutions, and ethics committees jointly participate in data verification. Only data unanimously approved by all parties can be uploaded to the blockchain, completely resolving the issue of lack of trust among parties and improving collaboration efficiency.

[0020] This invention employs access-based encrypted storage to protect data security and privacy. It utilizes an attribute-based encryption algorithm, assigning different access permissions based on the roles of different participants. This ensures data sharing and collaboration while effectively protecting the privacy of test subjects and core R&D data of enterprises, reducing the risk of data leakage. The invention also features end-to-end traceability, improving regulatory verification efficiency. Each data unit is associated with a unique traceability identifier, allowing regulatory agencies to access all trial data and operation records with a single click and automatically generate compliant audit reports. This significantly improves regulatory verification efficiency, reducing the verification cycle from months to days.

[0021] This invention is specifically designed for the characteristics of small-sample clinical trials, supports multiple pharmaceutical industry standard data formats, and generates audit reports that fully comply with the regulatory requirements of the National Medical Products Administration and can be directly used for drug application, significantly reducing the compliance costs for pharmaceutical companies. Attached Figure Description

[0022] The present invention can be further illustrated by the non-limiting embodiments given in the accompanying drawings; Figure 1 This is a flowchart illustrating the steps of an embodiment of the blockchain-based evidence storage method and system for small-sample clinical trial data according to the present invention. Figure 2 This is a system module diagram of an embodiment of the blockchain-based evidence storage method and system for small-sample clinical trial data of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be further described below with reference to the accompanying drawings and embodiments. The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention. It should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] like Figure 1 As shown, the blockchain-based evidence storage method for small-sample clinical trial data of the present invention includes the following steps: S1. Collect raw data from the entire process of small-sample clinical trials, standardize and structure the raw data, and generate trial data units with unique identifiers. S2. Send the test data unit to multiple consensus nodes in the blockchain network, complete the data authenticity verification through the preset consensus mechanism, and generate a verified block; S3. The verified test data units are encrypted using an attribute-based encryption algorithm. Decryption permissions are assigned according to the roles of different participants. The encrypted test data is then stored in the blockchain distributed ledger. S4. Establish the association mapping relationship between experimental data units and the entire process operation behavior, generate a unique traceability identifier and store it on the blockchain; S5. In response to regulatory audit requests, retrieve the corresponding full-process test data and operation records from the blockchain distributed ledger based on the traceability identifier, and generate an tamper-proof audit report.

[0025] During implementation, the system first automatically connects to the clinical trial electronic data acquisition system, collecting all raw data from trial initiation to completion in real time. After standardizing and transforming the collected unstructured data, it generates data units with unique hash identifiers. These data units are broadcast to all consensus nodes on the consortium blockchain, and after cross-verification by multiple nodes, they are packaged and uploaded to the blockchain. Attribute-based encryption algorithms are used to encrypt and store the data, and access permissions are assigned according to the roles of the participants. Simultaneously, a mapping between data and operational behavior is established, generating unique traceability identifiers. When a regulatory agency initiates an audit request, the system can retrieve all process data with one click and automatically generate an immutable audit report. Its core principle is to utilize the immutability and traceability of the blockchain's distributed ledger to construct a decentralized, trusted data storage system. This method completely solves the core pain points of traditional centralized data storage, such as susceptibility to tampering and lack of trust among multiple parties, achieving trusted data storage for the entire process of small-sample clinical trials.

[0026] In practical applications of this embodiment, step S1 specifically includes the following sub-steps: S11. Connect to the clinical trial electronic data acquisition system to synchronously collect raw data throughout the entire process; S12. Standardize and structure the raw data to generate structured data that conforms to pharmaceutical industry standards; S13. Generate a globally unique identifier for each structured data unit, containing the test number, timestamp, and hash value.

[0027] The original data of the entire small-sample clinical trial process mentioned in S11 includes the trial protocol document, ethics review approval document, informed consent form of the subject, clinical observation data, laboratory test data, adverse event records and statistical analysis reports; the standardized structured conversion mentioned in step S12 refers to converting unstructured data such as PDF and Word into JSON format data that conforms to the CDISC standard.

[0028] During implementation, the system connects to the clinical trial EDC system via a standard API interface, automatically synchronizing all raw data throughout the process, including trial protocols, ethical approvals, informed consent forms, clinical observation data, and laboratory test data. Subsequently, unstructured data such as PDFs and Word documents are converted into structured data in JSON format conforming to CDISC pharmaceutical industry standards, unifying data fields and formats. Finally, a globally unique identifier is generated for each structured data unit, containing a trial number, a timestamp accurate to milliseconds, and a SHA-256 hash value. The principle behind this is eliminating data heterogeneity through standardization and ensuring data integrity and uniqueness through hash values. This design ensures that data from different sources and in different formats can be uniformly stored on the blockchain, laying the foundation for subsequent consensus verification and data sharing, with high accuracy in data standardization.

[0029] In practical applications of this embodiment, step S2 specifically includes the following sub-steps: S21. Broadcast the experimental data unit to all consensus nodes in the blockchain network; S22. Each consensus node independently verifies the authenticity and integrity of the data according to the preset verification rules. S23. When the preset consensus threshold is met, the verified test data units will be packaged to generate a new block and uploaded to the blockchain.

[0030] The preset verification rules in S22 include data format verification, data integrity verification, and data logical consistency verification; the preset consensus threshold in step S23 is that more than 2 / 3 of the consensus nodes pass the verification; the consensus nodes include sponsor nodes, CRO service nodes, clinical trial institution nodes, and ethics committee nodes.

[0031] During implementation, the master node broadcasts the generated trial data units to four consensus nodes in the blockchain network: the sponsor, CRO, clinical trial institution, and ethics committee. Each node independently performs triple verification on the data: first, it verifies whether the data format conforms to the CDISC standard; second, it verifies whether the data hash value is complete and tamper-proof; and finally, it verifies whether the data logic conforms to clinical trial guidelines. When more than two-thirds of the nodes pass the verification, the system packages the data into a new block, adds it to the end of the blockchain, and synchronizes it to all nodes. The principle behind this design is an improved practical Byzantine fault-tolerant consensus mechanism, using multi-party cross-verification to prevent a single node from tampering with the data. This design establishes a verification mechanism based on mutual trust among multiple parties, technically eliminating the possibility of data falsification.

[0032] In practical applications of this embodiment, step S3 specifically includes the following sub-steps: S31. Extract the role attributes, trial phase attributes, and data type attributes of each participant; S32. The test data units are encrypted using an attribute-based encryption algorithm; S33. Assign corresponding decryption permissions according to the attributes of the participants, generate permission control policies and put them on the blockchain.

[0033] The role attributes mentioned in S31 include sponsor, CRO, clinical trial institution, ethics committee and regulatory agency; the access control strategy mentioned in step S33 is as follows: the sponsor has read and write permissions for all data, the CRO service node has read and write permissions for the data of the corresponding stage it is responsible for, the clinical trial institution node only has read and write permissions for the data generated by its own institution, and the ethics committee node has read-only permissions for ethics-related data.

[0034] During implementation, the system first extracts three types of attributes from all participants: role attributes (sponsor / CRO / institution / ethics / regulatory), trial phase attributes (initiation / execution / statistics / completion), and data type attributes (protocol / ethics / clinical / laboratory). Then, it encrypts the trial data units using the CP-ABE attribute-based encryption algorithm, embedding the aforementioned attributes into the encryption key. Finally, based on a preset access control policy, it assigns corresponding decryption permissions to different participants; only participants meeting the attribute conditions can decrypt and access the corresponding data. The principle behind this is to achieve fine-grained access control of data through attribute-based encryption, eliminating the need to assign a separate key to each user. This design ensures secure data sharing among multiple parties while effectively protecting the privacy of research subjects and core R&D data of enterprises, reducing the risk of data leakage.

[0035] In the practical application of this embodiment, step S4 specifically includes the following sub-steps: S41. Collect all operational behavior data related to the experimental data; S42. Associate and bind the hash value of the operation behavior data with the hash value of the corresponding test data unit; S43. Generate a unique traceability identifier that relates all data and operational behaviors throughout the entire process and store it on the blockchain; The operational behavior data mentioned in S41 includes data collection time, collector, modification time, modifier, review time and reviewer; all operational behavior data generate independent hash values, which form a chain association with the hash values ​​of the experimental data units.

[0036] During implementation, the system collects all operational data related to the experimental data throughout the entire process, including the data collector, collection time, modifier, modification time, reviewer, and review time. It generates a unique SHA-256 hash value for each operational action and links the hash value of the operational action with the hash value of the corresponding experimental data unit in a chain. Finally, it generates a unique traceability identifier that links all data and operational actions and stores it on the blockchain. The principle is to establish a one-to-one correspondence between data and operational actions by utilizing the uniqueness and immutability of hash values. This design achieves full lifecycle traceability of experimental data; any modification to the data leaves an indelible trace, providing conclusive evidence for regulatory verification.

[0037] In practical applications of this embodiment, it includes a blockchain underlying platform, multiple business participation nodes, and regulatory audit nodes; All the business participation nodes and regulatory audit nodes are connected to the underlying blockchain platform and interact with data through the blockchain network. The business participation nodes include sponsor nodes, CRO service nodes, clinical trial institution nodes, and ethics committee nodes, which are used to collect, upload, and review trial data; The regulatory audit node is used to initiate audit requests, retrieve full-process test data, and generate audit reports. The underlying blockchain platform includes a data processing module, a consensus verification module, an encrypted storage module, and a traceability and auditing module. The output of the data processing module is electrically connected to the input of the consensus verification module, the output of the consensus verification module is electrically connected to the input of the encrypted storage module, and the traceability audit module is bidirectionally connected to the encrypted storage module and the regulatory audit node.

[0038] During implementation, the system adopts a consortium blockchain architecture, deploying a blockchain underlying platform and connecting four business participants—the sponsor, CRO, clinical trial institution, and ethics committee—as well as one regulatory audit node. All nodes interact peer-to-peer through the blockchain network. The blockchain underlying platform has four core modules: a data processing module responsible for data collection and preprocessing, a consensus verification module responsible for multi-node data verification, an encrypted storage module responsible for data encryption and distributed storage, and a traceability audit module responsible for data traceability and audit report generation. These modules are connected sequentially according to the data flow, forming a complete evidence storage loop. Its core principle is to construct a distributed system architecture with business nodes on the blockchain and core modules working together. This system architecture has low coupling and strong scalability, and can flexibly adapt to small-sample clinical trial projects of different sizes and types.

[0039] In practical applications of this embodiment, the data processing module includes a data acquisition unit, a data standardization unit, and a unique identifier generation unit; The data acquisition unit is used to interface with the clinical trial electronic data acquisition system to obtain raw trial data; the data standardization unit is used to convert the raw data into structured data that conforms to pharmaceutical industry standards; and the unique identifier generation unit is used to generate a unique identifier containing a hash value for each structured data unit.

[0040] During implementation, the data acquisition unit connects to various clinical trial electronic data acquisition systems via a standard API interface to achieve automatic synchronous acquisition of raw data, avoiding manual entry errors. The data standardization unit has a built-in CDISC standard conversion engine that automatically converts various unstructured data into structured data in a unified format. The unique identifier generation unit uses a combination of "trial number + timestamp + hash value" to generate a globally unique identifier for each data unit. The principle behind this is to ensure the standardization and uniqueness of the data uploaded to the blockchain through an automated data preprocessing workflow. This module achieves automated acquisition and standardized processing of clinical trial data, significantly reducing manual costs.

[0041] In practical applications of this embodiment, the consensus verification module includes a node management unit, a verification rule configuration unit, and a block generation unit; The node management unit is used to manage all business participation nodes connected to the blockchain network; the verification rule configuration unit is used to preset data verification rules and consensus thresholds; and the block generation unit is used to package the verified test data into blocks and upload them to the chain.

[0042] During implementation, the node management unit is responsible for the registration, authentication, and management of all business nodes connected to the blockchain network; only authorized nodes can participate in the consensus process. The verification rule configuration unit supports flexible configuration of data verification rules and consensus thresholds according to the regulatory requirements of different clinical trials. The block generation unit is responsible for packaging the verified trial data into new blocks in chronological order and synchronizing them to all nodes. Its principle is to achieve flexible configuration and secure operation of the consensus mechanism through modular consensus management. This module ensures the security and flexibility of the consensus process and can meet the requirements of different levels of pharmaceutical regulatory oversight.

[0043] In the practical application of this embodiment, the encrypted storage module includes an attribute encryption unit, an access control unit, and a distributed storage unit; The attribute encryption unit is used to encrypt the test data using an attribute-based encryption algorithm, the permission management unit is used to assign decryption permissions according to the role attributes of the participants, and the distributed storage unit is used to store the encrypted test data in the blockchain distributed ledger.

[0044] During implementation, the attribute encryption unit incorporates a hardware encryption accelerator and employs the CP-ABE attribute-based encryption algorithm for high-speed encryption of the experimental data. The access control unit maintains the attribute information and access control policies of the participants, supporting dynamic adjustment and revocation of permissions. The distributed storage unit uses the IPFS interplanetary file system to distribute the encrypted experimental data across all nodes, avoiding single points of failure. Its principle is to ensure data security and high availability through the combination of encryption algorithms and distributed storage. This module achieves secure data storage and reliable access.

[0045] In practical applications of this embodiment, the source tracing and auditing module includes a source tracing identifier generation unit, a data retrieval unit, and an audit report generation unit; The traceability identifier generation unit is used to generate a unique traceability identifier that associates the entire process data with the operational behavior. The data retrieval unit is used to retrieve the corresponding data from the distributed ledger based on the traceability identifier. The audit report generation unit is used to automatically generate an unalterable audit report that meets the regulatory requirements of the National Medical Products Administration.

[0046] In implementation, the traceability identifier generation unit generates a unique traceability identifier for each clinical trial project, linking it to all data and operation records of that project. The data retrieval unit automatically retrieves the corresponding full-process data and operation records from the blockchain distributed ledger based on the traceability identifier input by the regulatory agency. The audit report generation unit incorporates the National Medical Products Administration's standard audit report template and automatically generates an immutable audit report with a blockchain hash value. Its principle is to utilize the traceability characteristics of blockchain to automate and standardize the audit process. This module reduces regulatory verification time from several months to several days, improving regulatory verification efficiency, and the generated audit reports can be directly used for drug application.

[0047] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A blockchain storage method for small sample clinical trial data, characterized in that, Includes the following steps: S1. Collect raw data from the entire process of small-sample clinical trials, standardize and structure the raw data, and generate trial data units with unique identifiers. S2. Send the test data unit to multiple consensus nodes in the blockchain network, complete the data authenticity verification through the preset consensus mechanism, and generate a block that has passed the verification. S3. The verified test data units are encrypted using an attribute-based encryption algorithm. Decryption permissions are assigned according to the roles of different participants. The encrypted test data is then stored in the blockchain distributed ledger. S4. Establish the association mapping relationship between experimental data units and the entire process operation behavior, generate a unique traceability identifier and store it on the blockchain; S5. In response to regulatory audit requests, retrieve the corresponding full-process test data and operation records from the blockchain distributed ledger based on the traceability identifier, and generate an tamper-proof audit report.

2. The blockchain storage method for small sample clinical trial data according to claim 1, characterized in that: S1 specifically includes the following sub-steps: S11. Connect to the clinical trial electronic data acquisition system to synchronously collect raw data throughout the entire process; S12. Standardize and structure the raw data to generate structured data that conforms to pharmaceutical industry standards; S13. Generate a globally unique identifier for each structured data unit, containing the test number, timestamp, and hash value.

3. The blockchain storage method for small sample clinical trial data according to claim 1, characterized in that: S2 specifically includes the following sub-steps: S21. Broadcast the experimental data unit to all consensus nodes in the blockchain network; S22. Each consensus node independently verifies the authenticity and integrity of the data according to the preset verification rules. S23. When the preset consensus threshold is met, the verified test data units will be packaged to generate a new block and uploaded to the blockchain.

4. The blockchain storage method for small sample clinical trial data according to claim 1, characterized in that: S3 specifically includes the following sub-steps: S31. Extract the role attributes, trial phase attributes, and data type attributes of each participant; S32. The test data units are encrypted using an attribute-based encryption algorithm; S33. Assign corresponding decryption permissions according to the attributes of the participants, generate permission control policies and put them on the blockchain.

5. The blockchain storage method for small sample clinical trial data according to claim 1, characterized in that: Step S4 specifically includes the following sub-steps: S41. Collect all operational behavior data related to the experimental data; S42. Associate and bind the hash value of the operation behavior data with the hash value of the corresponding test data unit; S43. Generate a unique traceability identifier that relates all data and operational behaviors throughout the entire process and store it on the blockchain. 6.A blockchain storage system for small sample clinical trial data, characterized in that: This includes the underlying blockchain platform, multiple business participation nodes, and regulatory audit nodes; All the business participation nodes and regulatory audit nodes are connected to the underlying blockchain platform and interact with data through the blockchain network. The business participation nodes include sponsor nodes, CRO service nodes, clinical trial institution nodes, and ethics committee nodes, which are used to collect, upload, and review trial data; The regulatory audit node is used to initiate audit requests, retrieve full-process test data, and generate audit reports. The underlying blockchain platform includes a data processing module, a consensus verification module, an encrypted storage module, and a traceability and auditing module. The output of the data processing module is electrically connected to the input of the consensus verification module, the output of the consensus verification module is electrically connected to the input of the encrypted storage module, and the traceability audit module is bidirectionally connected to the encrypted storage module and the regulatory audit node.

7. The small sample size clinical trial data blockchain notarization system of claim 6, wherein: The data processing module includes a data acquisition unit, a data standardization unit, and a unique identifier generation unit; The data acquisition unit is used to interface with the clinical trial electronic data acquisition system to obtain raw trial data; the data standardization unit is used to convert the raw data into structured data that conforms to pharmaceutical industry standards; and the unique identifier generation unit is used to generate a unique identifier containing a hash value for each structured data unit.

8. The small sample size clinical trial data oriented blockchain storage system according to claim 6, characterized in that: The consensus verification module includes a node management unit, a verification rule configuration unit, and a block generation unit. The node management unit is used to manage all business participation nodes connected to the blockchain network; the verification rule configuration unit is used to preset data verification rules and consensus thresholds; and the block generation unit is used to package the verified test data into blocks and upload them to the chain. 9.The small sample oriented clinical trial data blockchain notarization system according to claim 6, characterized in that: The encrypted storage module includes an attribute encryption unit, an access control unit, and a distributed storage unit; The attribute encryption unit is used to encrypt the test data using an attribute-based encryption algorithm, the permission management unit is used to assign decryption permissions according to the role attributes of the participants, and the distributed storage unit is used to store the encrypted test data in the blockchain distributed ledger.

10. The small sample size clinical trial data oriented blockchain storage system according to claim 6, characterized in that: The source tracing and auditing module includes a source tracing identifier generation unit, a data retrieval unit, and an audit report generation unit; The traceability identifier generation unit is used to generate a unique traceability identifier that associates the entire process data with the operational behavior. The data retrieval unit is used to retrieve the corresponding data from the distributed ledger based on the traceability identifier. The audit report generation unit is used to automatically generate an unalterable audit report that meets the regulatory requirements of the National Medical Products Administration.

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