CN114724661A - Multi-source clinical trial data sharing method based on block chain technology - Google Patents
Multi-source clinical trial data sharing method based on block chain technology Download PDFInfo
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Abstract
The invention discloses a multisource clinical trial data sharing method based on a block chain technology, which carries out identity verification on each participant of a block chain through an intelligent contract; the participant is a system or platform that can provide clinical trial data for a subject; each participant secretly shares the clinical test data stored in the same subject by the participant; the computing node calls an SMPC algorithm to compute the clinical test data shared by the participants secretly according to the service requirement, and sends the computed result to a reconstruction participant, wherein the reconstruction participant is the participant needing to obtain the computed result; and the reconstruction participant receives the calculation result by adopting a collection function in MPI communication and carries out secret reconstruction on the calculation result to obtain an original value of the calculation result. According to the technical scheme, the data quality and the data accuracy of the clinical test data are efficiently supervised while the safety of the clinical test data is guaranteed.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a multi-source clinical trial data sharing method based on a block chain technology.
Background
The clinical test of the medicine is an important link in the research and development process of the new medicine, and plays a key role in final evaluation of the safety and the effectiveness of the new medicine before the new medicine is listed on the market. Clinical trial items are rapidly increasing year by year, both in type and quantity. The normative and reasonability of the record of the drug clinical test process plays an important role in protecting the safety of a subject and ensuring the scientific and reliable test result, but the quality of the current drug clinical test has the problems of nonstandard endorsement of an informed consent, untimely and incomplete record of a research medical record, incapability of tracing the source of a test result, safety risk of drug management for the test and the like, so that the safety of the subject and the completeness, accuracy, trueness and reliability of the drug clinical test data are difficult to ensure. Because of worry about data leakage problems, the method for improving medical record data through multi-source data comparison is difficult to implement practically. For a supervision organization, under the condition of limited human resources, the traditional supervision mode and means are far from meeting the supervision requirements of high efficiency and high quality. Therefore, it is very important to improve the supervision of clinical test items through new methods such as active exploration, innovative practice, and the like.
In the existing Clinical trial electronic data acquisition system, visit data of a subject is limited to be manually filled and maintained by a Clinical Research Coordinator (hereinafter, referred to as CRC), a single data source often faces problems of incomplete information acquisition of the subject, illegal operation of operators, data counterfeiting, data omission and the like, and problems of data quality, data safety and the like cause unpredictable influence on the result of a drug trial. When comparing data sources of multiple sources, security problems such as privacy disclosure are faced. The supervision of drug testing processes is a challenge faced by pharmaceutical, biotechnology companies, regulatory agencies. At present, pharmaceutical and biotechnology companies only visit clinical test places regularly and frequently to supervise the clinical test process of drugs, and compare original data with medical record report tables in a manual mode on site to find the problems of data entry errors, data loss and the like. All the supervision authorities can only review test reports and visit data information submitted after the test is finished, and can not effectively supervise the behavior of researchers and the recruitment of subjects in the clinical test process of the medicine.
Disclosure of Invention
The invention provides a multi-source clinical test data sharing method based on a block chain technology, which is used for carrying out multi-party collaborative calculation on multi-source clinical test data through the block chain technology, so that the data quality and the data accuracy of the clinical test data are efficiently supervised while the safety of the clinical test data is ensured.
An embodiment of the invention provides a multi-source clinical trial data sharing method based on a block chain technology, which comprises the following steps:
carrying out identity verification on each participant of the block chain through an intelligent contract, and collecting computing nodes and an initialization execution environment; the participant is a system or platform that can provide clinical trial data for a subject;
secret sharing: each participant secretly shares the clinical test data stored in the same subject by the participant;
SMPC encryption calculation: the computing node calls an SMPC algorithm to compute the clinical test data shared by the participants secretly according to the service requirement, and sends the computed result to a reconstruction participant, wherein the reconstruction participant is the participant needing to obtain the computed result;
secret reconstruction: and the reconstruction participant receives the calculation result by adopting a collection function in MPI communication and carries out secret reconstruction on the calculation result to obtain an original value of the calculation result.
Furthermore, each participant secretly shares the clinical test data stored in the participant by the same subject, specifically:
each participant shares the same subject to other participants after being cut and encrypted according to the shared value of the clinical test data stored in the participant by the same subject, and the clinical test data acquired by each participant comprises the clinical test data stored in the participant by the same subject and the clinical test data of the same subject shared by other participants.
Further, when the computing node calls an SMPC algorithm to compute the clinical test data shared by the participants secretly according to the service requirement, the computing node receives the clinical test data for computation through a receiving function in MPI non-blocking communication and sends the computation result to the reconstruction participants through a sending function in MPI non-blocking communication.
Further, generating a corresponding report according to the original value of the calculation result, and performing uplink storage and archive reservation on clinical test data generated in the secret sharing, SMPC encryption calculation and secret reconstruction processes; the report forms comprise a data difference early warning analysis report form and a data quality analysis report form.
Further, the reconstruction participant performs secret reconstruction on the calculation result, and when an original value of the calculation result is obtained, at least calculation results sent by m calculation nodes need to be collected, wherein m is greater than or equal to t, and t is a threshold value.
The embodiment of the invention has the following beneficial effects:
the invention provides a multisource clinical trial data sharing method based on a block chain technology. And calling an SMPC algorithm by the computing node according to the service requirement to calculate the clinical test data shared by the participants in secret, sending the calculation result to the reconstruction participants, realizing comparison analysis of the clinical test data, receiving the calculation result by the reconstruction participants by adopting a collection function in MPI communication, and carrying out secret reconstruction on the calculation result so as to recover the original value of the calculation result, namely obtaining the comparison analysis result of the clinical test data.
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FIG. 1 is a flow chart of a multi-source clinical trial data sharing method based on a blockchain technique according to an embodiment of the present invention;
FIG. 2 is a block chain technique based multi-source clinical trial data sharing system according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a multi-source clinical trial data sharing method based on the blockchain technique according to an embodiment of the present invention.
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the accompanying drawings, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the invention provides a multi-source clinical trial data sharing method based on a blockchain technique, including:
s101, performing identity verification on each participant of a block chain through an intelligent contract, and collecting computing nodes and an initialization execution environment; the participant is a system or platform that can provide clinical trial data for a subject.
Step S102, secret sharing: each participant shares the clinical trial data stored by the same subject among the participants. Each participant shares the same subject to other participants after being cut and encrypted according to the shared value of the clinical test data stored in the participant by the same subject, and the clinical test data acquired by each participant comprises the clinical test data stored in the participant by the same subject and the clinical test data of the same subject shared by other participants.
Step S103, SMPC encryption calculation: and the computing node calls an SMPC algorithm to compute the clinical test data shared by the secret of the participants according to the service requirement, and sends the computed result to a reconstruction participant, wherein the reconstruction participant is the participant needing to obtain the computed result. The business requirements include consistency review of the clinical trial data and comparative analysis of the clinical trial data.
Step S104, secret reconstruction: and the reconstruction participant receives the calculation result by adopting a collection function in MPI communication and carries out secret reconstruction on the calculation result to obtain an original value of the calculation result. And the reconstruction participant carries out secret reconstruction on the calculation result, and at least collects the calculation results sent by m calculation nodes when the original value of the calculation result is obtained, wherein m is more than or equal to t, and t is a threshold value. .
As one embodiment, when the computing node calls an SMPC algorithm to compute the clinical trial data shared by the participants secretly according to the service requirement, the computing node receives the clinical trial data for computation through a receiving function in the MPI non-blocking communication, and sends the computation result to the reconstruction participants through a sending function in the MPI non-blocking communication.
The method comprises the following steps of S105, generating a corresponding report according to the original value of the calculation result, and performing uplink storage and archive reservation on clinical test data generated in the secret sharing, SMPC encryption calculation and secret reconstruction processes; the report forms comprise a data difference early warning analysis report form and a data quality analysis report form.
As a detailed embodiment, the method comprises the following steps:
step A101: and performing initialization setting. The participants (i.e., the data sources) are authenticated, and then the computation nodes are gathered to prepare for subsequent computation, and the execution environment and the threshold t value are initialized. The participants are systems that can provide clinical trial data of a subject, and specifically, the participants include, but are not limited to, clinical drug trial process monitoring systems, clinical trial electronic data collection systems, national health platforms, provincial office medical record systems, HIS systems of medical institutions, PACS systems of medical institutions, and LIS systems of medical institutions.
The identity authentication of the participants is specifically as follows: the identity of the participant is verified by deriving the participant's ip address through the intelligent contract using a public key derived from the secp256kl elliptic curve algorithm, and proving the ownership of the ip address by generating a signature using a corresponding private key and an elliptic curve digital signature algorithm.
The collection computing node specifically comprises: a certain number of nodes are collected in a command input mode, and then part of the nodes are randomly extracted from the nodes to serve as computing nodes for the subsequent computing process aiming at the secret shared data. The number of the computing nodes is determined according to the actual situation of the required computing resources. One participant is defaulted to obtain one node, and the number of the nodes obtained by the one participant can be increased according to actual conditions. And storing the ip address of the computing node in a file of a public storage area (such as a files of the archives).
Initializing an execution environment and a threshold t value, specifically: connecting the processors indicated in the maps file stored in the public storage area, starting a daemon process of each processor, acquiring the number of processor units participating in operation, calculating the value of a threshold t, and setting t as [2n/3], wherein n represents the number of participants (namely, the original information can be obtained through reconstruction if sharing information of at least t participants is obtained). For example, if the ID number is cut or shared into 6 shares, at least 4 shares (i.e. the threshold value t) are combined together, and the ID information of the ID card can be recovered.
Step A102: secret sharing is performed on clinical trial data. By individual participants P1，P2，P3，...，PnAnd carrying out secret sharing on the clinical test data of the same subject stored in the own party. For example, each participant P1，P2，P3，...，PnThe clinical trial data stored in the same subject of own are respectively a1，a2，a3，…，anFrom each participant P1，P2，P3，...，PnAfter the clinical trial data a, b, c, …, n stored in the same subject of the own party are shared secretly, each participant can obtain the clinical trial data of the own party and the clinical trial data shared by other participants. The clinical trial data a1，a2，a3，…，anIncluding but not limited to name, ageGender, ID card, inspection result.
As one of the embodiments, in a finite field, for a participant P1Clinical trial data a for secret sharing, randomly selecting t-1 random numbers (r)1，r2，...，rt-1) Let r0A (i.e. a is a solution of a polynomial) constitutes a polynomial equation
Then in the polynomial equation
Taking x as xi(wherein i ∈ [1, n ]]) Then to the participant P1(wherein i ∈ [1, n ]]) The obtained clinical test data a has a shared value of ai＝fa(xi) The sharing value is correspondingly distributed (namely shared) to other participants, and a isiDistribute to corresponding PiI.e. according to formula ai＝fa(xi) And the clinical trial data a is divided, encrypted and shared to other participants.
Likewise, for participant P2Clinical trial data b for secret sharing, randomly selecting t-1 random numbers (l)1，l2，...，lt-1) Let l0B form a polynomial equation
Also in polynomial equation
In (1), take the value randomly, for example, let x ═ xi(wherein i ∈ [1, n ]]) Then for the participant P2The shared value of the obtained clinical test data b is bi＝fb(xi) The sharing value is correspondingly distributed (namely shared) to other participants, and b is carried outiDistribute to corresponding PiI.e. according to formula bi＝fb(xi) And segmenting and encrypting the clinical test data b and then sharing the data to other participants. Final participant P1Secret shared clinical trial data (a) will be obtained1，b1，…，n1) And the clinical trial data a segments the encrypted other data. Participant P2Secret shared clinical trial data (a) will be obtained2，b2，…，n2) And the clinical trial data b segments the encrypted other data.
Step A103: and the computing node calls an SMPC algorithm to compute the clinical test data shared by the secret of the participants according to the service requirement, and sends the computed result to a reconstruction participant, wherein the reconstruction participant is the participant needing to obtain the computed result. For example, the computing node i is according to ci＝g(ai，bi)＝g[fa(xi)，fb(xi)]Calculating to obtain a result ciWherein g (a)i，bi) Representing functions determined for calculation according to the traffic demand, aiAnd biAnd cutting the encrypted data of the clinical test data of the same subject for different participants.
And when the computing node calls an SMPC algorithm to compute the clinical test data shared by the participants secretly according to the service requirement, receiving the clinical test data to be computed through a receiving function in MPI non-blocking communication, respectively computing the clinical test data, and sending the computed result to the reconstruction participants through a sending function in the MPI non-blocking communication.
Step A104: the reconstruction participant receives the calculation result { c) by adopting a collection function in MPI communication1，c2，...，cmAnd secret reconstruction is carried out on the calculation result to obtain an original value of the calculation result.
As one of the embodiments, the reconstruction participant receives the participant P as a compute node using a collection function in MPI communication in pseudo codeiSent calculation result ciWhile, the reconstruction participant collects the calculation results { c }1，c2，...，cmThe original value of the calculation result can be recovered only when at least m calculation results sent by participants as calculation nodes are collected
(α1，α2，...，αn) Is a recombination vector, wherein m is more than or equal to t, and t is a threshold value.
As shown in fig. 3, clinical trial data of the same subject on different participants are subjected to secret sharing, SMPC calculation and secret reconstruction, and then an original value c of a calculation result of the clinical trial data subjected to multi-party collaborative calculation is obtained.
Step A105: and generating a corresponding report according to the original value of the calculation result, and performing uplink storage and archive reservation on the clinical test data generated in the secret sharing and secret reconstruction processes.
The embodiment of the invention solves the following problems:
(1) in the process of recruitment of the subjects, the medical record data of the subjects cannot be comprehensively checked by grouping examination, and the subjects hide the medical history or rule-breaking operation of a research center, so that unpredictable results are caused to the drug tests.
(2) In the clinical test process, the problems of data counterfeiting, data quality, illegal operation and the like cannot be effectively supervised due to a single data source.
(3) And when multi-source data are aggregated or verified, one party can know the data condition of the other party, so that the risk of data leakage of a subject exists.
(4) And when the sponsor checks, the original data and the CRC filling data are manually compared, so that the time consumption is too long, and the effect is not good.
(5) And a supervision mechanism cannot participate in process supervision, and cannot timely manage and control and effectively avoid when adverse events, safety events, operation violation and other problems occur, so that the difficulty of post-inspection is high.
The embodiment of the invention realizes the following effects:
(1) through multi-source data secret sharing and secret reconstruction, medical history data of the subjects can be acquired, comprehensive medical history of the subjects is provided, and the problems that the subjects hide the medical history in the process of recruitment of the subjects or the study center violates operations and the like are avoided.
(2) Through mutual verification of clinical test data of a plurality of systems, the problems of data counterfeiting, poor data quality and the like of a single data source are solved.
(3) And by adopting the block chain to carry out multi-party safety calculation, the problem of data leakage of the subject in the multi-system data verification process is solved.
(4) And providing multiple data sources for the sponsor to perform data verification, and improving the working efficiency of the sponsor in-situ examination.
(5) The multi-channel data verification method based on the multi-channel data analysis is capable of providing multi-party data verification for a supervision organization, providing data consistency verification through multi-channel data verification analysis, forming data difference early warning analysis, providing data quality analysis, guaranteeing data quality supervision, and providing process data tracing basis for adverse events and safety events.
The embodiment of the invention adopts the block chain to carry out multi-party safe calculation, solves the problem of cooperative calculation for protecting privacy among a group of distrusted parties, and provides multi-party cooperative calculation capability for data demand parties on the premise of not revealing original data. Meanwhile, by utilizing the characteristics of traceability and non-falsification of the block chain technology, the problems of data counterfeiting, operation violation, low data quality, difficult examination and the like in the processes of recruitment of a subject, clinical trials and examination after the end of the trial are solved. The multi-party safety calculation and block chain technology of the embodiment of the invention is a technology which is diffused to multi-level and multi-professional by one information technology, and the embodiment of the invention is applied to the field of medical information safety, and is particularly applied to the supervision of the clinical drug test process of multi-source data.
According to the embodiment of the invention, data verification and aggregation are carried out through multi-party safe calculation under the condition that privacy of data of all parties is not disclosed, the willingness of medical institutions to share medical information of the subjects is promoted, and then the information counterfeiting condition of the subjects in the recruitment process of the subjects is reduced after multi-source data comparison, so that the subjects with higher quality are screened for clinical trials. And through medical record data comparison, the data quality in the clinical test process is improved, so that the clinical test result is more real and reliable. And finally, the block chain technology is used for carrying out chain storage and gear reservation on the whole clinical test data secret sharing, data calculation and secret reconstruction processes, so that data leakage and change are prevented, and a supervision mechanism can supervise the whole clinical test process.
As shown in fig. 2, on the basis of the above embodiment of the method, another embodiment of the present invention correspondingly provides a multi-source clinical trial data sharing system based on the blockchain technology, where the system architecture includes a user layer, a service layer, a data layer and an operating environment.
The user layer faces to the user and is used for recording and inquiring various services of the clinical test of the medicine.
The business layer is used for providing access and node management for the user layer, recording data generated in a clinical drug test, providing data security transmission service, providing multi-source data comparison analysis service, storing and linking original data and data generated in each flow of the clinical drug test, guaranteeing test data security according to technical characteristics of the block chain, monitoring events generated in the clinical drug test, and realizing traceability of an experimental process.
The data layer comprises a database mysql, a block chain service FISCO BCOS, a cache database redis and a search service Elastic Seach, and the data support capability is provided for the whole system.
The operating environment is used for providing an operating environment and basic components required by the system.
For convenience and brevity of description, the multi-source clinical trial data sharing system based on the blockchain technology in the system embodiment of the present invention includes all the implementation manners in the above-mentioned multi-source clinical trial data sharing method based on the blockchain technology, and details are not repeated here.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
It will be understood by those skilled in the art that all or part of the processes of the above embodiments may be implemented by hardware related to instructions of a computer program, and the computer program may be stored in a computer readable storage medium, and when executed, may include the processes of the above embodiments. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
Claims (6)
1. A multi-source clinical trial data sharing method based on a block chain technology is characterized by comprising the following steps:
carrying out identity verification on each participant of the block chain through an intelligent contract, and collecting computing nodes and an initialization execution environment; the participant is a system or platform that can provide clinical trial data for a subject;
secret sharing: each participant secretly shares the clinical test data stored in the participant by the same subject;
SMPC encryption calculation: the computing node calls an SMPC algorithm to compute the clinical test data shared by the participants secretly according to the service requirement, and sends the computed result to a reconstruction participant, wherein the reconstruction participant is the participant needing to obtain the computed result;
secret reconstruction: and the reconstruction participant receives the calculation result by adopting a collection function in MPI communication and carries out secret reconstruction on the calculation result to obtain an original value of the calculation result.
2. The method of claim 1, wherein each participant secretly shares clinical trial data stored in the same subject among the participants, specifically:
each participant shares the same subject to other participants after being cut and encrypted according to the shared value of the clinical test data stored in the participant by the same subject, and the clinical test data acquired by each participant comprises the clinical test data stored in the participant by the same subject and the clinical test data of the same subject shared by other participants.
3. The blockchain technology-based multi-source clinical trial data sharing method according to claim 2, wherein the business requirements include consistency review of the clinical trial data and comparison analysis of the clinical trial data.
4. The method of claim 3, wherein when the computing node calls an SMPC algorithm to compute the secret clinical trial data shared by the participants according to business requirements, the computing node receives the clinical trial data for computation through a receiving function in MPI non-blocking communication and sends the computation result to the reconstruction participants through a sending function in MPI non-blocking communication.
5. The method according to claim 4, wherein a report is generated according to the original value of the calculation result, and the clinical trial data generated by the secret sharing, SMPC encryption calculation and secret reconstruction process is subjected to uplink storage and archive; the report forms comprise a data difference early warning analysis report form and a data quality analysis report form.
6. The multi-source medical data supervision method based on the block chain technology according to any one of claims 1 to 5, wherein the reconstruction participant performs secret reconstruction on the calculation result, and collects calculation results sent by m calculation nodes when obtaining an original value of the calculation result, wherein m is greater than or equal to t, and t is a threshold value.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115440332A (en) * | 2022-11-07 | 2022-12-06 | 南京邮电大学 | Clinical test data storage and sharing method based on public chain and alliance chain |
| CN116401715A (en) * | 2023-06-08 | 2023-07-07 | 中国移动紫金(江苏)创新研究院有限公司 | Medical data circulation privacy calculation method and system based on blockchain |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115440332A (en) * | 2022-11-07 | 2022-12-06 | 南京邮电大学 | Clinical test data storage and sharing method based on public chain and alliance chain |
| CN116401715A (en) * | 2023-06-08 | 2023-07-07 | 中国移动紫金(江苏)创新研究院有限公司 | Medical data circulation privacy calculation method and system based on blockchain |
| CN116401715B (en) * | 2023-06-08 | 2023-08-22 | 中国移动紫金(江苏)创新研究院有限公司 | Medical data circulation privacy calculation method and system based on blockchain |
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