A biological sample bank management system, method and device

Abstract

This application relates to the field of medical information technology and discloses a biobank management system, method, and equipment. The system includes: a cost accounting module for calculating the comprehensive input cost of a sample based on its availability weight coefficient, human resource cost, economic cost, and supporting service cost, and sending this comprehensive input cost to a utilization efficiency evaluation module. The availability weight coefficient characterizes the scarcity value of the sample. A benefit correlation module for calculating the comprehensive output benefit of the sample based on associated scientific research results, capacity building results, and social and economic benefits, and sending this comprehensive output benefit to the utilization efficiency evaluation module. A utilization efficiency evaluation module for obtaining utilization efficiency evaluation indicators based on the comprehensive input cost and comprehensive output benefit, for sample resource decision-making and management. Its beneficial effect is that it achieves a comprehensive and quantitative evaluation of sample utilization efficiency.

Description

Technical Field

[0001] This application relates to the field of medical information technology, and in particular to a biobank management system, method and device. Background Technology

[0002] Biobanks, as core resource platforms for biomedical research, house a large number of biological samples, including tissues, cells, and nucleic acids, that possess significant scientific value. Currently widely used biobank management systems primarily focus on the collection, identification, storage, retrieval, and inbound / outbound processes of samples. However, these systems lack the ability to scientifically quantify and evaluate the efficiency of sample resource utilization, resulting in a severe disconnect between sample usage and final research output. This situation makes it difficult for administrators to accurately identify high-value samples and inefficiently utilized projects, hindering data-driven optimization and planning decisions for sample resources. Summary of the Invention

[0003] This application provides a biobank management system, method, and device, which solves the technical problem that related technologies cannot quantify sample utilization efficiency, and achieves the technical effect of comprehensively and quantitatively evaluating sample utilization efficiency.

[0004] To achieve the above objectives, the main technical solutions adopted in this application include: In a first aspect, embodiments of this application provide a biobank management system, the system comprising: a cost accounting module, used to obtain the comprehensive input cost of the sample based on the sample's availability weight coefficient, human resource cost, economic cost, and supporting service cost, and send the comprehensive input cost to a utilization efficiency evaluation module, wherein the availability weight coefficient is used to characterize the scarcity value of the sample; a benefit correlation module, used to obtain the comprehensive output benefit of the sample based on scientific research results information, capacity building results information, and social and economic benefit information associated with the sample, and send the comprehensive output benefit to the utilization efficiency evaluation module; and a utilization efficiency evaluation module, used to obtain utilization efficiency evaluation indicators based on the comprehensive input cost and the comprehensive output benefit, for sample resource decision management.

[0005] The biobank management system provided in this application monetizes the value of scarcity by introducing an availability weight coefficient and calculates human resource costs, economic costs, and supporting service costs to obtain a more scientific comprehensive input cost. By uniformly quantifying the scientific research results, capacity building results, and social and economic benefits associated with the samples into calculable benefit values, a strong correlation is established between the samples and the final comprehensive output benefits. Utilization efficiency evaluation indicators are calculated using comprehensive input costs and comprehensive output benefits to guide sample resource decision-making and management, thereby maximizing the overall value of the biobank.

[0006] Optionally, the system further includes a basic data module, which is connected to the cost accounting module and is used to provide the cost accounting module with the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the sample; the basic data module is also connected to the benefit correlation module and is used to provide the benefit correlation module with the usage records of the sample.

[0007] The basic data module provides the cost accounting module with the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the samples. This ensures that the data sources for calculating the availability weight coefficient and the comprehensive input cost accounting are consistent and standardized, guaranteeing the scientific and accurate nature of cost quantification. Furthermore, the basic data module provides the benefit correlation module with sample usage records, resolving the disconnect between output benefits and sample data.

[0008] Optionally, the cost accounting module includes: an availability assessment unit, used to determine the availability weight coefficient of the sample based on the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the sample; a cost assessment unit, used to calculate the human resource cost, economic cost, and supporting service cost of the sample; and a comprehensive input cost calculation unit, used to generate the comprehensive input cost based on the availability weight coefficient, the human resource cost, the economic cost, and the supporting service cost.

[0009] The availability assessment unit uses the disease incidence rate range, sample size limit, and dynamic adjustment factor as the basis for determining the availability weight coefficient, ensuring that the weight coefficient accurately reflects the actual difficulty of sample acquisition. Through step-by-step calculations using the cost assessment unit and the comprehensive input cost calculation unit, the actual input costs of human resources, economic resources, and supporting services are calculated separately first. Then, these costs are integrated with the availability weight coefficient to generate the comprehensive input cost. This approach achieves a comprehensive consideration of both the implicit costs corresponding to the difficulty of sample acquisition and the explicit costs of actual input, while also ensuring the traceability of the comprehensive input cost calculation logic and guaranteeing the accuracy of cost quantification. This provides precise cost data support for subsequent sample utilization efficiency assessments.

[0010] Optionally, the availability assessment unit is specifically used to: determine a basic weight coefficient based on the disease incidence rate range and the upper limit of the sample size; and adjust the basic weight coefficient based on the dynamic adjustment factor to generate the availability weight coefficient.

[0011] By determining the basic weight coefficients using both the disease incidence rate range and the upper limit of sample size, the one-sidedness of relying solely on the incidence rate dimension is avoided, providing a clear and quantifiable basis for the generation of basic weights. Targeted adjustments to the basic weight coefficients through dynamic factor adjustment incorporate various practical influencing factors during sample acquisition, besides basic scarcity, into the weighting considerations. This achieves refined calibration of the basic weights, ensuring that the final availability weight coefficients comprehensively and accurately reflect the true difficulty of sample availability.

[0012] Optionally, the comprehensive input cost calculation unit is specifically used to: calculate the sum of the labor cost, the economic cost, and the supporting service cost to obtain the total direct cost; multiply the total direct cost by the availability weight coefficient, and use the product as the comprehensive input cost.

[0013] By summing the costs of human resources, economic benefits, and supporting services to obtain the total direct cost, a centralized and integrated accounting of various explicit actual input costs in the process of sample acquisition, processing, and application is achieved. By clearly defining the boundaries of human resources, economic benefits, and supporting service costs, a unified calculation standard for direct costs is established, avoiding numerical deviations caused by decentralized accounting. The accounting method of multiplying the total direct cost by the availability weight coefficient can accurately quantify the implicit cost premium corresponding to the difficulty of sample acquisition into the comprehensive input cost. This allows scarce samples with high acquisition difficulty to reflect the matching comprehensive cost through a higher weight coefficient, realizing a full-dimensional cost consideration of both explicit direct input and implicit acquisition difficulty costs.

[0014] Optionally, the benefit association module includes: a scientific research achievement association unit, used to acquire scientific research achievement information associated with the usage records of the sample; a capacity building association unit, used to acquire capacity building information associated with the usage records of the sample, wherein the capacity building information is used to characterize the contribution of sample utilization to the development of the academic system or talent pool; a social and economic benefit association unit, used to acquire social and economic benefit information associated with the usage records of the sample; and a comprehensive benefit quantification unit, used to standardize and quantify the scientific research achievement information, the capacity building information, and the social and economic benefit information to generate the comprehensive output benefit.

[0015] Each associated unit establishes a mapping relationship of "sample - usage record - various output information" based on sample usage records, thereby ensuring the accurate binding of scientific research results, capacity building, social and economic benefits with the sample and guaranteeing the authenticity and relevance of various benefit information. Through these three associated units, a full-dimensional coverage of the output benefits of sample utilization is achieved, encompassing core scientific research results such as papers and patents, capacity building contributions to the academic system and talent development, and also taking into account the social and economic benefits of scientific research transformation and application. This compensates for the one-sidedness of solely calculating scientific research results and comprehensively represents the diverse value of the sample. The comprehensive benefit quantification unit, through standardized quantification rules, transforms various forms of output information that are difficult to directly compare into unified quantitative indicators that can be summed and compared, generating comprehensive output benefits. This solves the problem of inconsistent measurement standards for benefits across different dimensions, making the output benefits of different samples and projects horizontally comparable.

[0016] Optionally, the scientific research achievement information includes at least one of the following: paper information, patent information, and scientific research project information; the capacity building information includes at least one of the following: the construction level of the supported discipline or platform, the number of talents trained at each level, and the promotion status of relevant scientific researchers; the social and economic benefit information includes at least one of the following: the scope of the promotion and application of the achievement or the number of audiences, the amount of technology transfer contract or market valuation.

[0017] By defining and clarifying the indicators and scope of the three core output information categories—scientific research results, capacity building, and social and economic benefits—the problem of vague collection criteria and subjective evaluation of sample benefit information has been solved, ensuring the scientific, comprehensive, and operable nature of the multi-output benefit evaluation of the sample.

[0018] Optionally, the utilization efficiency evaluation index includes the input-output efficiency ratio, and the utilization efficiency evaluation module is specifically used to: calculate the ratio between the comprehensive output benefit and the comprehensive input cost, and use the ratio as the input-output efficiency ratio.

[0019] By combining comprehensive input cost considerations with multi-dimensional value representation of comprehensive output benefits, the assessment bias caused by single cost or benefit calculation is avoided. It can accurately and intuitively reflect the actual output benefits brought by each unit of input cost to sample utilization, clearly define the differences in utilization efficiency between different samples and different sample batches, and transform the originally abstract sample utilization efficiency into a quantitative value that can be compared horizontally and is traceable. This solves the problems of subjective efficiency assessment and lack of unified benchmark in traditional sample management.

[0020] Secondly, embodiments of this application provide a biobank management method, the method comprising: obtaining the comprehensive input cost of the sample based on the sample's availability weight coefficient, human resource cost, economic cost, and supporting service cost, wherein the availability weight coefficient is used to characterize the scarcity value of the sample; obtaining the comprehensive output benefit of the sample based on the scientific research results information, capacity building results information, and social and economic benefit information associated with the sample; and obtaining a utilization efficiency evaluation index based on the comprehensive input cost and the comprehensive output benefit, for sample resource decision management.

[0021] Thirdly, embodiments of this application provide a computer device, including: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the above-described biobank management method.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the above-described biobank management method.

[0023] Fifthly, embodiments of this application provide a computer program product, including computer instructions, which are used to cause a computer to execute the above-described biobank management method. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 A schematic diagram of a biobank management system provided in this application embodiment; Figure 2 A flowchart of a biobank management method provided in this application embodiment; Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Biobanks, as crucial material platforms for biomedical and clinical medical research, centrally preserve a large number of biological samples of various types, including tissues, cells, serum, plasma, and DNA, with extremely high scientific research value. With the deepening of precision medicine and big data research, the scale and complexity of biobanks are increasing daily, and the scientific and efficient management and operation of these biobanks have become key constraints on realizing their value. Currently, widely used biobank management systems primarily focus on basic operations such as sample collection, processing, long-term storage, information recording, retrieval, and inbound / outbound process management. These systems achieve digital management of the physical state and basic information of samples, but generally suffer from the following limitations: First, they lack scientific and quantitative efficiency evaluation functions. These systems typically only record static sample inventory and simple usage frequency (such as the number of times samples are requested), failing to provide in-depth and scientific quantitative evaluation of the overall utilization efficiency of sample resources. Managers struggle to objectively answer core questions such as "How much value has the investment in the biobank generated?" and "Which samples or projects have the highest benefits?" Second, cost accounting is fragmented and unsystematic. The collection, processing, preservation, and subsequent management of samples involve significant human, material, and financial resources, including manpower hours, reagents and consumables, equipment depreciation, and storage space. The lack of systematic recording, aggregation, and accounting for these comprehensive costs makes it impossible to accurately calculate the true input costs of individual samples or sample sets, resulting in a lack of a reliable cost basis for any efficiency assessment. Furthermore, output benefits are difficult to effectively link with sample utilization. The research results (such as papers, patents, and projects), talent cultivation, discipline development, and even socio-economic benefits generated after sample use are often disconnected from the sample's own management data in relevant systems. This disconnect makes it impossible to establish a traceability and correlation analysis from "sample use" to "multiple outputs," and the actual contribution and value of the samples cannot be accurately measured. Finally, decision support capabilities are weak. Due to the lack of integrated analysis and quantitative evaluation of input costs and output benefits, relevant systems struggle to provide managers with strong data support, fail to effectively identify high-value samples and high-efficiency projects, and struggle to discover areas of idle or inefficient resource utilization, thus hindering the optimal allocation of sample bank resources and the formulation of long-term strategic plans.

[0028] In summary, current biobank management systems are essentially closer to "static storage information recording systems," failing to evolve into "dynamic value management and decision support systems." Therefore, there is an urgent need in this field for an innovative management system that can deeply integrate refined sample management with in-depth utilization efficiency assessment to fully unleash the potential value of biobank resources.

[0029] Please refer to Figure 1 , Figure 1 This is a schematic diagram of a biobank management system provided in an embodiment of this application. The system can be deployed on a server or cloud platform of a biobank management center, such as... Figure 1 As shown, the system includes: a cost accounting module, used to obtain the comprehensive input cost of the sample based on the sample's availability weight coefficient, human resource cost, economic cost, and supporting service cost, and send the comprehensive input cost to the utilization efficiency evaluation module, wherein the availability weight coefficient is used to characterize the scarcity value of the sample; a benefit correlation module, used to obtain the comprehensive output benefit of the sample based on the scientific research results information, capacity building results information, and social and economic benefit information associated with the sample, and send the comprehensive output benefit to the utilization efficiency evaluation module; and a utilization efficiency evaluation module, used to obtain utilization efficiency evaluation indicators based on the comprehensive input cost and the comprehensive output benefit, for sample resource decision management.

[0030] The availability weighting coefficient is a numerical coefficient greater than or equal to 1, used to quantify the scarcity and difficulty of obtaining a sample. In practical applications, the weighting coefficient for an extremely rare case sample might be 10, while that for a common healthy control sample might be 1. Human resource costs refer to the costs incurred by various professionals (such as nurses, technicians, and researchers) throughout the entire process of sample collection, including questionnaire design, clinical information gathering, sample collection, processing, transportation, storage, and release. Economic costs refer to the direct monetary expenditures related to the sample, including reagents, consumables, collection tubes, storage boxes, liquid nitrogen, electricity, equipment depreciation, and dedicated storage space costs. Ancillary service costs refer to the additional service fees incurred when the sample is used in research, such as the costs of third-party or internal services like gene sequencing, proteomics analysis, and statistical data analysis. The comprehensive input cost is a quantitative assessment of the total resource value consumed in obtaining or preserving the sample. By introducing the availability weighting coefficient, non-monetary factors such as sample scarcity and difficulty of obtaining are quantified and integrated into cost accounting, making the assessment more scientific. Research output information refers to the direct research output generated after the sample is used, typically including published academic papers (and their journal impact factors, citation counts), patent applications (type, number, and commercialization status), and approved research projects (level, funding amount). Capacity building output information refers to the contribution of sample resource utilization to the institution's soft power, such as supporting the platform construction of a key discipline or laboratory, training graduate students / postdoctoral fellows based on the sample resources, and assisting researchers in obtaining professional titles. Social and economic benefit information refers to the broad impact of sample research, such as the citation of research results in clinical guidelines, the number of people influenced by public science education, income from technology transfer or licensing, and potential social health benefits for disease prevention and treatment. Comprehensive output benefit refers to the total quantification of the multi-dimensional value generated after the sample is utilized. By standardizing and summing the above information on research output, capacity building, and socio-economic benefits, a benefit value representing the total output is finally calculated.

[0031] Efficiency evaluation indicators are used to characterize the utilization efficiency and value of samples. In practical applications, the efficiency evaluation indicator can be the input-output ratio. By calculating the efficiency evaluation indicator, the complex problem of sample management is transformed into comparable and measurable data, providing a basis for sample resource management decisions. For example, samples with extremely high input-output ratios indicate high research and development efficiency and should receive more resource support. Samples with low input-output ratios indicate that they may not be fully utilized or that the research direction is not of high value. Based on this, managers can decide whether to stop collecting similar samples or actively promote existing idle samples. By comparing the efficiency indicators of different samples, managers can allocate limited human resources, funding, and storage space from inefficient areas to efficient areas, maximizing the overall value of the sample bank.

[0032] The biobank management system provided in this application monetizes the value of scarcity by introducing an availability weight coefficient and calculates human resource costs, economic costs, and supporting service costs to obtain a more scientific comprehensive input cost. By uniformly quantifying the scientific research results, capacity building results, and social and economic benefits associated with the samples into calculable benefit values, a strong correlation is established between the samples and the final comprehensive output benefits. Utilization efficiency evaluation indicators are calculated using comprehensive input costs and comprehensive output benefits to guide sample resource decision-making and management, thereby maximizing the overall value of the biobank.

[0033] In some specific embodiments, the system further includes a basic data module, which is connected to the cost accounting module and is used to provide the cost accounting module with the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the sample; the basic data module is also connected to the benefit correlation module and is used to provide the benefit correlation module with the usage records of the sample.

[0034] The basic data module is used to manage and maintain basic sample information and usage records. In practical applications, basic sample information includes sample ID, type, source, collection time, processing status, and storage location. Sample usage records can be structured data, including user ID, usage time, project ID, sample ID, and research purpose. The upper limit of sample size refers to the maximum theoretical or practically achievable reserve of a certain type of sample, or the extremely difficult-to-break scale limit. The incidence rate range refers to the proportion of new cases or existing patients within a specific reference population within a unit of time for the disease or physiological state corresponding to the sample. Dynamic adjustment factors are used to characterize real-time variables affecting the difficulty of sample acquisition. In practical applications, dynamic adjustment factors include sample integrity factors, ethical and compliance complexity factors, geographical accessibility factors, and time sensitivity factors. The sample integrity factor quantifies the impact of the completeness of the sample's accompanying data on the cost of sample acquisition and management. The ethical and compliance complexity factor considers the additional management costs incurred during sample collection, storage, and use due to ethical approval requirements and compliance restrictions; the coefficient is positively correlated with the complexity of ethical compliance. The geographic accessibility factor is used to quantify the impact of the geographic distribution of sample sources on the difficulty of obtaining them. The time sensitivity factor is used to differentiate the impact of the timeliness requirements of samples on processing and preservation costs.

[0035] The basic data module provides the cost accounting module with the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the samples. This ensures that the data sources for calculating the availability weight coefficient and the comprehensive input cost accounting are consistent and standardized, guaranteeing the scientific and accurate nature of cost quantification. Furthermore, the basic data module provides the benefit correlation module with sample usage records, resolving the disconnect between output benefits and sample data.

[0036] In some specific implementations, when a sample is requested for use, the basic data module automatically or after review generates a "sample usage record." This record is structured data, with key fields including: applicant (associated user ID), application time, purpose of use, project (associated project ID), list of sample identifiers used (associated sample ID set), and quantity requested. Each sample usage record is assigned a globally unique sample ID, serving as its lifelong identifier within the system.

[0037] In some specific embodiments, the system further includes a visualization analysis and reporting module and a system integration and security module. The visualization analysis and reporting module transforms efficiency evaluation indicators into intuitive graphics and structured reports, and provides an output and interaction module with a direct user interface for resource optimization decisions. The system integration and security module manages external data interfaces (such as epidemiological databases and academic literature repositories) and ensures data security and access control within the system.

[0038] In some specific implementations, the visualization analysis and reporting module integrates a front-end data visualization library to automatically generate various interactive charts. For example, radar charts can be used to compare the output of different projects across multiple dimensions such as scientific research, talent development, and social benefits; trend charts can be used to display the changes in core efficiency indicators over time; and bar charts can be used to compare the inputs and outputs of different sample types. After the calculations are completed, this module automatically populates the data and generates a detailed evaluation report.

[0039] In some specific implementations, the system integration and security module implements a role-based, fine-grained access control model to ensure that users can only operate on data and functions within their authorized scope. Simultaneously, it provides standardized APIs (Application Programming Interfaces) for data exchange with external systems. For example, it periodically and automatically synchronizes and updates disease incidence data from public databases; and it verifies and retrieves the journal and impact factor information of published papers through a DOI (Digital Object Identifier) ​​interface.

[0040] In some specific embodiments, the cost accounting module includes: an availability assessment unit, used to determine the availability weight coefficient of the sample based on the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the sample; a cost assessment unit, used to calculate the human resource cost, economic cost, and supporting service cost of the sample; and a comprehensive input cost calculation unit, used to generate the comprehensive input cost based on the availability weight coefficient, the human resource cost, the economic cost, and the supporting service cost.

[0041] The range of disease incidence and the upper limit of sample size are core dimensions for determining the basic scarcity of a sample. For example, the lower the incidence rate and the smaller the upper limit of sample size, the more difficult it is to obtain a sample, and the larger the basic weight coefficient determined by the range of disease incidence and the upper limit of sample size. Fine-tuning the basic weight coefficient based on a dynamic adjustment factor can yield a more accurate availability weight coefficient.

[0042] The availability assessment unit uses the disease incidence rate range, sample size limit, and dynamic adjustment factor as the basis for determining the availability weight coefficient, ensuring that the weight coefficient accurately reflects the actual difficulty of sample acquisition. Through step-by-step calculations using the cost assessment unit and the comprehensive input cost calculation unit, the actual input costs of human resources, economic resources, and supporting services are calculated separately first. Then, these costs are integrated with the availability weight coefficient to generate the comprehensive input cost. This approach achieves a comprehensive consideration of both the implicit costs corresponding to the difficulty of sample acquisition and the explicit costs of actual input, while also ensuring the traceability of the comprehensive input cost calculation logic and guaranteeing the accuracy of cost quantification. This provides precise cost data support for subsequent sample utilization efficiency assessments.

[0043] In some specific embodiments, the availability assessment unit is specifically used to: determine a basic weight coefficient based on the disease incidence rate range and the upper limit of the sample size; and adjust the basic weight coefficient based on the dynamic adjustment factor to generate the availability weight coefficient.

[0044] By determining the basic weight coefficients using both the disease incidence rate range and the upper limit of sample size, the one-sidedness of relying solely on the incidence rate dimension is avoided, providing a clear and quantifiable basis for the generation of basic weights. Targeted adjustments to the basic weight coefficients through dynamic factor adjustment incorporate various practical influencing factors during sample acquisition, besides basic scarcity, into the weighting considerations. This achieves refined calibration of the basic weights, ensuring that the final availability weight coefficients comprehensively and accurately reflect the true difficulty of sample availability.

[0045] In some specific implementations, the availability assessment unit includes a sample classification and basic weight mapping rule library. The preset rules are as follows: based on the incidence rate (p) of the disease associated with the sample and the existing sample library's stock (s), the sample type is automatically classified and assigned a value: 1) If p≤1 / 10000 and s≤10 cases, then it is classified as a particularly rare sample and given a basic weight of 10.

[0046] 2) If 1 / 10000 < p and s ≤ 100 cases, then it is classified as a rare sample and assigned a basic weight of 5.

[0047] 3) If 1 / 1000 < p ≤ 1 / 100 and 100 < s ≤ 3000 cases, then it is classified as a common sample and assigned a basic weight of 2.

[0048] 4) If p > 1 / 100 and s > 3000 cases, then classify it as a sample that is available at any time and assign it a basic weight of 1.

[0049] Incidence data can be updated periodically (e.g., every two years) from the epidemiological database through the system integration and security module interface.

[0050] To achieve refined evaluation, dynamic adjustment factors are introduced to modify the basic weights. These dynamic adjustment factors include sample integrity (F1), ethical and compliance complexity (F2), geographic accessibility (F3), and time sensitivity (F4). Each dynamic adjustment factor can be selected or entered based on the actual situation when the sample is entered into the database. 1) Sample integrity factor: 1.0 when only biological samples are available; 1.2 when basic clinical information is included; 1.5 to 2.0 when long-term follow-up and multi-omics data are included.

[0051] 2) Ethics and compliance complexity factor: 1.0 for ordinary adult samples; 1.3 to 1.8 for samples involving genetic information, minors, etc.

[0052] 3) Geographic accessibility factor: 1.0 for accessibility at a single center; 1.5 for accessibility requiring collaboration across three or more provinces.

[0053] 4) Time sensitivity factor: 1.0 for frozen stable samples; 1.5 to 2.0 for fresh samples that need to be processed within 24 hours.

[0054] The formula for calculating the availability weight coefficient w is: w = basic weight × F1 × F2 × F3 × F4.

[0055] In some specific embodiments, the comprehensive input cost calculation unit is specifically used to: calculate the sum of the labor cost, the economic cost, and the supporting service cost to obtain the total direct cost; multiply the total direct cost by the availability weight coefficient, and use the product as the comprehensive input cost.

[0056] By summing the costs of human resources, economic benefits, and supporting services to obtain the total direct cost, a centralized and integrated accounting of various explicit actual input costs in the process of sample acquisition, processing, and application is achieved. By clearly defining the boundaries of human resources, economic benefits, and supporting service costs, a unified calculation standard for direct costs is established, avoiding numerical deviations caused by decentralized accounting. The accounting method of multiplying the total direct cost by the availability weight coefficient can accurately quantify the implicit cost premium corresponding to the difficulty of sample acquisition into the comprehensive input cost. This allows scarce samples with high acquisition difficulty to reflect the matching comprehensive cost through a higher weight coefficient, realizing a full-dimensional cost consideration of both explicit direct input and implicit acquisition difficulty costs.

[0057] In some specific implementations, labor costs are calculated as follows: A standardized time entry template is provided. The time consumed in each stage of sample collection, including questionnaire collection, clinical information gathering, physical collection, processing, storage, and release, is recorded and categorized by operator title (senior, intermediate, and junior). Based on preset time cost coefficients for different title units (e.g., a ratio of 10:5:1), labor costs are automatically calculated.

[0058] Economic costs are calculated as follows: A form is provided to record direct economic expenditures related to the sample, including the cost of questionnaire printing, collection consumables, processing reagents, storage consumables (such as liquid nitrogen), as well as equipment depreciation amortization (calculated based on equipment value / specified service life / number of samples to be carried) and dedicated storage space costs. The economic costs are then summed up.

[0059] The cost of supporting services is calculated as follows: third-party or internal supporting costs such as testing fees, sequencing fees, and data analysis service fees incurred when the collected samples are used in research.

[0060] In some specific embodiments, the benefit association module includes: a scientific research achievement association unit, used to acquire scientific research achievement information associated with the usage records of the sample; a capacity building association unit, used to acquire capacity building information associated with the usage records of the sample, wherein the capacity building information is used to characterize the contribution of sample utilization to the development of the academic system or talent pool; a social and economic benefit association unit, used to acquire social and economic benefit information associated with the usage records of the sample; and a comprehensive benefit quantification unit, used to standardize and quantify the scientific research achievement information, the capacity building information, and the social and economic benefit information to generate the comprehensive output benefit.

[0061] Each associated unit establishes a mapping relationship of "sample - usage record - various output information" based on sample usage records, thereby ensuring the accurate binding of scientific research results, capacity building, social and economic benefits with the sample and guaranteeing the authenticity and relevance of various benefit information. Through these three associated units, a full-dimensional coverage of the output benefits of sample utilization is achieved, encompassing core scientific research results such as papers and patents, capacity building contributions to the academic system and talent development, and also taking into account the social and economic benefits of scientific research transformation and application. This compensates for the one-sidedness of solely calculating scientific research results and comprehensively represents the diverse value of the sample. The comprehensive benefit quantification unit, through standardized quantification rules, transforms various forms of output information that are difficult to directly compare into unified quantitative indicators that can be summed and compared, generating comprehensive output benefits. This solves the problem of inconsistent measurement standards for benefits across different dimensions, making the output benefits of different samples and projects horizontally comparable.

[0062] In some specific implementations, the research achievement association unit provides an achievement registration interface or API interface. After a paper is published, a patent is granted, or a project is approved, the project leader logs into the system, selects the corresponding project and the set of sample IDs used based on the historical "sample usage record," and enters the achievement details. For example, this includes: the paper's title, journal, impact factor, and citation count; the patent's number, type (invention or utility model), commercialization status, and estimated value; and the project's name, level, and approved funding amount. The system can standardize non-monetary outputs according to preset rules; for example, an impact factor of 1.0 is counted as 1 standard benefit unit, one invention patent is counted as 2 units, and project funding can be converted into benefit value at a certain percentage (e.g., 20%).

[0063] The capacity building related unit supports the input of information on the contribution of sample resources to discipline development, key laboratory platform construction, number of graduate students and postdoctoral fellows trained, and promotion of researchers, and quantifies it into benefit value according to preset rules.

[0064] The social and economic benefit assessment unit supports the entry of social benefits (such as the number of people impacted by popular science and the number of clinical guideline citations) and direct economic benefits (such as the amount of technology transfer contracts) generated by research findings. For example, it can be calculated according to the rule of "10,000 yuan of benefit for every 100 people impacted".

[0065] The comprehensive benefit quantification unit obtains the comprehensive benefit of the sample or sample set by summing up all the quantified benefit values ​​mentioned above.

[0066] In some specific embodiments, the scientific research results information includes at least one of paper information, patent information, and scientific research project information; the capacity building information includes at least one of the construction level of the supported discipline or platform, the number of talents trained at each level, and the promotion status of relevant scientific researchers; the social and economic benefits information includes at least one of the scope of application of the results or the number of audiences, the amount of technology transfer contracts, or the market valuation.

[0067] By focusing on core research outputs such as papers, patents, and research projects, and by covering academic and talent development dimensions including discipline or platform construction, talent cultivation at all levels, and the promotion of researchers' professional titles, the project achieves comprehensive coverage of the diverse values ​​generated by sample utilization. This overcomes the limitations of single-dimensional evaluation and ensures that all related benefit information represents a substantial contribution from sample utilization, while avoiding cross-attribution and duplicate statistics of benefits from different dimensions. By transforming diverse forms of output information into summable and comparable unified quantitative values, the project significantly reduces the difficulty of standardization and quantification, enhances the objectivity and horizontal comparability of quantitative results, and provides a unified benchmark for comparing the output benefits of different samples and projects.

[0068] By defining and clarifying the indicators and scope of the three core output information categories—scientific research results, capacity building, and social and economic benefits—the problem of vague collection criteria and subjective evaluation of sample benefit information has been solved, ensuring the scientific, comprehensive, and operable nature of the multi-output benefit evaluation of the sample.

[0069] In some specific embodiments, the utilization efficiency evaluation index includes the input-output efficiency ratio, and the utilization efficiency evaluation module is specifically used to: calculate the ratio between the comprehensive output benefit and the comprehensive input cost, and use the ratio as the input-output efficiency ratio.

[0070] By combining comprehensive input cost considerations with multi-dimensional value representation of comprehensive output benefits, the assessment bias caused by single cost or benefit calculation is avoided. It can accurately and intuitively reflect the actual output benefits brought by each unit of input cost to sample utilization, clearly define the differences in utilization efficiency between different samples and different sample batches, and transform the originally abstract sample utilization efficiency into a quantitative value that can be compared horizontally and is traceable. This solves the problems of subjective efficiency assessment and lack of unified benchmark in traditional sample management.

[0071] In some specific implementations, the efficiency evaluation metric also includes sample turnover rate. During the evaluation period, the sample turnover rate is calculated as the percentage of samples that have been used out of the total sample size.

[0072] In some specific implementations, the efficiency evaluation metric also includes the resource idle rate. During the evaluation period, the cumulative total input cost of unused samples is calculated as a percentage of the total cost of the sample library; this percentage yields the resource idle rate.

[0073] Accordingly, please refer to Figure 2 , Figure 2 A flowchart of a biobank management method provided for embodiments of this application is shown below. Figure 2 As shown, the method includes: Step S1: Based on the availability weight coefficient, human resource cost, economic cost and supporting service cost of the sample, the comprehensive input cost of the sample is obtained, wherein the availability weight coefficient is used to characterize the scarcity value of the sample.

[0074] Step S3: Based on the scientific research results information, capacity building results information, and social and economic benefit information associated with the sample, obtain the comprehensive output benefit of the sample.

[0075] Step S5: Based on the comprehensive input cost and the comprehensive output benefit, obtain the utilization efficiency evaluation index for sample resource decision management.

[0076] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0077] In this embodiment, the biobank management system is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit), a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0078] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application, such as... Figure 3As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 3 Take a processor 10 as an example.

[0079] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0080] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0081] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0082] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0083] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0084] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0085] This application provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method of any embodiment of this application.

[0086] The systems and modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0087] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0088] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] This application is described with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0090] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0091] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0092] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0093] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0094] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

[0095] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A biobank management system, characterized in that, The system includes: The cost accounting module is used to obtain the comprehensive input cost of the sample based on the availability weight coefficient, human resource cost, economic cost and supporting service cost, and send the comprehensive input cost to the utilization efficiency evaluation module. The availability weight coefficient is used to characterize the scarcity value of the sample. The benefit correlation module is used to obtain the comprehensive output benefit of the sample based on the scientific research results information, capacity building results information and social and economic benefit information associated with the sample, and send the comprehensive output benefit to the utilization efficiency evaluation module. The efficiency evaluation module is used to obtain utilization efficiency evaluation indicators based on the comprehensive input cost and the comprehensive output benefit, so as to carry out sample resource decision management.

2. The system according to claim 1, characterized in that, The system also includes a basic data module, which is connected to the cost accounting module and is used to provide the cost accounting module with the disease incidence rate range, sample size limit, and dynamic adjustment factor corresponding to the sample; the basic data module is also connected to the benefit correlation module and is used to provide the benefit correlation module with the usage records of the sample.

3. The system according to claim 2, characterized in that, The cost accounting module includes: The availability assessment unit is used to determine the availability weight coefficient of the sample based on the disease incidence range, sample size limit, and dynamic adjustment factor corresponding to the sample. The cost assessment unit is used to calculate the labor cost, economic cost, and supporting service cost of the sample. The comprehensive input cost calculation unit is used to generate the comprehensive input cost based on the availability weight coefficient, the human resource cost, the economic cost, and the supporting service cost.

4. The system according to claim 3, characterized in that, The availability assessment unit is specifically used for: The basic weighting coefficients are determined based on the disease incidence rate range and the upper limit of the sample size. The basic weight coefficients are adjusted based on the dynamic adjustment factor to generate the availability weight coefficients.

5. The system according to claim 3, characterized in that, The comprehensive input cost calculation unit is specifically used for: Calculate the sum of the labor cost, the economic cost, and the supporting service cost to obtain the total direct cost; Multiply the sum of direct costs by the availability weighting coefficient, and use the product as the comprehensive input cost.

6. The system according to claim 2, characterized in that, The benefit-related module includes: The scientific research achievement association unit is used to obtain scientific research achievement information associated with the usage records of the sample; A capacity-building association unit is used to acquire capacity-building information associated with the usage records of the sample, wherein the capacity-building information is used to characterize the contribution of the sample utilization to the development of the academic system or talent pool; A social and economic benefit correlation unit is used to obtain social and economic benefit information associated with the usage records of the sample; The comprehensive benefit quantification unit is used to standardize and quantify the scientific research results information, the capacity building information, and the social and economic benefit information to generate the comprehensive output benefit.

7. The system according to claim 6, characterized in that, The scientific research achievements information includes at least one of the following: paper information, patent information, and scientific research project information; the capacity building information includes at least one of the following: the construction level of the supported discipline or platform, the number of talents trained at each level, and the promotion status of relevant scientific researchers; the social and economic benefits information includes at least one of the following: the scope of the promotion and application of the achievements or the number of audiences, the amount of technology transfer contracts, or the market valuation.

8. The system according to claim 1, characterized in that, The utilization efficiency evaluation index includes the input-output efficiency ratio, and the utilization efficiency evaluation module is specifically used for: Calculate the ratio between the overall output benefit and the overall input cost, and use the ratio as the input-output efficiency ratio.

9. A method for managing a biobank, characterized in that, The method includes: The comprehensive input cost of the sample is obtained based on the availability weight coefficient, human resource cost, economic cost and supporting service cost, wherein the availability weight coefficient is used to characterize the scarcity value of the sample. Based on the scientific research achievements, capacity building achievements, and social and economic benefits associated with the sample, the comprehensive output benefits of the sample are obtained. Based on the comprehensive input cost and the comprehensive output benefit, utilization efficiency evaluation indicators are obtained for sample resource decision management.

10. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the biobank management method of claim 9.

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