A laboratory process standardization intelligent processing system and method

Abstract

This invention discloses an intelligent processing system and method based on laboratory process standardization, belonging to the field of intelligent processing technology. The system includes a change clause extraction module, a core change identification module, an equivalent node mapping module, and a historical data adaptation module. The method obtains the old and new versions of standard operating procedures, compares and extracts target change clauses, divides core and non-core change clauses and constructs a version difference chain, establishes equivalent node mapping relationships for core change nodes, and converts old process nodes and processes historical experimental data based on these relationships to reconstruct historical experimental processes adapted to the new version of the procedures. This invention solves the problems of low efficiency, easy omissions, and difficulty in adapting complex nodes in manual processing, improves the level of process standardization automation and data adaptation accuracy, and ensures the traceability of experimental results.

Description

Technical Field

[0001] This invention relates to the field of intelligent processing technology, specifically to an intelligent processing system and method based on standardized laboratory processes. Background Technology

[0002] Standard operating procedures (SOPs) are the core basis for laboratories to conduct standardized experimental operations and ensure the accuracy and traceability of experimental results. In daily operations, laboratories continuously revise SOPs due to factors such as technological upgrades, updated standards, and equipment iterations, with changes primarily involving modifications to operating parameters being the most common.

[0003] Currently, when processing standard operating procedure (SOP) version updates, laboratories often rely on manual comparison of each clause and manual conversion of historical experimental data. This approach is not only inefficient and prone to human error, but also fails to accurately identify core changes that significantly impact process execution. Furthermore, complex one-to-many and many-to-one correspondences often exist between old and new versions of the process nodes. Existing technologies lack standardized rules for determining and mapping equivalent nodes, making it difficult to adapt historical experimental data to the new SOP version and hindering automated traceability and consistency verification across versions. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent processing system and method based on standardized laboratory procedures to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] A standardized intelligent processing method based on laboratory procedures includes the following steps:

[0007] S1. Obtain the standard operating procedures for the new and old versions, compare the process nodes and operating parameters, define the modified clauses as target change clauses, and extract all target change clauses;

[0008] S2. Preset the threshold for the impact of process execution, classify target change clauses whose operational parameter deviations exceed the threshold as core target change clauses, and the rest as non-core target change clauses; construct a version difference chain and mark the core target change nodes;

[0009] S3. For the core target change nodes in the version difference chain, extract the operation objects, experimental steps and result indicators of the old and new process nodes and match them; when the operation objects of the old and new nodes are the same and the deviation of their result indicators is within the preset equivalent allowable range, they are determined to be equivalent nodes; if one process node of the old version corresponds to multiple process nodes of the new version, then according to the preset combination rule library, the operation data of the old node is split and mapped to multiple new nodes to establish a one-to-many or many-to-one equivalent node mapping relationship.

[0010] S4. Retrieve historical experimental data and its associated old version standard operating procedures. Based on the equivalent node mapping relationship, convert the old version process nodes corresponding to the historical experimental data into equivalent process nodes under the new version standard operating procedures, and reconstruct the historical experimental process corresponding to the new version procedures.

[0011] Furthermore, S1 includes the following:

[0012] Collect the old version and the new version of the standard operating procedure, extract all experimental process nodes of the two versions of the procedure and assign a unique node identifier to each process node, and extract the corresponding operating parameters of each node, including process parameters and equipment operating parameters.

[0013] Based on node identifiers, the nodes and operating parameters of the two versions of the procedure are compared. Clauses with the same node identifiers but different operating parameters are defined as target change clauses. All target change clauses are identified and screened out, and the node identifiers and differences in operating parameters corresponding to each target change clause are recorded.

[0014] Furthermore, S2 includes the following:

[0015] The preset process execution impact threshold is set based on laboratory quality control standards, experiment type, and equipment characteristics. For each target change clause, the operational parameter deviation impact coefficient is calculated. This coefficient is the sum of the products of the deviation ratio of each operational parameter and its corresponding weight. The weight is set according to the degree of influence of the parameter on the experimental results, and the sum of all weights is 1.

[0016] Based on the comparison between the operational parameter deviation impact coefficient and the preset threshold, the target change clauses are divided into core target change clauses and non-core target change clauses; combined with the classification results, a version difference chain is constructed, and the node identifiers and corresponding operational parameter deviation impact coefficients of all core target change nodes are marked.

[0017] Furthermore, S3 includes the following:

[0018] Extract the new and old process node information corresponding to the core objective change node. The node information includes the operation object, experimental steps and result indicators. The extracted information is then standardized to eliminate expression differences and redundant information.

[0019] The three core dimensions for equivalence determination are defined as the matching degree of the operation object, the similarity of the experimental procedure, and the deviation of the result index. A corresponding weight is set for each dimension, and the sum of the weights of each dimension is 1. The weights are set according to the degree of influence of each dimension on the equivalence of the experimental procedure, and are calibrated by combining historical data statistical analysis, industry standard comparison and experimental verification.

[0020] A preset equivalent allowable threshold is used to calculate quantified values ​​for three dimensions for each core target change node. The matching degree of the operation object is determined based on the consistency of the operation objects of the new and old nodes; the similarity of the experimental steps is determined based on the overlap of the experimental steps of the new and old nodes; and the deviation of the result index is determined based on the relative deviation of the result index of the new and old nodes. The comprehensive equivalent deviation coefficient of the new and old nodes is calculated by weighted summation of the quantified values ​​of the three dimensions and their corresponding weights.

[0021] When the comprehensive equivalent deviation coefficient is less than or equal to the preset equivalent allowable threshold, the new and old nodes are determined to be equivalent nodes, and a one-to-one equivalent node mapping relationship is established.

[0022] For a core objective change node in the old version of the standard operating procedure (SOP), corresponding to multiple process nodes in the new version of the SOP, a splitting and mapping method is determined based on a pre-defined combination rule base. This combination rule base includes splitting and merging mapping rules based on experimental functions, sample types, process sequence, and node importance. The operation data of the old node is extracted, and a splitting weight is calculated for each corresponding new node. The sum of the splitting weights of all new nodes corresponding to the same old node is a fixed value. The splitting weight is determined based on the proportion of experimental functions undertaken by each new node, which is quantified based on the number of experimental steps, sample allocation ratio, or functional importance score. Based on the splitting weight, the operation data of the old node is split and mapped to multiple corresponding new nodes, establishing a one-to-many equivalent node mapping relationship.

[0023] For the case where multiple core target change nodes in the old version of the standard operating procedure correspond to a single process node in the new version of the standard operating procedure, the operation data of multiple old nodes are aggregated and mapped to the new node based on the combined rule base, thus establishing a many-to-one equivalent node mapping relationship.

[0024] Furthermore, S4 includes the following:

[0025] Collect the set of historical experimental data stored in the laboratory, and simultaneously retrieve the old version of the standard operating procedure and the corresponding old version process node identifier associated with each historical experimental data, and establish a one-to-one correspondence between historical experimental data and old version process nodes.

[0026] Based on the constructed equivalent node mapping table, the old version process node identifier corresponding to each historical experimental data is traversed, and the equivalent process node identifier corresponding to it under the new version standard operating procedure is retrieved. For one-to-one mapping relationships, a unique equivalent process node identifier is directly determined. For one-to-many mapping relationships, a set of multiple equivalent process node identifiers is determined. For many-to-one mapping relationships, multiple old version process node identifiers are merged and mapped to the same equivalent process node identifier, thus completing the matching of old and new version process node identifiers.

[0027] Historical experimental operation data is processed separately for different mapping relationships. Specifically: for one-to-one mapping, the historical experimental operation data corresponding to the old process node is completely migrated to the new equivalent process node; for one-to-many mapping, the historical experimental operation data corresponding to the old process node is proportionally split and distributed to multiple corresponding new equivalent process nodes according to the preset split weight; for many-to-one mapping, the historical experimental operation data corresponding to multiple old process nodes is summarized, and duplicate parameter items are merged and conflicting parameter items are selected according to the preset priority during integration. Then, the summarized data is mapped to the same new equivalent process node.

[0028] Based on the process node sequence of the new version standard operating procedure, the processed historical experimental operation data is classified according to the equivalent process node identifier. The execution order of each equivalent process node is arranged according to the experimental sequence rules. Redundant data that conflicts with the process sequence of the new version procedure is removed, and necessary data items required by the new version procedure are added. Finally, the historical experimental process corresponding to the new version standard operating procedure is reconstructed, and the cross-version process adaptation of historical experimental data is completed.

[0029] A standardized intelligent processing system for laboratory procedures includes: a change clause extraction module, a core change identification module, an equivalent node mapping module, and a historical data adaptation module.

[0030] The change clause extraction module obtains the standard operating procedures for both the old and new versions, extracts the experimental process nodes and operating parameters of the two versions of the procedures, compares the differences in nodes and parameters, defines and filters the target change clauses, and records the node identifiers and parameter differences of the target change clauses.

[0031] The core change identification module presets the impact threshold of process execution, calculates the impact coefficient of the deviation of operation parameters of each target change clause, divides the core and non-core target change clauses according to the comparison of the coefficient and the threshold, constructs the version difference chain and marks the core target change nodes;

[0032] The equivalent node mapping module extracts the old and new process node information of the core target change node and standardizes it, sets the equivalence judgment dimension and weight, calculates the comprehensive equivalence deviation coefficient, judges the equivalent nodes, and establishes one-to-one, one-to-many and many-to-one equivalent node mapping relationships.

[0033] The historical data adaptation module collects historical experimental data from the laboratory, retrieves the old version of the procedures and node identifiers associated with the data, matches the old and new node identifiers according to the equivalent node mapping relationship, processes and migrates the historical data, and reconstructs the historical experimental process to adapt to the new version of the procedures.

[0034] Furthermore, the change clause extraction module includes a procedure collection unit and a clause filtering unit;

[0035] The procedure acquisition unit collects the old and new versions of standard operating procedures, extracts all experimental process nodes of the two versions of procedures and assigns unique node identifiers, and extracts the process parameters and equipment operating parameters corresponding to each node.

[0036] The clause filtering unit uses node identifiers as the matching basis, compares the nodes and operation parameters of the two versions of the procedure, identifies and filters target change clauses with the same node identifiers but different parameters, and records the differences in node identifiers and operation parameters of each target change clause.

[0037] Furthermore, the core change identification module includes a threshold setting unit and a change classification unit;

[0038] The threshold setting unit presets the process execution impact threshold based on laboratory quality control standards, experiment type and equipment characteristics, sets the weight of each operation parameter and ensures that the sum of all weights is 1, and calculates the operation parameter deviation impact coefficient for each target change clause.

[0039] The change classification unit divides core and non-core target change clauses based on the comparison between the operational parameter deviation impact coefficient and the preset threshold, constructs a version difference chain containing change clause details and classification identifiers, and marks the core target change nodes and their corresponding impact coefficients.

[0040] Furthermore, the equivalent node mapping module includes an information processing unit and a mapping establishment unit;

[0041] The information processing unit extracts the information of the old and new process nodes of the core target change node and standardizes it, defines three core dimensions for equivalence judgment and their corresponding weights, presets the equivalence allowable threshold, calculates the quantitative value of each dimension and the comprehensive equivalence deviation coefficient, and judges the equivalent nodes.

[0042] The mapping establishment unit determines one-to-many and many-to-one mapping methods based on the combination rule base, calculates the split weight and quantifies the functional proportion, splits or summarizes the old node operation data, and establishes various equivalent node mapping relationships.

[0043] Furthermore, the historical data adaptation module includes a data association unit and a process refactoring unit;

[0044] The data association unit collects historical experimental data sets, retrieves the old version of the procedures and old version of the process node identifiers associated with each data, establishes a one-to-one correspondence between historical experimental data and old version process nodes, matches the new and old process node identifiers, and processes the corresponding historical data.

[0045] The process reconstruction unit uses the process node sequence of the new version of the procedure as a benchmark, classifies, sorts, removes redundancy and supplements necessary data on the processed historical data, and reconstructs the historical experimental process corresponding to the new version of the standard operating procedure, thus completing the cross-version data adaptation.

[0046] Compared with existing technologies, the beneficial effects of this invention are as follows: By acquiring the standard operating procedures of the old and new versions and comparing process nodes, operating parameters, and the impact coefficient of operating parameter deviations, this invention accurately identifies target change clauses and core change clauses, constructs version difference chains, and marks core nodes, thereby achieving accurate classification and quantification of the impact of change clauses; by extracting the operation objects, experimental steps, and result indicators of the old and new process nodes and standardizing them, and combining the weight settings of three dimensions—operation object matching degree, experimental step similarity, and result indicator deviation degree—and the calculation of comprehensive equivalent deviation coefficients, it accurately determines equivalent nodes and establishes one-to-one, one-to-many, and many-to-one equivalent mapping relationships, thereby achieving equivalent matching and data splitting and summary mapping of the old and new process nodes; by retrieving historical experimental data and completing process node conversion and process reconstruction based on the equivalent node mapping relationship, it achieves cross-version adaptation of historical experimental data, solving the problems of low efficiency, easy omissions, inability to accurately identify core changes, and difficulty in data adaptation under complex correspondences in existing technologies, improving the automation level and data adaptation accuracy of laboratory process standardization processing, and ensuring the accuracy and traceability of experimental results. Attached Figure Description

[0047] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0048] Figure 1 This is a schematic diagram of a module of an intelligent processing system based on standardized laboratory processes according to the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Please see Figure 1The present invention provides the following technical solution:

[0051] A standardized intelligent processing system for laboratory procedures includes: a change clause extraction module, a core change identification module, an equivalent node mapping module, and a historical data adaptation module.

[0052] The change clause extraction module obtains the standard operating procedures for both the old and new versions, extracts the experimental process nodes and operating parameters of the two versions of the procedures, compares the differences in nodes and parameters, defines and filters the target change clauses, and records the node identifiers and parameter differences of the target change clauses.

[0053] The core change identification module presets the impact threshold of process execution, calculates the impact coefficient of the deviation of operation parameters of each target change clause, divides the core and non-core target change clauses according to the comparison of the coefficient and the threshold, constructs the version difference chain and marks the core target change nodes;

[0054] The equivalent node mapping module extracts the old and new process node information of the core target change node and standardizes it, sets the equivalence judgment dimension and weight, calculates the comprehensive equivalence deviation coefficient, judges the equivalent nodes, and establishes one-to-one, one-to-many and many-to-one equivalent node mapping relationships.

[0055] The historical data adaptation module collects historical experimental data from the laboratory, retrieves the old version of the procedures and node identifiers associated with the data, matches the old and new node identifiers according to the equivalent node mapping relationship, processes and migrates the historical data, and reconstructs the historical experimental process to adapt to the new version of the procedures.

[0056] The change clause extraction module includes a procedure collection unit and a clause filtering unit;

[0057] The procedure acquisition unit collects the old and new versions of standard operating procedures, extracts all experimental process nodes of the two versions of procedures and assigns unique node identifiers, and extracts the process parameters and equipment operating parameters corresponding to each node.

[0058] The clause filtering unit uses node identifiers as the matching basis, compares the nodes and operation parameters of the two versions of the procedure, identifies and filters target change clauses with the same node identifiers but different parameters, and records the differences in node identifiers and operation parameters of each target change clause.

[0059] The core change identification module includes a threshold setting unit and a change classification unit;

[0060] The threshold setting unit presets the process execution impact threshold based on laboratory quality control standards, experiment type and equipment characteristics, sets the weight of each operation parameter and ensures that the sum of all weights is 1, and calculates the operation parameter deviation impact coefficient for each target change clause.

[0061] The change classification unit divides core and non-core target change clauses based on the comparison between the operational parameter deviation impact coefficient and the preset threshold, constructs a version difference chain containing change clause details and classification identifiers, and marks the core target change nodes and their corresponding impact coefficients.

[0062] The equivalent node mapping module includes an information processing unit and a mapping establishment unit;

[0063] The information processing unit extracts the information of the old and new process nodes of the core target change node and standardizes it, defines three core dimensions for equivalence judgment and their corresponding weights, presets the equivalence allowable threshold, calculates the quantitative value of each dimension and the comprehensive equivalence deviation coefficient, and judges the equivalent nodes.

[0064] The mapping establishment unit determines one-to-many and many-to-one mapping methods based on the combination rule base, calculates the split weight and quantifies the functional proportion, splits or summarizes the old node operation data, and establishes various equivalent node mapping relationships.

[0065] The historical data adaptation module includes a data association unit and a process refactoring unit;

[0066] The data association unit collects historical experimental data sets, retrieves the old version of the procedures and old version of the process node identifiers associated with each data, establishes a one-to-one correspondence between historical experimental data and old version process nodes, matches the new and old process node identifiers, and processes the corresponding historical data.

[0067] The process reconstruction unit uses the process node sequence of the new version of the procedure as a benchmark, classifies, sorts, removes redundancy and supplements necessary data on the processed historical data, and reconstructs the historical experimental process corresponding to the new version of the standard operating procedure, thus completing the cross-version data adaptation.

[0068] A standardized intelligent processing method based on laboratory procedures includes the following steps:

[0069] S1. Obtain the standard operating procedures for the new and old versions, compare the process nodes and operating parameters, define the modified clauses as target change clauses, and extract all target change clauses;

[0070] S2. Preset the threshold for the impact of process execution, classify target change clauses whose operational parameter deviations exceed the threshold as core target change clauses, and the rest as non-core target change clauses; construct a version difference chain and mark the core target change nodes;

[0071] S3. For the core target change nodes in the version difference chain, extract the operation objects, experimental steps and result indicators of the old and new process nodes and match them; when the operation objects of the old and new nodes are the same and the deviation of their result indicators is within the preset equivalent allowable range, they are determined to be equivalent nodes; if one process node of the old version corresponds to multiple process nodes of the new version, then according to the preset combination rule library, the operation data of the old node is split and mapped to multiple new nodes to establish a one-to-many or many-to-one equivalent node mapping relationship.

[0072] S4. Retrieve historical experimental data and its associated old version standard operating procedures. Based on the equivalent node mapping relationship, convert the old version process nodes corresponding to the historical experimental data into equivalent process nodes under the new version standard operating procedures, and reconstruct the historical experimental process corresponding to the new version procedures.

[0073] S1 includes the following:

[0074] Collect the old version and the new version of the standard operating procedure, extract all experimental process nodes of the two versions of the procedure and assign a unique node identifier to each process node, and extract the corresponding operating parameters of each node, including process parameters and equipment operating parameters.

[0075] Based on node identifiers, the nodes and operating parameters of the two versions of the procedure are compared. Clauses with the same node identifiers but different operating parameters are defined as target change clauses. All target change clauses are identified and screened out, and the node identifiers and differences in operating parameters corresponding to each target change clause are recorded.

[0076] In this embodiment, the old and new versions of the laboratory standard operating procedures are collected and denoted as SO and SN, respectively. All experimental process nodes in the two versions of the procedures are extracted, and each process node corresponds to a unique node identifier. At the same time, the operation parameters corresponding to each node are extracted. The operation parameters include, but are not limited to, experimental process parameters and equipment operating parameters, forming the SO node parameter set PO={PO1,PO2,...,POn} and the SN node parameter set PN={PN1,PN2,...,PNm}, where n and m are the number of process nodes in SO and SN, respectively.

[0077] Target change clauses are defined as clauses where SO and SN have the same node identifier but different corresponding operation parameters. Based on the node identifier, the nodes of PO and PN are compared to identify and filter out all target change clauses, and the node identifier and operation parameter differences corresponding to each target change clause are recorded simultaneously.

[0078] S2 includes the following:

[0079] The preset process execution impact threshold is set based on laboratory quality control standards, experiment type, and equipment characteristics. For each target change clause, the operational parameter deviation impact coefficient is calculated. This coefficient is the sum of the products of the deviation ratio of each operational parameter and its corresponding weight. The weight is set according to the degree of influence of the parameter on the experimental results, and the sum of all weights is 1.

[0080] Based on the comparison between the operational parameter deviation impact coefficient and the preset threshold, the target change clauses are divided into core target change clauses and non-core target change clauses; combined with the classification results, a version difference chain is constructed, and the node identifiers and corresponding operational parameter deviation impact coefficients of all core target change nodes are marked.

[0081] In this embodiment, a preset threshold T for the impact of process execution is used, where T is a constant set based on laboratory quality control standards, experiment type, and equipment characteristics to determine the degree of impact of target change clauses on the execution of the experimental process. For all identified target change clauses, an operational parameter deviation impact coefficient K is calculated for each individual change clause, where K = ∑(|PNj-POi| / POi) × Wk, where PNj is the operational parameter value of the corresponding target change node in SN, POi is the operational parameter value of the corresponding target change node in SO, and Wk is the weight of the corresponding operational parameter, with the weight set according to the degree of influence of the parameter on the experimental results, and the sum of all parameter weights is 1.

[0082] The target change clauses are classified according to the calculated K value. When K > T, they are determined to be core target change clauses; when K ≤ T, they are determined to be non-core target change clauses. Based on the above classification results of the target change clauses, a version difference chain is constructed. The version difference chain includes the node identifiers, operational parameter differences, and core or non-core classification identifiers of all target change clauses. The node identifiers of all core target change nodes are marked. For core target change nodes, the corresponding operational parameter deviation influence coefficient K value needs to be additionally marked.

[0083] S3 includes the following:

[0084] Extract the new and old process node information corresponding to the core objective change node. The node information includes the operation object, experimental steps and result indicators. The extracted information is then standardized to eliminate expression differences and redundant information.

[0085] The three core dimensions for equivalence determination are defined as the matching degree of the operation object, the similarity of the experimental procedure, and the deviation of the result index. A corresponding weight is set for each dimension, and the sum of the weights of each dimension is 1. The weights are set according to the degree of influence of each dimension on the equivalence of the experimental procedure, and are calibrated by combining historical data statistical analysis, industry standard comparison and experimental verification.

[0086] A preset equivalent allowable threshold is used to calculate quantified values ​​for three dimensions for each core target change node. The matching degree of the operation object is determined based on the consistency of the operation objects of the new and old nodes; the similarity of the experimental steps is determined based on the overlap of the experimental steps of the new and old nodes; and the deviation of the result index is determined based on the relative deviation of the result index of the new and old nodes. The comprehensive equivalent deviation coefficient of the new and old nodes is calculated by weighted summation of the quantified values ​​of the three dimensions and their corresponding weights.

[0087] When the comprehensive equivalent deviation coefficient is less than or equal to the preset equivalent allowable threshold, the new and old nodes are determined to be equivalent nodes, and a one-to-one equivalent node mapping relationship is established.

[0088] For a core objective change node in the old version of the standard operating procedure (SOP), corresponding to multiple process nodes in the new version of the SOP, a splitting and mapping method is determined based on a pre-defined combination rule base. This combination rule base includes splitting and merging mapping rules based on experimental functions, sample types, process sequence, and node importance. The operation data of the old node is extracted, and a splitting weight is calculated for each corresponding new node. The sum of the splitting weights of all new nodes corresponding to the same old node is a fixed value. The splitting weight is determined based on the proportion of experimental functions undertaken by each new node, which is quantified based on the number of experimental steps, sample allocation ratio, or functional importance score. Based on the splitting weight, the operation data of the old node is split and mapped to multiple corresponding new nodes, establishing a one-to-many equivalent node mapping relationship.

[0089] For the case where multiple core target change nodes in the old version of the standard operating procedure correspond to a single process node in the new version of the standard operating procedure, the operation data of multiple old nodes are aggregated and mapped to the new node based on the combined rule base, thus establishing a many-to-one equivalent node mapping relationship.

[0090] In this embodiment, for the core target change nodes marked in the version difference chain, relevant information about the old and new process nodes corresponding to each core target change node is extracted from SO and SN. The relevant information includes the operation object, experimental steps and result indicators. The extracted information is standardized to eliminate expression differences and redundant information to ensure the comparability of the old and new node information. Among them, the operation object is the core object or material targeted by the experiment, the experimental steps are the specific experimental steps corresponding to the node, and the result indicators are the quantitative or qualitative standards that need to be achieved after the experiment of the node is completed.

[0091] Three core dimensions for equivalence determination are defined: matching degree of the operation object, similarity of the experimental procedure, and deviation of the result index. Weights are assigned to each dimension, with the matching degree of the operation object weight denoted as A, the similarity of the experimental procedure weight denoted as B, and the deviation of the result index weight denoted as C, satisfying A+B+C=1. The weights A, B, and C are set according to the degree of influence of each dimension on the equivalence of the experimental procedure, and are calibrated through a combination of historical data statistical analysis, industry standard comparison, and experimental verification. The final values ​​are determined by the laboratory based on the experimental type and accuracy requirements.

[0092] A preset equivalence threshold S is set, which is a dimensionless constant determined based on the stability of experimental results, industry standards, and statistical analysis of historical equivalence cases. This threshold is used to determine whether the new and old nodes are equivalent. For each core objective change node, the quantitative values ​​of the three dimensions are calculated, and then the comprehensive equivalence deviation coefficient E of the new and old nodes is obtained by weighted summation. The calculation formula is: E=A×(1-M)+B×(1-N)+C×(|Rn-Ro| / Ro), where M is the matching degree of the operation object. If the operation objects of the new and old nodes are completely consistent, M=1; if the operation objects of the new and old nodes are partially consistent, M is the proportion of the number of matched object types to the total number of object types, and the value range is 0<M<1; if they are completely inconsistent, M=0; N is the similarity of the experimental steps, which is calculated by comparing the overlap of the experimental steps of the new and old nodes, and N=number of overlapping steps / total number of steps, with a value range of 0≤N≤1; Rn is the result index value of the corresponding core objective change node in SN; Ro is the result index value of the corresponding core objective change node in SO.

[0093] When the comprehensive equivalence deviation coefficient E≤S, the old and new nodes are determined to be equivalent nodes, and a one-to-one equivalent node mapping relationship is established. When a core target change node in the old version SO corresponds to multiple process nodes in the new version SN, according to the preset combination rule library, which includes splitting and merging mapping rules based on experimental function, sample type, process sequence, and node importance, the corresponding splitting method is automatically selected according to the functional characteristics of the old node. The operation data of the old node is extracted, and the splitting weight Dg corresponding to each new node is calculated, where g is the new node number and ∑Dg=1. The splitting weight Dg is set according to the proportion of experimental functions undertaken by each new node, and Dg=Fg / ∑Fg', where Fg is the proportion of experimental functions undertaken by the g-th new node, ∑Fg' is the sum of the proportions of experimental functions corresponding to all new nodes under the same old node, and g' is the number of the new node in the set. The functional proportion Fg is quantified according to the number of experimental steps, sample allocation ratio, or functional importance score.

[0094] Based on the splitting weight Dg, the operation data of the old nodes are split and mapped to multiple corresponding new nodes, establishing a one-to-many equivalent node mapping relationship. Similarly, when multiple core target change nodes in the old version SO correspond to a process node in the new version SN, the operation data of multiple old nodes are aggregated and mapped to the new node according to the combination rule base, establishing a many-to-one equivalent node mapping relationship, and completing the construction of the equivalent node mapping relationship for all core target change nodes.

[0095] S4 includes the following:

[0096] Collect the set of historical experimental data stored in the laboratory, and simultaneously retrieve the old version of the standard operating procedure and the corresponding old version process node identifier associated with each historical experimental data, and establish a one-to-one correspondence between historical experimental data and old version process nodes.

[0097] Based on the constructed equivalent node mapping table, the old version process node identifier corresponding to each historical experimental data is traversed, and the equivalent process node identifier corresponding to it under the new version standard operating procedure is retrieved. For one-to-one mapping relationships, a unique equivalent process node identifier is directly determined. For one-to-many mapping relationships, a set of multiple equivalent process node identifiers is determined. For many-to-one mapping relationships, multiple old version process node identifiers are merged and mapped to the same equivalent process node identifier, thus completing the matching of old and new version process node identifiers.

[0098] Historical experimental operation data is processed separately for different mapping relationships. Specifically: for one-to-one mapping, the historical experimental operation data corresponding to the old process node is completely migrated to the new equivalent process node; for one-to-many mapping, the historical experimental operation data corresponding to the old process node is proportionally split and distributed to multiple corresponding new equivalent process nodes according to the preset split weight; for many-to-one mapping, the historical experimental operation data corresponding to multiple old process nodes is summarized, and duplicate parameter items are merged and conflicting parameter items are selected according to the preset priority during integration. Then, the summarized data is mapped to the same new equivalent process node.

[0099] Based on the process node sequence of the new version standard operating procedure, the processed historical experimental operation data is classified according to the equivalent process node identifier. The execution order of each equivalent process node is arranged according to the experimental sequence rules. Redundant data that conflicts with the process sequence of the new version procedure is removed, and necessary data items required by the new version procedure are added. Finally, the historical experimental process corresponding to the new version standard operating procedure is reconstructed, and the cross-version process adaptation of historical experimental data is completed.

[0100] In this embodiment, the historical experimental data set D={D1,D2,...,Dx} stored in the laboratory is collected, where x is the total number of historical experimental data records; each historical experimental data record Dh is retrieved synchronously, where h=1,2,...,x; the associated old version standard operating procedure SO and the corresponding old version process node identifier set L={L1,L2,...,Ly} are also retrieved, where y is the total number of old version process nodes associated with the historical experimental data, and a one-to-one correspondence between the historical experimental data and the old version process nodes is established.

[0101] Based on the equivalent node mapping table constructed in S2, the old process node identifiers Lp corresponding to the historical experimental data Dh are traversed, where p=1,2,...,y. The equivalent process node identifier set Qp under the new version standard operating procedure SN corresponding to Lp is retrieved in the equivalent node mapping table. For one-to-one mapping relationships, the unique equivalent process node identifier corresponding to Lp is directly determined. For one-to-many mapping relationships, multiple equivalent process node identifier sets corresponding to Lp are determined. For many-to-one mapping relationships, multiple old process node identifiers are merged and mapped to the same equivalent process node identifier, thus completing the identifier matching from all old process nodes to new equivalent process nodes.

[0102] For equivalent nodes with one-to-one mapping, the historical experimental operation data corresponding to the old process node Lp is directly migrated to the new equivalent process node. For equivalent nodes with one-to-many mapping, the historical experimental operation data corresponding to the old process node Lp is proportionally split and allocated to multiple corresponding new equivalent process nodes according to the split weight Dg determined in S2. After splitting, the sum of the data of each new node is consistent with the original old node data. For equivalent nodes with many-to-one mapping, the historical experimental operation data corresponding to multiple old process nodes are summarized, integrated, and mapped to the same new equivalent process node. When summarizing, duplicate parameter items are merged, and conflicting parameter items are selected according to preset priority.

[0103] Based on the process node sequence of SN, the historical experimental operation data after splitting and summarizing is classified according to the equivalent process node identifier, and the execution order of each equivalent process node is arranged according to the experimental sequence rules. Redundant data that conflicts with the process sequence of the new version of the procedure is removed, and necessary data items required by the new version of the procedure are added. Finally, the historical experimental process corresponding to the new version of the standard operating procedure SN is reconstructed, and the cross-version process adaptation of historical experimental data is completed.

[0104] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, 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.

[0105] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A standardized intelligent processing method based on laboratory procedures, characterized in that: The method includes the following steps: S1. Obtain the standard operating procedures for the new and old versions, compare the process nodes and operating parameters, define the modified clauses as target change clauses, and extract all target change clauses; S2. Preset the threshold for the impact of process execution, classify target change clauses whose operational parameter deviations exceed the threshold as core target change clauses, and the rest as non-core target change clauses; construct a version difference chain and mark the core target change nodes; S3. For core target change nodes in the version difference chain, extract the operation objects, experimental steps, and result indicators of the old and new process nodes for matching; when the operation objects of the old and new nodes are consistent and the deviation of their result indicators is within the preset equivalence allowable range, they are determined to be equivalent nodes; define three core dimensions for equivalence determination, namely, operation object matching degree, experimental step similarity, and result indicator deviation degree; the operation object matching degree is determined based on the consistency of the operation objects of the old and new nodes; the experimental step similarity is determined based on the overlap of the experimental steps of the old and new nodes; the result indicator deviation degree is determined based on the relative deviation of the result indicators of the old and new nodes; If one process node in the old version corresponds to multiple process nodes in the new version, then according to the preset combination rule library, the operation data of the old node is split and mapped to multiple new nodes to establish an equivalent node mapping relationship of one-to-many or many-to-one. S4. Retrieve historical experimental data and its associated old version standard operating procedures. Based on the equivalent node mapping relationship, convert the old version process nodes corresponding to the historical experimental data into equivalent process nodes under the new version standard operating procedures, and reconstruct the historical experimental process corresponding to the new version procedures.

2. The intelligent processing method based on standardized laboratory procedures according to claim 1, characterized in that: S1 includes the following: Collect the old version and the new version of the standard operating procedure, extract all experimental process nodes of the two versions of the procedure and assign a unique node identifier to each process node, and extract the corresponding operating parameters of each node, including process parameters and equipment operating parameters. Based on node identifiers, the nodes and operating parameters of the two versions of the procedure are compared. Clauses with the same node identifiers but different operating parameters are defined as target change clauses. All target change clauses are identified and screened out, and the node identifiers and differences in operating parameters corresponding to each target change clause are recorded.

3. The intelligent processing method based on standardized laboratory procedures according to claim 2, characterized in that: S2 includes the following: The preset process execution impact threshold is set based on laboratory quality control standards, experiment type, and equipment characteristics. For each target change clause, the operational parameter deviation impact coefficient is calculated. This coefficient is the sum of the products of the deviation ratio of each operational parameter and its corresponding weight. The weight is set according to the degree of influence of the parameter on the experimental results, and the sum of all weights is 1. Based on the comparison between the operational parameter deviation impact coefficient and the preset threshold, the target change clauses are divided into core target change clauses and non-core target change clauses; combined with the classification results, a version difference chain is constructed, and the node identifiers and corresponding operational parameter deviation impact coefficients of all core target change nodes are marked.

4. The intelligent processing method based on laboratory process standardization according to claim 3, characterized in that: S3 includes the following: Extract the new and old process node information corresponding to the core objective change node. The node information includes the operation object, experimental steps and result indicators. The extracted information is then standardized to eliminate expression differences and redundant information. The three core dimensions for equivalence determination are defined as the matching degree of the operation object, the similarity of the experimental procedure, and the deviation of the result index. A corresponding weight is set for each dimension, and the sum of the weights of each dimension is 1. The weights are set according to the degree of influence of each dimension on the equivalence of the experimental procedure, and are calibrated by combining historical data statistical analysis, industry standard comparison and experimental verification. A preset equivalent allowable threshold is set, and quantified values ​​for three dimensions are calculated for each core objective change node. The comprehensive equivalent deviation coefficient between the old and new nodes is calculated by weighted summation of the quantified values ​​of the three dimensions and their corresponding weights. When the comprehensive equivalent deviation coefficient is less than or equal to the preset equivalent allowable threshold, the new and old nodes are determined to be equivalent nodes, and a one-to-one equivalent node mapping relationship is established. For a core objective change node in the old version of the standard operating procedure (SOP), corresponding to multiple process nodes in the new version of the SOP, a splitting and mapping method is determined based on a pre-defined combination rule base. This combination rule base includes splitting and merging mapping rules based on experimental functions, sample types, process sequence, and node importance. The operation data of the old node is extracted, and a splitting weight is calculated for each corresponding new node. The sum of the splitting weights of all new nodes corresponding to the same old node is a fixed value. The splitting weight is determined based on the proportion of experimental functions undertaken by each new node, which is quantified based on the number of experimental steps, sample allocation ratio, or functional importance score. Based on the splitting weight, the operation data of the old node is split and mapped to multiple corresponding new nodes, establishing a one-to-many equivalent node mapping relationship. For the case where multiple core target change nodes in the old version of the standard operating procedure correspond to a single process node in the new version of the standard operating procedure, the operation data of multiple old nodes are aggregated and mapped to the new node based on the combined rule base, thus establishing a many-to-one equivalent node mapping relationship.

5. The intelligent processing method based on laboratory process standardization according to claim 4, characterized in that: S4 includes the following: Collect the set of historical experimental data stored in the laboratory, and simultaneously retrieve the old version of the standard operating procedure and the corresponding old version process node identifier associated with each historical experimental data, and establish a one-to-one correspondence between historical experimental data and old version process nodes. Based on the constructed equivalent node mapping table, the old version process node identifier corresponding to each historical experimental data is traversed, and the equivalent process node identifier corresponding to it under the new version standard operating procedure is retrieved. For one-to-one mapping relationships, a unique equivalent process node identifier is directly determined. For one-to-many mapping relationships, a set of multiple equivalent process node identifiers is determined. For many-to-one mapping relationships, multiple old version process node identifiers are merged and mapped to the same equivalent process node identifier, thus completing the matching of old and new version process node identifiers. Historical experimental operation data is processed separately for different mapping relationships. Specifically: for one-to-one mapping, the historical experimental operation data corresponding to the old process node is completely migrated to the new equivalent process node; for one-to-many mapping, the historical experimental operation data corresponding to the old process node is proportionally split and distributed to multiple corresponding new equivalent process nodes according to the preset split weight; for many-to-one mapping, the historical experimental operation data corresponding to multiple old process nodes is summarized, and duplicate parameter items are merged and conflicting parameter items are selected according to the preset priority during integration. Then, the summarized data is mapped to the same new equivalent process node. Based on the process node sequence of the new version standard operating procedure, the processed historical experimental operation data is classified according to the equivalent process node identifier. The execution order of each equivalent process node is arranged according to the experimental sequence rules. Redundant data that conflicts with the process sequence of the new version procedure is removed, and necessary data items required by the new version procedure are added. Finally, the historical experimental process corresponding to the new version standard operating procedure is reconstructed, and the cross-version process adaptation of historical experimental data is completed.

6. A laboratory process standardization-based intelligent processing system for implementing the laboratory process standardization-based intelligent processing method according to any one of claims 1-5, characterized in that: The system includes: a change clause extraction module, a core change identification module, an equivalent node mapping module, and a historical data adaptation module; The change clause extraction module obtains the standard operating procedures of the old and new versions, extracts the experimental process nodes and operating parameters of the two versions of the procedures, compares the differences in nodes and parameters, defines and filters the target change clauses, and records the node identifiers and parameter differences of the target change clauses. The core change identification module presets the process execution impact threshold, calculates the operation parameter deviation impact coefficient of each target change clause, divides core and non-core target change clauses based on the comparison between the coefficient and the threshold, constructs a version difference chain, and marks the core target change nodes. The equivalent node mapping module extracts and standardizes the information of the old and new process nodes of the core target change node, sets the equivalence judgment dimensions and weights, calculates the comprehensive equivalence deviation coefficient, judges equivalent nodes, and establishes one-to-one, one-to-many, and many-to-one equivalent node mapping relationships. It defines three core dimensions for equivalence judgment: operation object matching degree, experimental step similarity, and result indicator deviation degree. The operation object matching degree is determined based on the consistency of the operation objects of the old and new nodes; the experimental step similarity degree is determined based on the overlap of the experimental steps of the old and new nodes; and the result indicator deviation degree is determined based on the relative deviation of the result indicators of the old and new nodes. The historical data adaptation module collects historical experimental data from the laboratory, retrieves the old version of the procedures and node identifiers associated with the data, matches the old and new node identifiers according to the equivalent node mapping relationship, processes and migrates the historical data, and reconstructs the historical experimental process to adapt to the new version of the procedures.

7. The intelligent processing system based on standardized laboratory procedures according to claim 6, characterized in that: The change clause extraction module includes a procedure collection unit and a clause filtering unit; The procedure acquisition unit collects old and new versions of standard operating procedures, extracts all experimental process nodes of the two versions of procedures and assigns unique node identifiers, and extracts the process parameters and equipment operating parameters corresponding to each node. The clause filtering unit uses node identifiers as the matching basis, compares the nodes and operation parameters of the two versions of the procedure, identifies and filters target change clauses with the same node identifiers but different parameters, and records the differences in node identifiers and operation parameters of each target change clause.

8. The intelligent processing system based on standardized laboratory procedures according to claim 6, characterized in that: The core change identification module includes a threshold setting unit and a change classification unit; The threshold setting unit presets process execution impact thresholds based on laboratory quality control standards, experiment types, and equipment characteristics, sets the weights of each operation parameter, ensures that the sum of all weights is 1, and calculates the operation parameter deviation impact coefficient for each target change clause. The change classification unit divides core and non-core target change clauses based on the comparison between the operational parameter deviation impact coefficient and the preset threshold, constructs a version difference chain containing change clause details and classification identifiers, and marks core target change nodes and their corresponding impact coefficients.

9. The intelligent processing system based on standardized laboratory procedures according to claim 6, characterized in that: The equivalent node mapping module includes an information processing unit and a mapping establishment unit; The information processing unit extracts the old and new process node information of the core target change node and standardizes it, defines three core dimensions for equivalence determination and their corresponding weights, presets the equivalence allowable threshold, calculates the quantitative value of each dimension and the comprehensive equivalence deviation coefficient, and determines the equivalent node. The mapping establishment unit determines one-to-many and many-to-one mapping methods based on the combination rule base, calculates the split weight and quantifies the function proportion, splits or summarizes the old node operation data, and establishes various equivalent node mapping relationships.

10. The intelligent processing system based on standardized laboratory procedures according to claim 6, characterized in that: The historical data adaptation module includes a data association unit and a process reconstruction unit; The data association unit collects historical experimental data sets, retrieves the old version of the procedures and old version of the process node identifiers associated with each data, establishes a one-to-one correspondence between historical experimental data and old version process nodes, matches the new and old process node identifiers, and processes the corresponding historical data. The process reconstruction unit uses the process node sequence of the new version of the procedure as a benchmark to classify, sort, remove redundancies, and supplement necessary data in the processed historical data, and reconstructs a historical experimental process corresponding to the new version of the standard operating procedure to complete cross-version data adaptation; wherein, the necessary data refers to the data items that are missing in the historical experimental data and must be supplemented as specified in the new version of the standard operating procedure.

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