IND declaration material generation management system and method based on large model

Abstract

The invention discloses an IND declaration material generation management system and method based on a large model, and relates to the technical field of declaration material generation management, and the method comprises the steps: evaluating the reference value of a standard declaration material in a standard material database for an IND declaration material; analyzing the functional correlation degree between the functional block of the IND declaration material and the standard functional block of the reference standard declaration material; evaluating correlation conditions among different related function blocks in the related function block set, generating a target correlation range, and analyzing approval reference values of the related function blocks on the function blocks under different correlation scales of the function blocks in the IND declaration material and the related function blocks in the related function block set; the abnormal state of the function block is diagnosed, the abnormal function block is obtained, the abnormal function block in the IND declaration material is marked on the declaration material generation platform, the abnormal detection efficiency is improved, and the quality of the IND declaration material is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of declaration material generation management, and particularly relates to an IND declaration material generation management system and method based on a large model. BACKGROUND

[0002] IND is the Chinese meaning of "new drug clinical research application", and IND declaration material refers to the application materials submitted by a drug research and development institution to a drug regulatory agency before the drug is applied to start clinical experiments. The IND declaration material needs to integrate a large amount of research data, and therefore, the generation of the IND declaration material is a very complex and time-consuming task. The traditional declaration material method has the problems of scattered data and low efficiency, and cannot guarantee the consistency and accuracy of the information of the declaration material. The use of the large model technology can effectively integrate data from different sources, thereby quickly generating the declaration material, and the large model technology can also effectively guarantee the consistency of the data and avoid the consistency problems caused by manual generation of the material in the traditional method.

[0003] At present, although the technical scheme of using the large model to generate the IND declaration material has gradually matured, the IND declaration material needs to be approved by different approval agencies in different regions in the actual approval process, different approval agencies have different requirements for the IND declaration material, and normal IND declaration material in one approval agency may also be determined as abnormal in another approval agency. In addition, the properties of the drug corresponding to the IND declaration material also have an impact. These will cause problems in the abnormal detection of the IND declaration material, thereby affecting the final declaration progress of the IND declaration material, and even cause the IND declaration material to fail to be declared successfully, resulting in huge losses. SUMMARY

[0004] The present application aims to provide an IND declaration material generation management system and method based on a large model to solve the problems in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme: an IND declaration material generation management method based on a large model, the method comprising: Step S1: obtaining a constructed declaration material generation platform, using the declaration material generation platform to generate declaration material for a declared drug, obtaining IND declaration material, obtaining a standard material database of an approval agency for the IND declaration material, evaluating the reference value of the standard declaration material in the standard material database to the IND declaration material, and obtaining a reference standard declaration material; Step S2: Obtain the reference standard declaration materials of the IND declaration materials, analyze the functional correlation between the functional blocks of the IND declaration materials and the standard functional blocks of the reference standard declaration materials, and obtain a set of related functional blocks; Step S3: Obtain the set of related functional blocks of the functional blocks, evaluate the correlation between different related functional blocks in the set of related functional blocks, generate a target correlation range, and according to the target correlation range, analyze the approval reference value of the related functional blocks in the set of related functional blocks to the functional blocks under different correlation scales, and obtain a set of reference functional blocks of the functional blocks; Step S4: Diagnose the abnormal state of the functional blocks according to the set of reference functional blocks and the set of related functional blocks, obtain abnormal functional blocks, and mark the abnormal functional blocks in the IND declaration materials on the declaration material generation platform to assist the review personnel in the platform to review the IND declaration materials.

[0006] Further, step S1 includes: Step S11: Obtain a pre-constructed declaration material generation platform, use the declaration material generation platform to generate declaration materials for declared drugs according to preset rules, and obtain IND declaration materials corresponding to the declared drugs; Step S12: Obtain a standard material database of the approval agency of the material declaration of the IND declaration materials, wherein the standard material database includes various standard declaration materials approved by the approval agency; Step S13: Evaluate the reference value of the standard declaration materials in the standard material database to the IND declaration materials, and the specific evaluation process is: Obtain the drug attribute data of the declared drugs of the standard declaration materials and the IND declaration materials, respectively, wherein the drug attribute data includes the data of various drug attributes; According to the drug attribute data of the declared drugs of the IND declaration materials, construct a drug feature vector A of the IND declaration materials, and calculate the drug reference value R of the standard declaration materials to the IND declaration materials A ; Obtain the research type sets F and F' of the IND declaration materials and the standard declaration materials, respectively, wherein the research type set F includes several research types involved in the IND declaration materials; Obtain the total number F of the same research types existing between the research type set F and the research type set F' △ sum Calculate the research reference value R of the standard declaration materials to the IND declaration materials F = (F △ sum / F sum ) × (F △ sum / F´ sum ), wherein F sum is the total number of research types contained in the research type set F, F´ sum is the total number of research types contained in the research type set F´; obtain a preset research reference coefficient η F and a drug reference coefficient η A , calculate the value of the research reference coefficient η F multiplied by the research reference value R F plus the value of the drug reference coefficient η A multiplied by the drug reference value R A , to obtain the reference value α of the standard declaration material to the IND declaration material; When the reference value α is greater than the preset reference threshold, it is determined that the standard declaration material has reference value to the IND declaration material, and the standard declaration material is recorded as a reference standard declaration material.

[0007] Further, step S2 includes: Step S21: obtaining each reference standard declaration material of the IND declaration material from the standard material database of the approval agency; using the declaration material generation platform, dividing the IND declaration material into each functional block; using the declaration material generation platform, obtaining a plurality of standard functional blocks corresponding to each reference standard declaration material; Step S22: obtaining the structure data of the functional blocks in the IND declaration material and the plurality of standard functional blocks of the reference standard declaration material, obtaining the standard functional blocks similar to the structure of the functional blocks in the IND declaration material from the plurality of functional blocks of the reference standard declaration material and marking them; analyzing the correlation between the functional blocks in the IND declaration material and the plurality of marked standard functional blocks in the reference standard declaration material, and the specific analysis process is: obtaining the document content of the functional blocks in the IND declaration material, and preprocessing the document content of the functional blocks, and using the declaration material generation platform to obtain the semantic vectors between the marked standard functional blocks and the functional blocks after preprocessing respectively; calculating the cosine similarity between the functional blocks and the standard functional blocks to obtain the semantic correlation value E between the functional blocks and the standard functional blocks; Step S23: using the declaration material generation platform to obtain the entity sets L and L´ of the functional blocks and the standard functional blocks; calculating the entity correlation value H=(L∩L´) / (L∪L´) between the functional blocks and the standard functional blocks; Step S24: using the declaration material generation platform to obtain the data set of the functional blocks and the standard functional blocks; acquiring the total number m of elements in the data set of the function block that are identical to elements in the data set of the standard function block sum acquiring the total number M of all elements in the data set of the function block that are identical to elements in the data set of the standard function block sum acquiring a certain index that is contained in the data set of the function block and the data set of the standard function block, respectively acquiring the value V and V' of the certain index in the data set of the function block and the data set of the standard function block, and calculating the numerical difference U = |V-V'| / max{V,V'} of the function block and the standard function block in the certain index acquiring the data difference U of the function block and the standard function block in the same number of indexes △ calculating the data correlation value G = (m sum / M sum ) x (1-U) between the function block and the standard function block Step S25: normalizing the semantic correlation value E, the entity correlation value H and the data correlation value G respectively, and calculating the function correlation value P = ζ E x E + ζ H x H + ζ G x G between the function block and the standard function block, wherein ζ E , ζ H and ζ G are respectively preset semantic correlation coefficients, entity correlation coefficients and data correlation coefficients acquiring the maximum value of the function correlation value between the function block and the marked number of standard function blocks in the reference standard declaration material, and when the maximum value is greater than a preset maximum threshold value, recording the standard function block corresponding to the maximum value as a relevant function block of the function block Step S26: acquiring each reference standard declaration material of the IND declaration material, obtaining each relevant function block of the function block from each reference standard declaration material and collecting to obtain a relevant function block set.

[0008] Further, step S3 includes: Step S31: acquiring the relevant function block set of the function block in the IND declaration material, and taking the semantic correlation value, the entity correlation value and the data correlation value between the function block and the relevant function blocks in the relevant function block set as the correlation indexes between the function block and the relevant function blocks Step S32: acquiring the values of the correlation indexes between each relevant function block in the relevant function block set, acquiring the maximum value and the minimum value of a certain correlation index between each relevant function block, and constructing the numerical range W of the certain correlation index between each relevant function block Step S33: acquiring the median μ of the numerical range W, and acquiring the standard deviation σ of the certain correlation index between each relevant function block constructing the jth feature numerical range Q of the certain correlation index with the median μ as the centerj =[μ-j×σ,μ+j×σ], when the value of a certain correlation index between one related functional block and another related functional block is in Q j If it is inside, then determine Q. j There is a one-time inclusion relationship for a certain related indicator; Get the total number N of a certain related indicator among the various related functional blocks. sum Get Q j The total number of times N exists that a certain related indicator has an inclusion relationship （j,sum） Calculate Q j The inclusion ratio Z j =N （j,sum） / N sum ; When the proportion value Z is included j If Q is the smallest feature data range among several feature data ranges that are greater than a preset inclusion ratio threshold, then Q will be... j The target relevant range Q of a certain related indicator; Step S34: Obtain the target relevant range of each relevant indicator. When the values ​​of each relevant indicator between the ε-th relevant functional block in the relevant functional block set and the functional block are all within the target relevant range of each relevant indicator, it is determined that the ε-th relevant functional block has approval reference value for the functional block, and the ε-th relevant functional block is recorded as the reference functional block of the functional block. Obtain each reference functional block of the functional block and aggregate them to obtain the reference functional block set of the functional block. The reason for acquiring the target-related data range in the above steps is that the relevant function sets of the function blocks are all standard function blocks that have been approved by the approval agency, and there is a correlation between these standard function blocks and the function blocks in the IND application materials. Therefore, the more similar the correlation between different related function blocks in the relevant function sets is to the correlation between different related function blocks, the lower the probability of anomalies in the function blocks in the IND application materials. Conversely, the lower the correlation, the higher the probability. This scientific mathematical formula can effectively identify anomalies in the function blocks of the IND application materials according to the approval style of the approval agency, thereby ensuring that the style of the function blocks in the IND application materials meets the actual needs of the approval agency.

[0009] Furthermore, step S4 includes: Step S41: Obtain the total number S of reference function blocks in the reference function block set of the function block. ▽ sum Get the total number S of related function blocks. sum Calculate the function block outlier τ = 1 - (S) ▽ sum / S sum ); Step S42: When the function block abnormal value τ is greater than the preset abnormal threshold value, it is determined that the function block is an abnormal function block, and the abnormal function block in the IND declaration material is marked on the declaration material generation platform to assist the review personnel in the platform to review the IND declaration material.

[0010] According to the above method, a IND declaration material generation management system based on a large model is also proposed, which includes a reference value module, a function correlation analysis module, an approval reference value analysis module and an abnormality detection module. The reference value module is used to obtain the standard material database of the approval institution for the IND declaration material, evaluate the reference value of the standard declaration material in the standard material database to the IND declaration material, and obtain the reference standard declaration material. The function correlation analysis module is used to obtain the reference standard declaration material of the IND declaration material, analyze the function correlation degree between the function block of the IND declaration material and the standard function block of the reference standard declaration material, and obtain the related function block set. The approval reference value analysis module is used to evaluate the correlation between different related function blocks in the related function block set, generate a target correlation range, and analyze the approval reference value of the related function block to the function block under different correlation scales according to the target correlation range, and obtain the reference function block set of the function block. The abnormality detection module is used to diagnose the abnormal state of the function block according to the reference function block set and the related function block set, obtain the abnormal function block, and mark the abnormal function block in the IND declaration material on the declaration material generation platform to assist the review personnel in the platform to review the IND declaration material.

[0011] Further, the reference value module includes a reference value calculation unit and a reference value evaluation unit. The reference value calculation unit is used to obtain the standard material database of the approval institution for the IND declaration material, and calculate the reference value of the standard declaration material in the standard material database to the IND declaration material. The reference value evaluation unit is used to evaluate the reference value of the standard declaration material to the IND declaration material according to the reference value of the standard declaration material to the IND declaration material, and obtain the reference standard declaration material.

[0012] Further, the function correlation analysis module includes a data correlation value calculation unit and a function correlation analysis unit. A data correlation value calculation unit is configured to obtain a reference standard declaration material of the IND declaration material, obtain a function block of the IND declaration material and a standard function block of the reference standard declaration material respectively, and calculate a data correlation value between the function block and the standard function block. A function correlation analysis unit is configured to analyze a function correlation degree between the function block and the standard function block according to the data correlation value of the function block and the standard function block, and obtain a relevant function block set.

[0013] Further, the approval reference value analysis module comprises a target correlation range generation unit and an approval reference value analysis unit. The target correlation range generation unit is configured to obtain the relevant function block set of the function block, evaluate a correlation condition between different relevant function blocks in the relevant function block set, and generate a target correlation range. The approval reference value analysis unit is configured to analyze, according to the target correlation data, an approval reference value of a relevant function block in the relevant function block set to the function block under different correlation scales, and obtain a reference function block set of the function block.

[0014] Further, the abnormality detection module comprises an abnormality detection unit. The abnormality detection unit is configured to obtain the reference function block set and the relevant function block set, diagnose an abnormal state of the function block, obtain an abnormal function block, and mark the abnormal function block in the IND declaration material on the declaration material generation platform.

[0015] Compared with the prior art, the present application has the following beneficial effects: the present application realizes intelligent management of IND declaration material generation, and, compared with a traditional IND declaration material generation method, the present application considers that different approval agencies in different regions have different approval styles for IND declaration materials, therefore, starting from the approval agencies, standard declaration materials with reference value are obtained from a database of the approval agencies in terms of declared drugs and research directions, and the present application also considers that the declaration material has a large amount of data, function blocks of the declaration material are obtained according to a standard hierarchical structure and semantics of the declaration material, and relevant function blocks related to the function blocks of the declaration material are obtained from the reference standard declaration material, so as to obtain a relevant function set, construct a specific target correlation range according to a relationship between different relevant function blocks in the relevant function set in different correlation scales, filter the relevant function blocks in the relevant function set, obtain reference function blocks with reference value for the function blocks, and determine an abnormality of the function blocks according to a proportion between the reference function blocks of the function blocks and the relevant function blocks, so as to realize accurate detection of the abnormality of the function blocks, greatly improve the efficiency of abnormality detection, and guarantee the quality of the IND declaration material. BRIEF DESCRIPTION OF DRAWINGS

[0016] Fig. 1 This is a method logic diagram of an IND application material generation and management method based on a large model according to the present invention; Fig. 2 This is a flowchart of the modules of an IND application material generation and management system based on a large model, according to the present invention. Detailed Implementation

[0017] 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.

[0018] Example: Figs. 1-2 As shown, this invention provides a technical solution: a method for generating and managing IND application materials based on a large model, the method comprising: Step S1: Obtain the constructed application material generation platform, use the application material generation platform to generate application materials for the drug to be applied for, obtain IND application materials, obtain the standard material database of the approval agency for IND application materials, evaluate the reference value of the standard application materials in the standard material database for IND application materials, and obtain reference standard application materials; For example, the standard materials database stores standard application materials that have been approved by the approval agency; Step S1 includes: Step S11: Obtain the pre-built application material generation platform, use the application material generation platform to generate application materials for the drug according to the preset rules, and obtain the IND application materials corresponding to the drug. Step S12: Obtain the standard materials database of the approval agency for IND application materials, wherein the standard materials database contains various standard application materials approved by the approval agency; Step S13: Evaluate the reference value of the standard application materials in the standard materials database for the IND application materials. The specific evaluation process is as follows: Obtain the drug attribute data for the drugs submitted in the standard application materials and the IND application materials, respectively. The drug attribute data includes data for each drug attribute. For example, various drug properties include drug molecular fingerprint, oil-water partition coefficient, molecular weight, and hydrogen bond donors; Based on the drug attribute data of the drug submitted in the IND application materials, a drug feature vector A is constructed for the IND application materials, and the drug reference value R of the standard application materials to the IND application materials is calculated. A; For example, the drug reference value R is specifically calculated as the cosine similarity between the drug feature vectors in the standard application materials and the IND application materials. Obtain the research type sets F and F' of the IND application materials and standard application materials respectively. The research type set F includes several research types involved in the IND application materials. Get the total number of identical research types between research type set F and research type set F'. △ sum The calculation of standard application materials has significant reference value for IND application materials. F =(F △ sum / F sum )×(F △ sum / F´ sum ), where F sum Let F' be the total number of research types contained in the research type set F. sum The total number of research types contained in the research type set F'; For example, several types of research can include pharmacological research, toxicological research, etc. Obtain the preset research reference coefficient η F and drug reference coefficient η A Calculate the research reference coefficient η F Multiply by the research reference value R F The value plus the drug reference coefficient η A Multiply by the drug reference value R A The value of α is used to determine the reference value of standard application materials for IND application materials. When the reference value α is greater than the preset reference threshold, the standard application materials are determined to have reference value for the IND application materials, and the standard application materials are recorded as reference standard application materials.

[0019] Step S2: Obtain the reference standard application materials for the IND application materials, analyze the functional correlation between the functional blocks of the IND application materials and the standard functional blocks of the reference standard application materials, and obtain the relevant functional block set; Step S2 includes: Step S21: Obtain the reference standard application materials for the IND application materials from the standard materials database of the approval agency; Use the application material generation platform to divide the IND application materials into various functional blocks; For example, the IND declaration material can be divided into several function blocks according to the standard hierarchical structure of CTD (Common Technical Document of Drug Registration Application for Human Use), and the IND declaration material can be divided according to the different semantics on the basis of the standard hierarchical structure of CTD. For example, one function block can be Module 2: CTD Overview -> 2.6: Toxicology Summary -> 2.6.6: Overview of Genetic Toxicity Studies -> Background Introduction. Using the declaration material generation platform, a plurality of standard function blocks corresponding to the reference standard declaration material are obtained. Step S22: Obtain the structure data of the function block in the IND declaration material and the plurality of standard function blocks of the reference standard declaration material, obtain the standard function block similar to the structure of the function block in the IND declaration material from the plurality of function blocks of the reference standard declaration material, and mark the standard function block. For example, the structure data of the function block in the IND declaration material is Module 2: CTD Overview -> 2.6: Toxicology Summary -> 2.6.6: Overview of Genetic Toxicity Studies -> Background Introduction. The text content of the last path in the result structure data of the function block in the IND declaration material is the background introduction of the overview of genetic toxicity studies, and the feature vector of the text corresponding to the background introduction of the overview of genetic toxicity studies is obtained using a preset sentence embedding model, thereby obtaining the structure feature vector of the function block in the IND declaration material. When the cosine similarity between the structure feature vector of a standard function block in the reference standard declaration material and the structure feature vector of the function block in the IND declaration material is less than a preset threshold, it is determined that the function block structure between the standard function block and the standard function block is similar. The correlation between the function block in the IND declaration material and the plurality of marked standard function blocks in the reference standard declaration material is analyzed, and the specific analysis process is as follows: The document content of the function block in the IND declaration material is obtained, and the document content of the function block is preprocessed, and the semantic vector between the preprocessed marked standard function block and the function block is obtained using the declaration material generation platform. For example, the preprocessed content includes text extraction and text cleaning. For example, the semantic vector of the function block obtained by the declaration material generation platform is as follows: The pre-trained sentence embedding model (such as Sentence-BERT) is used to process all the text in the function block, thereby generating a high-dimensional semantic vector. The cosine similarity between the function block and the standard function block is calculated, thereby obtaining the semantic correlation value E between the function block and the standard function block. Step S23: obtaining the entity set L and L' of the function block and the standard function block using the declaration material generation platform; For example, the specific process of obtaining the entity set L of the function block using the declaration material generation platform is as follows: The declaration material generation platform uses the NER model specific to the field of the declaration material and based on the preset dictionary to identify the key terms in the function block, thereby collecting and obtaining the entity set L of the function block; Calculating the entity correlation value H=(L∩L´) / (L∪L´) between the function block and the standard function block; Step S24: obtaining the data set of the function block and the standard function block using the declaration material generation platform; The specific process of obtaining the data set of the function block using the declaration material generation platform is as follows: The declaration material generation platform uses the preset named entity recognition (NER) model to automatically identify and extract all numerical data and their contexts in the format of (value, unit, index) from the text in the function block; For example, if the text content of the function block is "NOAEL value is 500 mg / kg", then (500, "mg / kg", "NOAEL") is extracted, and all the extracted data are unitized and index normalized, and collected to obtain the data set of the function block; Obtaining the total number m of elements in the data set of the function block and the standard function block that have the same index sum Obtaining the total number M of all elements in the data set of the function block and the standard function block sum Obtaining the value V and V' of a certain index in the data set of the function block and the standard function block, respectively, and calculating the numerical difference U=|V-V´| / max{V,V´} of the function block and the standard function block on the certain index; Obtaining the data difference U of the function block and the standard function block on the same several indexes △ Calculating the data correlation value G=(m sum / M sum )×(1-U) between the function block and the standard function block; Step S25: normalizing the semantic correlation value E, the entity correlation value H, and the data correlation value G, respectively, and calculating the function correlation value P=ζ E ×E+ζ H ×H+ζ G ×G between the function block and the standard function block, where ζ E , ζ H , and ζ G are preset semantic correlation coefficients, entity correlation coefficients, and data correlation coefficients, respectively; Obtain the maximum value of the function-related values ​​between the function block and several standard function blocks marked in the reference standard application materials. When the maximum value is greater than the preset maximum threshold, the standard function block corresponding to the maximum value is recorded as the related function block of the function block. Step S26: Obtain the reference standard application materials for each IND application, extract the relevant functional blocks from each reference standard application material and aggregate them to obtain the relevant functional block set.

[0020] Step S3: Obtain the relevant functional block set of the functional block, evaluate the correlation between different relevant functional blocks in the relevant functional block set, generate the target correlation range, and based on the target correlation range, analyze the reference value of the relevant functional blocks for the approval of the functional block in the IND application materials and the relevant functional blocks in the relevant functional set under different correlation scales, and obtain the reference functional block set of the functional block; Step S3 includes: Step S31: Obtain the relevant functional block set of the functional block in the IND application materials, and use the semantic correlation value, entity correlation value and data correlation value between the functional block and the relevant functional block in the relevant functional block set as various correlation indicators between the functional block and the relevant functional block; Step S32: Obtain the values ​​of various related indicators among the various related functional blocks in the relevant functional block set, obtain the maximum and minimum values ​​of a certain related indicator among the various related functional blocks, and construct the numerical range W of a certain related indicator among the various related functional blocks; Step S33: Obtain the median μ of the numerical range W, and obtain the standard deviation σ of a certain related index among the relevant functional blocks; Centered on the median μ, construct the range Q of the j-th characteristic values ​​of a certain related indicator. j =[μ-j×σ,μ+j×σ], when the value of a certain correlation index between one related functional block and another related functional block is in Q j If it is inside, then determine Q. j There is a one-time inclusion relationship for a certain related indicator; Get the total number N of a certain related indicator among the various related functional blocks. sum Get Q j The total number of times N exists that a certain related indicator has an inclusion relationship （j,sum） Calculate Q j The inclusion ratio Z j =N （j,sum） / N sum ; When the proportion value Z is included j If Q is the smallest feature data range among several feature data ranges that are greater than a preset inclusion ratio threshold, then Q will be... jA target correlation range Q of a certain correlation index; Step S34: Obtain the target correlation range of each correlation index, when the values of each correlation index between the e-th correlation function block in the correlation function block set and the function block are all within the target correlation range corresponding to each correlation index, it is determined that the e-th correlation function block has the approval reference value for the function block, and the e-th correlation function block is recorded as the reference function block of the function block. Obtain each reference function block of the function block and collect them to obtain the reference function block set of the function block.

[0021] Step S4: Diagnose the abnormal state of the function block according to the reference function block set and the correlation function block set, obtain the abnormal function block, and mark the abnormal function block in the IND declaration material on the declaration material generation platform to assist the examiner in the platform to examine the IND declaration material; Step S4 includes: Step S41: Obtain the total number S of reference function blocks of the reference function block set of the function block ▽ sum Obtain the total number S of correlation function blocks of the function block sum Calculate the function block abnormal value τ of the function block τ = 1 - (S ▽ sum / S sum ); Step S42: When the function block abnormal value τ is greater than the preset abnormal threshold value, it is determined that the function block is an abnormal function block, and the abnormal function block in the IND declaration material is marked on the declaration material generation platform to assist the examiner in the platform to examine the IND declaration material.

[0022] According to the above method, an IND declaration material generation management system based on a large model can also be proposed, which includes a reference value module, a function correlation analysis module, an approval reference value analysis module, and an abnormality detection module. The reference value module is used to obtain the standard material database of the approval institution for the declaration of the IND declaration material, evaluate the reference value of the standard declaration material in the standard material database for the IND declaration material, and obtain the reference standard declaration material. The function correlation analysis module is used to obtain the reference standard declaration material of the IND declaration material, analyze the function correlation degree between the function block of the IND declaration material and the standard function block of the reference standard declaration material, and obtain the correlation function block set. The approval reference value analysis module is configured to evaluate the correlation between different related function blocks in the related function block set, generate a target correlation range, and analyze the approval reference value of the related function block in the related function block set to the function block in the IND declaration material under different correlation scales according to the target correlation range, so as to obtain the reference function block set of the function block. The abnormality detection module is configured to diagnose the abnormal state of the function block according to the reference function block set and the related function block set, obtain an abnormal function block, and mark the abnormal function block in the IND declaration material on the declaration material generation platform to assist the reviewer in reviewing the IND declaration material.

[0023] The reference value module includes a reference value calculation unit and a reference value evaluation unit. The reference value calculation unit is configured to obtain a standard material database of a declaration material review institution of the IND declaration material, and calculate the reference value of the standard declaration material in the standard material database to the IND declaration material. The reference value evaluation unit is configured to evaluate the reference value of the standard declaration material to the IND declaration material according to the reference value of the standard declaration material to the IND declaration material, and obtain a reference standard declaration material.

[0024] The function correlation analysis module includes a data correlation value calculation unit and a function correlation analysis unit. The data correlation value calculation unit is configured to obtain the reference standard declaration material of the IND declaration material, obtain the function block of the IND declaration material and the standard function block of the reference standard declaration material respectively, and calculate the data correlation value between the function block and the standard function block. The function correlation analysis unit is configured to analyze the function correlation degree between the function block and the standard function block according to the data correlation value of the function block and the standard function block, and obtain the related function block set.

[0025] The approval reference value analysis module includes a target correlation range generation unit and an approval reference value analysis unit. The target correlation range generation unit is configured to obtain the related function block set of the function block, evaluate the correlation between different related function blocks in the related function block set, and generate a target correlation range. The approval reference value analysis unit is configured to analyze the approval reference value of the related function block in the related function block set to the function block in the IND declaration material under different correlation scales according to the target correlation data, and obtain the reference function block set of the function block.

[0026] The abnormality detection module includes an abnormality detection unit. Anomaly detection unit is used to acquire the function block set and the related function block set, diagnose the anomaly state of the function block, obtain the abnormal function block, and mark the abnormal function block in the IND declaration material on the declaration material generation platform.

[0027] It will be apparent to those skilled in the art that the application is not limited to the details of the above-exemplified embodiments and that the present application can be implemented in other particular forms without departing from the spirit or essential characteristics thereof. The presently disclosed embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. No feature of the application is to be construed as limiting the scope of the claims to its exact counterpart.

Claims

1. A method for IND declaration material generation management based on a large model, characterized in that, The method comprises: Step S1: obtaining a constructed declaration material generation platform, using the declaration material generation platform to generate declaration materials for declared drugs, obtaining IND declaration materials, obtaining a standard material database of an approval agency for the IND declaration materials, evaluating the reference value of standard declaration materials in the standard material database to the IND declaration materials, and obtaining reference standard declaration materials; Step S2: obtaining the reference standard declaration materials of the IND declaration materials, analyzing the functional correlation between the functional blocks of the IND declaration materials and the standard functional blocks of the reference standard declaration materials, and obtaining a relevant functional block set; Step S3: obtaining the relevant functional block set of the functional blocks, evaluating the correlation between different relevant functional blocks in the relevant functional block set, generating a target correlation range, and analyzing the approval reference value of the relevant functional blocks in the relevant functional block set to the functional blocks under different correlation scales, and obtaining a reference functional block set of the functional blocks; Step S4: diagnosing the abnormal state of the functional blocks according to the reference functional block set and the relevant functional block set, obtaining abnormal functional blocks, and marking the abnormal functional blocks in the IND declaration materials on the declaration material generation platform to assist the review personnel in the platform in reviewing the IND declaration materials.

2. The IND declaration material generation management method based on a large model according to claim 1, characterized in that, The step S1 comprises: Step S11: obtaining a pre-constructed declaration material generation platform, using the declaration material generation platform to generate declaration materials for declared drugs according to a preset rule, and obtaining IND declaration materials corresponding to the declared drugs; Step S12: obtaining a standard material database of an approval agency for the IND declaration materials, wherein the standard material database comprises various standard declaration materials approved by the approval agency; Step S13: evaluating the reference value of the standard declaration materials in the standard material database to the IND declaration materials, and the specific evaluation process is: respectively obtaining the drug attribute data of the declared drugs of the standard declaration materials and the IND declaration materials, wherein the drug attribute data comprises the data of various drug attributes; According to the drug attribute data of the drug for which the IND declaration material is declared, a drug feature vector A of the IND declaration material is constructed, and a drug reference value R of the standard declaration material to the IND declaration material is calculated A ; respectively obtaining the research type sets F and F' of the IND declaration materials and the standard declaration materials, wherein the research type set F comprises several research types involved in the IND declaration materials; obtaining the total number F of identical research types existing between the research type set F and the research type set F' △ sum , calculating the research reference value R of the standard declaration material to the IND declaration material F △ sum / F sum ) × (F △ sum / F´ sum ), wherein F sum is the total number of research types contained in the research type set F, and F´ sum is the total number of research types contained in the research type set F´​ acquiring a preset research reference coefficient η F and a drug reference coefficient η A , calculating a research reference coefficient η F multiplying the value of the research reference value R F adding the value of the drug reference coefficient η A multiplying the value of the drug reference value R A , to obtain the reference value α of the standard declaration material to the IND declaration material; When the reference value a is greater than a preset reference threshold, it is determined that the standard declaration material has reference value to the IND declaration material, and the standard declaration material is recorded as a reference standard declaration material.

3. The IND declaration material generation management method based on a large model according to claim 2, characterized in that, The step S2 comprises: Step S21: obtaining each reference standard declaration material of the IND declaration materials from the standard material database of the approval agency; using the declaration material generation platform to divide the IND declaration materials into functional blocks; using the declaration material generation platform to obtain several standard functional blocks corresponding to each reference standard declaration material; Step S22: obtaining the structure data of the functional block in the IND declaration material and the standard functional blocks in the reference standard declaration material, obtaining the standard functional block similar to the structure of the functional block in the IND declaration material from the standard functional blocks in the reference standard declaration material and marking; analyzing the correlation between the functional block in the IND declaration material and the marked standard functional blocks in the reference standard declaration material, and the specific analysis process is: obtaining the document content of the functional block in the IND declaration material, preprocessing the document content of the functional block, and obtaining the semantic vector between the marked standard functional block and the functional block after preprocessing respectively using the declaration material generation platform; calculating the cosine similarity between the functional block and the standard functional block to obtain the semantic correlation value E between the functional block and the standard functional block; Step S23: obtaining the entity set L and L' of the functional block and the standard functional block using the declaration material generation platform; calculating the entity correlation value H=(L∩L´) / (L∪L´) between the functional block and the standard functional block; Step S24: obtaining the data set of the functional block and the standard functional block using the declaration material generation platform; acquiring the total number m of elements in the data set of the function block that are identical to elements in the data set of the standard function block sum acquiring the total number M of elements in the data set of the function block and the data set of the standard function block sum acquiring an index that is contained in the data set of the function block and the data set of the standard function block, respectively acquiring the value V and V' of the index in the data set of the function block and the data set of the standard function block, and calculating the numerical difference U of the function block and the standard function block in the index, U = |V-V'| / max{V,V'} acquiring data differences U of the function block and the standard function block on the same several indicators △ , calculating data correlation values G between the function block and the standard function block G = (m sum / M sum ) × (1-U); Step S25: normalizing the semantic correlation value E, the entity correlation value H and the data correlation value G respectively, and calculating the function correlation value P = ζ E × E + ζ H × H + ζ G × G, wherein ζ E , ζ H and ζ G are preset semantic correlation coefficient, entity correlation coefficient and data correlation coefficient respectively. obtaining the maximum value of the functional correlation value between the functional block and the marked standard functional blocks in the reference standard declaration material, when the maximum value is greater than the preset maximum threshold, the standard functional block corresponding to the maximum value is recorded as the related functional block of the functional block; Step S26: obtaining each reference standard declaration material of the IND declaration material, obtaining each related functional block of the functional block from each reference standard declaration material and collecting to obtain the related functional block set.

4. The IND declaration material generation management method based on a large model according to claim 3, characterized in that, The step S3 includes: Step S31: obtaining the related functional block set of the functional block in the IND declaration material, taking the semantic correlation value, the entity correlation value and the data correlation value between the functional block and the related functional block in the related functional block set as the correlation indicators between the functional block and the related functional block; Step S32: obtaining the value of each correlation indicator between each related functional block in the related functional block set, obtaining the maximum value and the minimum value of a certain correlation indicator between each related functional block, and constructing the numerical range W of a certain correlation indicator between each related functional block; Step S33: obtaining the median μ of the numerical range W, and obtaining the standard deviation σ of a certain correlation indicator between the related functional blocks; A jth characteristic value range Q of the certain correlation index is constructed with a median μ as a center j =[μ-j×σ,μ+j×σ], when a value of a certain correlation index between a certain correlation function block and another correlation function block is in Q j , it is determined that Q j There is a one-time inclusion relationship for a certain correlation index; Obtaining the total number N of a certain correlation index between each related function block sum , obtaining Q j The total number N of the containing relationship of a certain correlation index （j,sum） , calculating the containing proportion value Z of Q j j =N （j,sum） / N sum ;​ When the proportion value Z j is the smallest characteristic data range among several characteristic data ranges with a preset proportion threshold value, the Q j target correlation range Q as the certain relevant index; Step S34: obtaining the target correlation range of the correlation indicators, when the values of the correlation indicators between the εth related functional block in the related functional block set and the functional block are within the target correlation range of the correlation indicators, it is determined that the εth related functional block has the approval reference value for the functional block, and the εth related functional block is recorded as the reference functional block of the functional block, obtaining each reference functional block of the functional block and collecting to obtain the reference functional block set of the functional block.

5. The IND declaration material generation management method based on a large model according to claim 4, characterized in that, The step S4 includes: Step S41: obtain the total number S of reference function blocks of the reference function block set of the function block ▽ sum , obtain the total number S of related function blocks of the function block sum , calculate the function block outlier τ of the function block τ = 1 - (S ▽ sum / S sum ); Step S42: when the function block abnormal value τ is greater than the preset abnormal threshold value, it is determined that the function block is an abnormal function block, and the abnormal function block in the IND declaration material is marked on the declaration material generation platform to assist the review personnel in the platform to review the IND declaration material. 6.A large model-based IND declaration material generation management system for performing the large model-based IND declaration material generation management method of any one of claims 1-5. The system comprises a reference value module, a function correlation analysis module, an approval reference value analysis module and an abnormality detection module. The reference value module is configured to acquire a standard material database of an approval institution for the IND declaration material, evaluate reference values of standard declaration materials in the standard material database for the IND declaration material, and obtain reference standard declaration materials. The function correlation analysis module is configured to acquire the reference standard declaration materials of the IND declaration material, analyze a function correlation degree between function blocks of the IND declaration material and standard function blocks of the reference standard declaration materials, and obtain a relevant function block set. The approval reference value analysis module is configured to evaluate a correlation condition between different relevant function blocks in the relevant function block set, generate a target correlation range, analyze approval reference values of the relevant function blocks in the relevant function block set for the function blocks of the IND declaration material under different correlation scales according to the target correlation range, and obtain a reference function block set of the function blocks. The abnormality detection module is configured to diagnose an abnormal state of the function blocks according to the reference function block set and the relevant function block set, obtain abnormal function blocks, mark the abnormal function blocks in the IND declaration material on the declaration material generation platform, and assist the review personnel in the platform to review the IND declaration material.

7. The IND declaration material generation management system based on a large model according to claim 6, characterized by, The reference value module comprises a reference value calculation unit and a reference value evaluation unit. The reference value calculation unit is configured to acquire a standard material database of an approval institution for the IND declaration material, and calculate reference values of standard declaration materials in the standard material database for the IND declaration material. The reference value evaluation unit is configured to evaluate the reference values of the standard declaration materials for the IND declaration material according to the reference values of the standard declaration materials for the IND declaration material, and obtain reference standard declaration materials.

8. The IND declaration material generation management system based on a large model according to claim 6, characterized by, The function correlation analysis module comprises a data correlation value calculation unit and a function correlation analysis unit. The data correlation value calculation unit is configured to acquire the reference standard declaration materials of the IND declaration material, acquire the function blocks of the IND declaration material and the standard function blocks of the reference standard declaration materials respectively, and calculate data correlation values between the function blocks and the standard function blocks. The function correlation analysis unit is configured to analyze a function correlation degree between the function blocks and the standard function blocks according to the data correlation values of the function blocks and the standard function blocks, and obtain the relevant function block set. 9.The IND declaration material generation management system based on a large model according to claim 6, wherein, The approval reference value analysis module comprises a target correlation range generation unit and an approval reference value analysis unit. The target correlation range generation unit is configured to acquire the relevant function block set of the function blocks, evaluate a correlation condition between different relevant function blocks in the relevant function block set, and generate a target correlation range. The approval reference value analysis unit is configured to analyze approval reference values of the relevant function blocks in the relevant function block set for the function blocks of the IND declaration material under different correlation scales according to the target correlation range, and obtain the reference function block set of the function blocks. The approval reference value analysis unit is configured to analyze, according to target related data, approval reference values of related function blocks in a related function set to a function block in the IND declaration material under different related scales, and obtain a reference function block set of the function block.

10. The IND declaration material generation management system based on a large model according to claim 6, characterized in that, The abnormality detection module comprises an abnormality detection unit; The abnormality detection unit is configured to acquire the reference function block set and the related function block set, diagnose an abnormal state of the function block, obtain an abnormal function block, and mark the abnormal function block in the IND declaration material on a declaration material generation platform.

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