Artificial intelligence expert system and method based on cell chip cancer drug screening

Abstract

The invention provides an artificial intelligence expert system and method for cancer drug screening based on a cell chip. The artificial intelligence expert system and method comprises the following steps: acquiring first micro-fluidic chip experimental data, reference drug molecule data of reference drug components, and one or more reference drug component directories of the reference drug components; and performing drug feature vector analysis processing on the first micro-fluidic chip experimental data to obtain a first visual recommendation result of the cell reaction feature vector set. Obtaining one or more first cell reaction feature vector set directories of the cell reaction feature vector set; and obtaining an intelligent screening result of the cancer drugs according to the similarity between the first visual recommendation result and the reference drug molecule data and the matching condition of the one or more first cell reaction feature vector set directories and the one or more reference drug component directories. The problems that traditional screening is low in efficiency, insufficient in precision and poor in interpretability are solved, and efficient and intelligent technical support is provided for research and development of anti-cancer drugs.

Description

Technical Field

[0001] This application relates to the fields of biomedical engineering and artificial intelligence technology, and more specifically, to an artificial intelligence expert system and method for cancer drug screening based on cell chips. Background Technology

[0002] Cancer drug screening is a crucial step in new drug development. Traditional methods rely on in vitro cell experiments and animal models, which have the following drawbacks: low efficiency (requiring the manual design of multiple drug concentration gradient experiments, with a single screening cycle lasting several weeks); insufficient precision (relying on the experience of experimenters to judge drug efficacy, making it difficult to quantify the complex relationship between cellular responses and drug molecular characteristics); and insufficient data utilization (multimodal data such as cell images and biochemical indicators generated by microfluidic chips are not deeply integrated, and historical screening cases and domain knowledge lack systematic reuse). Therefore, a technological solution is urgently needed to overcome these problems. Summary of the Invention

[0003] In view of this, this application provides an artificial intelligence expert system and method for cancer drug screening based on cell chip.

[0004] In a first aspect, an artificial intelligence expert method for cancer drug screening based on cell-chip microarrays is provided, the method comprising at least:

[0005] The experiment data is obtained from a first microfluidic chip, reference drug molecule data of a reference drug component, and a catalog of one or more reference drug components. The first microfluidic chip experimental data includes a set of cell response feature vectors that need to be preprocessed. Drug feature vector analysis is performed on the first microfluidic chip experimental data to obtain a first visualization recommendation result of the set of cell response feature vectors that need to be preprocessed.

[0006] Obtain one or more directories of first cell response feature vector sets that require preprocessing; based on the similarity between the first visualization recommendation result and the reference drug molecule data, and the matching between the one or more directories of first cell response feature vector sets and the one or more directories of reference drug components, obtain the intelligent cancer drug screening result of the cell response feature vector sets that require preprocessing and the reference drug components.

[0007] In this application, the step of obtaining the intelligent cancer drug screening result of the cell response feature vector set requiring preprocessing and the reference drug components by using the similarity between the first visualization recommendation result and the reference drug molecule data, and the matching situation between the one or more first cell response feature vector set catalogs and the one or more reference drug component catalogs, includes:

[0008] Provided that the similarity between the first visual recommendation result and the reference drug molecule data is greater than the first similarity specified value, the entire directory is filtered through the one or more first cell response feature vector set directories and the one or more reference drug component directories to obtain the cancer drug intelligent screening result of the cell response feature vector set that needs to be preprocessed and the reference drug component.

[0009] In this application, provided that the one or more first cell response feature vector set directories include the first multi-strategy results of the cell response feature vector set requiring preprocessing, and the one or more reference drug component directories include the reference multi-strategy results of the reference drug components, the step of obtaining the cancer drug intelligent screening results of the cell response feature vector set requiring preprocessing and the reference drug components through the one or more first cell response feature vector set directories and the one or more reference drug component directories includes:

[0010] If the first multi-strategy result matches the reference multi-strategy result, the intelligent screening result for cancer drugs is determined to include a set of cell response feature vectors requiring pretreatment that is identical to the reference drug component; if the first multi-strategy result does not match the reference multi-strategy result, the intelligent screening result for cancer drugs is determined to include a set of cell response feature vectors requiring pretreatment that is different from the reference drug component.

[0011] In this application, the one or more first cell response feature vector set directories include the first multi-strategy result of the cell response feature vector set to be preprocessed and one or more first complete directories of the cell response feature vector set to be preprocessed, and the one or more reference drug component directories include the reference multi-strategy result of the reference drug component and one or more reference complete directories of the reference drug component; obtaining the cancer drug intelligent screening result of the cell response feature vector set to be preprocessed and the reference drug component through the one or more first cell response feature vector set directories and the one or more reference drug component directories includes: under the premise that the first multi-strategy result matches the reference multi-strategy result, obtaining the cancer drug intelligent screening result of the cell response feature vector set to be preprocessed and the reference drug component through the one or more first complete directories and the one or more reference complete directories.

[0012] In this application, the one or more reference drug ingredient catalogs include one or more reference complete catalogs of the reference drug ingredients; the step of obtaining one or more cell response feature vector set catalogs of the cell response feature vector set that needs to be preprocessed after the similarity between the first visualization recommendation result and the reference drug molecule data is greater than a first similarity specified value includes: performing a full catalog screening process on the first microfluidic chip experimental data to obtain one or more first complete catalogs of the cell response feature vector set that needs to be preprocessed, provided that the first multi-strategy result of the cell response feature vector set that needs to be preprocessed is not analyzed;

[0013] The step of obtaining the intelligent cancer drug screening results of the cell response feature vector set requiring preprocessing and the reference drug components through the one or more first cell response feature vector set directories and the one or more reference drug component directories includes: obtaining the intelligent cancer drug screening results of the cell response feature vector set requiring preprocessing and the reference drug components through the one or more first all directories and the one or more reference all directories.

[0014] In this application, obtaining the set of cell response feature vectors requiring preprocessing and the intelligent cancer drug screening results of the reference drug components through one or more first complete directories and one or more reference complete directories includes:

[0015] Determine whether there is a matching relationship between the one or more first complete directories and the one or more reference complete directories to obtain the first matching situation;

[0016] Under the premise that the first matching situation includes matching of one or more first all directories and one or more reference all directories, it is determined that the intelligent screening result of cancer drugs includes the set of cell response feature vectors that need to be preprocessed being the same as the reference drug components;

[0017] If the first matching condition includes a mismatch between one or more first complete directories and one or more reference complete directories, it is determined that the intelligent screening result for cancer drugs includes a set of cell response feature vectors requiring preprocessing that is different from the reference drug components.

[0018] In this application, the one or more first complete directories and the one or more reference complete directories all include quantification results; before determining whether the one or more first complete directories and the one or more reference complete directories have a matching relationship and obtaining the first matching situation, the method further includes: obtaining a second similarity specified value, wherein the second similarity specified value is greater than the first similarity specified value;

[0019] The step of determining whether there is a matching relationship between the one or more first complete directories and the one or more reference complete directories to obtain a first matching situation includes: under the premise that the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the second similarity specified value, and the one or more first complete directories and the one or more reference complete directories meet the first matching relationship requirement or the second matching relationship requirement, the first matching situation is determined to include the one or more first complete directories and the one or more reference complete directories having a matching relationship;

[0020] If the similarity between the first visual recommendation result and the reference drug molecule data is greater than the second similarity specified value, and the one or more first all directories and the one or more reference all directories do not meet the first matching relationship requirement and the second matching relationship requirement, the first matching situation is determined to include the one or more first all directories and the one or more reference all directories not having a matching relationship.

[0021] The first requirement for the existence of a matching relationship includes: there are no directories representing the same total directory in the one or more first total directories and the one or more reference total directories, and the quantization result is greater than the specified value of the quantization result;

[0022] The second requirement for a matching relationship includes: the second complete directory in one or more first complete directories is the same as the third complete directory in one or more reference complete directories, the second complete directory and the third complete directory represent the same complete directory, and the quantization result of the second complete directory and the quantization result of the third complete directory are both greater than the specified value of the quantization result.

[0023] In this application, provided that the similarity between the first visual recommendation result and the reference drug molecule data is less than or equal to the second specified similarity value, the method further includes:

[0024] If there are no directories representing the same total directory in one or more first total directories and one or more reference total directories, and the quantization result is greater than the specified value of the quantization result, then the first matching situation is determined to include the fact that there is no matching relationship between the one or more first total directories and the one or more reference total directories.

[0025] Determine whether there is a matching relationship between the fourth all directory in one or more first all directories and the fifth all directory in one or more reference all directories to obtain a second matching situation, wherein the quantization result of the fourth all directory and the quantization result of the fifth all directory are both greater than the specified value of the quantization result, and the fourth all directory and the fifth all directory represent the same all directory.

[0026] If the second matching scenario includes the matching of the fourth and fifth all directories, it is determined that the first matching scenario includes the matching relationship between the one or more first all directories and the one or more reference all directories.

[0027] If the second matching condition includes the mismatch between the fourth and fifth all directories, it is determined that the first matching condition includes the lack of a matching relationship between the one or more first all directories and the one or more reference all directories.

[0028] In this application, determining whether there is a matching relationship between the fourth complete directory in one or more first complete directories and the fifth complete directory in one or more reference complete directories to obtain a second matching situation includes:

[0029] If the fourth and fifth all directories are the same, the second matching condition is determined to include a matching relationship between the fourth and fifth all directories; if the fourth and fifth all directories are different, the second matching condition is determined to include a non-matching relationship between the fourth and fifth all directories.

[0030] In this application, determining whether there is a matching relationship between the fourth complete directory in one or more first complete directories and the fifth complete directory in one or more reference complete directories to obtain a second matching situation includes:

[0031] Given that the fourth and fifth all directories respectively represent the first drug recommendation list and the second drug recommendation list, it is found that the drug recommendation lists of the first drug recommendation list and the second drug recommendation list have a matching relationship;

[0032] If, based on the existence of a matching relationship in the drug recommendation lists, it is determined that the first drug recommendation list and the second drug recommendation list do not match, then the second matching situation includes the fourth all-directory and the fifth all-directory not having a matching relationship; if, based on the existence of a matching relationship in the drug recommendation lists, it is determined that the first drug recommendation list and the second drug recommendation list match, then the second matching situation includes the fourth all-directory and the fifth all-directory having a matching relationship.

[0033] In this application, obtaining the intelligent cancer drug screening result of the cell response feature vector set requiring preprocessing and the reference drug components by means of the similarity between the first visualization recommendation result and the reference drug molecule data, and the matching situation between the one or more first cell response feature vector set directories and the one or more reference drug component directories, includes: under the premise that the one or more first cell response feature vector set directories and the one or more reference drug component directories match, obtaining the intelligent cancer drug screening result of the cell response feature vector set requiring preprocessing and the reference drug components by means of the similarity between the first visualization recommendation result and the reference drug molecule data.

[0034] Secondly, an artificial intelligence expert system for cancer drug screening based on cell chips is provided, comprising a processor and a memory that communicate with each other, wherein the processor is used to retrieve a computer program from the memory and implement the above-mentioned method by running the computer program.

[0035] This application provides an artificial intelligence expert system and method for cancer drug screening based on cell-chip microarrays. The system acquires experimental data from a first microfluidic chip, reference drug molecule data for reference drug components, and one or more reference drug component directories. Drug feature vector analysis is performed on the first microfluidic chip experimental data to obtain a first visual recommendation result for a set of cell response feature vectors requiring preprocessing. One or more directories of the first cell response feature vector set requiring preprocessing are obtained. Based on the similarity between the first visual recommendation result and the reference drug molecule data, and the matching results of one or more first cell response feature vector directories and one or more reference drug component directories, intelligent screening results for cancer drugs using the cell response feature vector set requiring preprocessing and the reference drug components are obtained. This invention solves the problems of low efficiency, insufficient accuracy, and poor interpretability in traditional screening methods, providing efficient and intelligent technical support for anti-cancer drug development. Attached Figure Description

[0036] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart illustrating an artificial intelligence expert method for cancer drug screening based on cell chip technology, provided as an embodiment of this application. Detailed Implementation

[0038] To better understand the above technical solutions, the technical solutions of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0039] Please see Figure 1 This paper presents an artificial intelligence expert method for cancer drug screening based on cell chip technology, which may include the technical solutions described in steps 101-104.

[0040] 101. Obtain experimental data of the first microfluidic chip, reference drug molecule data of the reference drug component, and one or more reference drug component catalogs of the reference drug component. The experimental data of the first microfluidic chip includes a set of cell response feature vectors that need to be preprocessed.

[0041] In this embodiment, the set of cell response feature vectors to be preprocessed and the reference drug component can be a random set of cell response feature vectors.

[0042] In this embodiment, the reference drug molecule data for the reference drug component includes an attribute catalog of the reference drug component. Specifically, by comparing the visualized recommendation results of a randomly selected set of cell response feature vectors with the reference drug molecule data, it can be determined whether the set of cell response feature vectors is identical to the reference drug component. Furthermore, the reference drug molecule data includes a key description accompanying the attribute catalog of the reference drug component.

[0043] In an alternative embodiment, the reference drug molecule data is accompanied by significant key information about the reference drug component.

[0044] In one possible implementation, the reference drug molecule data is accompanied by all key information about the reference drug component, wherein all key information includes full multi-strategy outcome description information of the reference drug component.

[0045] In another possible implementation, the reference drug molecule data includes both salient key information of the reference drug component and all key information of the reference drug component.

[0046] In this embodiment, the cell response feature vector set directory includes at least one of the following: cell response feature vector set types, drug recommendation list, cell response feature vector set directory, and multi-strategy results.

[0047] In this embodiment, one or more reference drug ingredient directories are directories of cellular response feature vector sets for reference drug ingredients. One or more reference drug ingredient directories can be a single directory, or they can be a single directory of reference drug ingredients. For example, one or more reference drug ingredient directories may include a drug recommendation list of reference drug ingredients. Alternatively, one or more reference drug ingredient directories may include both a drug recommendation list of reference drug ingredients and multi-strategy results for the reference drug ingredients.

[0048] In one implementation of obtaining one or more reference drug ingredient directories, the directories are recorded in a data processing system. The data processing system can filter the directories to obtain the one or more reference drug ingredient directories.

[0049] In another implementation of obtaining one or more reference drug ingredient catalogs, the data processing system collects one or more reference drug ingredient catalogs.

[0050] In another implementation of obtaining one or more reference drug ingredient catalogs, the data processing system loads one or more reference drug ingredient catalogs.

[0051] It is understood that, in this embodiment, the steps of acquiring the experimental data of the first microfluidic chip, acquiring the reference drug molecule data of the reference drug component, and acquiring one or more reference drug component catalogs can be performed separately or simultaneously. For example, the data processing system can first acquire the experimental data of the first microfluidic chip, then acquire the reference drug molecule data of the reference drug component, and finally acquire one or more reference drug component catalogs. Alternatively, the data processing system can first acquire the reference drug molecule data of the reference drug component, then acquire the experimental data of the first microfluidic chip, and finally acquire one or more reference drug component catalogs. Yet another example: the data processing system can first acquire one or more reference drug component catalogs, then acquire the experimental data of the first microfluidic chip, and finally acquire the reference drug molecule data of the reference drug component. For example, the data processing system may acquire reference drug molecule data and one or more reference drug ingredient catalogs during the process of acquiring experimental data of the first microfluidic chip, or acquire experimental data of the first microfluidic chip and one or more reference drug ingredient catalogs during the process of acquiring reference drug molecule data of the reference drug ingredient, or acquire experimental data of the first microfluidic chip and reference drug molecule data during the process of acquiring one or more reference drug ingredient catalogs.

[0052] 102. Perform drug feature vector analysis on the experimental data of the first microfluidic chip to obtain the first visualization recommendation result of the cell response feature vector set that needs to be preprocessed.

[0053] In this embodiment, the first visual recommendation result includes an attribute directory of the set of cell response feature vectors that need preprocessing. Specifically, by comparing the visual recommendation result of a randomly selected set of cell response feature vectors with the first visual recommendation result, it can be determined whether the selected set of cell response feature vectors is the same as the set of cell response feature vectors that need preprocessing. Furthermore, the first visual recommendation result includes a key description of the attribute directory of the set of cell response feature vectors that need preprocessing.

[0054] In an alternative embodiment, the first visual recommendation result is accompanied by salient key information of the set of cellular response feature vectors that need to be preprocessed.

[0055] In one possible implementation, the first visual recommendation result is accompanied by all key information of the set of cell response feature vectors that need to be preprocessed, wherein all key information includes all multi-strategy result description information of the set of cell response feature vectors that need to be preprocessed.

[0056] In another possible implementation, the first visual recommendation result includes both salient key information of the set of cell response feature vectors that need to be preprocessed and all key information of the set of cell response feature vectors that need to be preprocessed.

[0057] In this embodiment, drug feature vector analysis is used to filter and visualize recommended results of the set of cellular response feature vectors in microfluidic chip experimental data. In an alternative embodiment, the data processing system performs feature extraction on the microfluidic chip experimental data to achieve drug feature vector analysis of the microfluidic chip experimental data.

[0058] 103. Obtain a catalog of one or more first-cell response feature vector sets for reference drug components.

[0059] In this embodiment, one or more directories of first cell response feature vector sets refer to directories of cell response feature vector sets that require preprocessing. These directories can be a single directory of first cell response feature vector sets, or they can be multiple directories of first cell response feature vector sets. For example, one or more directories of first cell response feature vector sets may include the types of cell response feature vector sets that require preprocessing. Alternatively, one or more directories of first cell response feature vector sets may include the types of cell response feature vector sets that require preprocessing and the multi-strategy results of the cell response feature vector sets that require preprocessing.

[0060] In one implementation of obtaining one or more directories of first cell response feature vector sets that require preprocessing, the directory of one or more first cell response feature vector sets that require preprocessing is recorded in the data processing system. The data processing system can filter the directory of one or more first cell response feature vector sets that require preprocessing to obtain the directory of one or more first cell response feature vector sets that require preprocessing.

[0061] In another implementation of obtaining one or more directories of first cell response feature vector sets that need to be preprocessed, the data processing system collects one or more directories of first cell response feature vector sets that need to be preprocessed.

[0062] In another implementation of obtaining one or more directories of first cell response feature vector sets that need to be preprocessed, the data processing system collects one or more directories of first cell response feature vector sets that need to be preprocessed.

[0063] 104. Based on the similarity between the first visualization recommendation results and the reference drug molecule data, and the matching between the first cell response feature vector set directory and the reference drug component directory, the intelligent screening results of the cell response feature vector set that needs to be preprocessed and the reference drug components are obtained.

[0064] In this embodiment, the matching status of one or more first cell response feature vector sets and one or more reference drug ingredient lists includes either a matching relationship between the first cell response feature vector sets and one or more reference drug ingredient lists, or no matching relationship between the first cell response feature vector sets and one or more reference drug ingredient lists. The intelligent cancer drug screening result may include cases where the cell response feature vector set requiring preprocessing is the same as the reference drug ingredient, or cases where the cell response feature vector set requiring preprocessing is different from the reference drug ingredient.

[0065] In an alternative embodiment, the data processing system determines whether there is a connection between the first visual recommendation result and the reference drug molecule data based on the similarity between the first visual recommendation result and the reference drug molecule data.

[0066] If a connection is found between the first visualization recommendation result and the reference drug molecule data, and the matching includes one or more directories of first cell response feature vector sets and one or more directories of reference drug components, then the intelligent cancer drug screening result is determined to include cell response feature vector sets requiring preprocessing that are identical to the reference drug components. Otherwise, the intelligent cancer drug screening result is determined to include cell response feature vector sets requiring preprocessing that are different from the reference drug components.

[0067] In one possible implementation, the data processing system determines whether there is a connection between the first visual recommendation result and the reference drug molecule data based on the similarity between the first visual recommendation result and the reference drug molecule data.

[0068] Assuming a connection exists between the first visualization recommendation result and the reference drug molecular data, the intelligent cancer drug screening result is determined to include a set of cell response feature vectors requiring preprocessing that are identical to the reference drug components. Assuming the matching includes one or more directories of first cell response feature vectors and one or more directories of reference drug components, the intelligent cancer drug screening result is determined to include a set of cell response feature vectors requiring preprocessing that are identical to the reference drug components. Assuming a connection exists between the first visualization recommendation result and the reference drug molecular data, and the matching includes one or more directories of first cell response feature vectors and one or more directories of reference drug components, the intelligent cancer drug screening result is determined to include a set of cell response feature vectors requiring preprocessing that are identical to the reference drug components. Assuming no connection exists between the first visualization recommendation result and the reference drug molecular data, and the matching includes one or more directories of first cell response feature vectors and one or more directories of reference drug components not matching, the intelligent cancer drug screening result is determined to include a set of cell response feature vectors requiring preprocessing that are identical to the reference drug components.

[0069] In this embodiment, the data processing system determines the intelligent screening results of cancer drugs between the reference drug components and the cell response feature vector sets that need to be preprocessed by using the similarity between the first visual recommendation results and the reference drug molecule data, as well as the matching of one or more first cell response feature vector sets and one or more reference drug component sets. This can improve the reliability of the intelligent screening results of cancer drugs.

[0070] In one standalone embodiment, the data processing system may perform the following during step 104.

[0071] 1. Under the premise that the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the first similarity specified value, the cancer drug intelligent screening result of the cell response feature vector set that needs to be preprocessed and the reference drug component is obtained through the first cell response feature vector set directory and the reference drug component directory.

[0072] In this embodiment, the first similarity specification value is a positive integer. If the similarity between the reference drug molecule data and the first visualization recommendation result is greater than the first similarity specification value, it indicates that there is a high probability that the set of cell response feature vectors requiring preprocessing and the reference drug components are identical. Therefore, it can be further determined whether the set of cell response feature vectors requiring preprocessing and the reference drug components are identical by using one or more first cell response feature vector set directories and one or more reference drug component directories.

[0073] In an alternative embodiment, the data processing system determines whether the set of cell response feature vectors to be preprocessed is the same as the reference drug components by determining whether there is a matching relationship between one or more first cell response feature vector sets and one or more reference drug component sets, thereby obtaining the intelligent screening results of cancer drugs between the set of cell response feature vectors to be preprocessed and the reference drug components.

[0074] In one possible implementation, the data processing system determines the degree of matching between one or more first cell response feature vector sets and one or more reference drug ingredient lists. If the degree of matching is greater than a specified value, the cell response feature vector set requiring preprocessing is determined to be the same as the reference drug ingredient. If the degree of matching is less than or equal to the specified value, the cell response feature vector set requiring preprocessing is determined to be different from the reference drug ingredient.

[0075] Furthermore, if the data processing system determines that the similarity between the first visual recommendation result and the reference drug molecule data is less than or equal to a specified first similarity value, it will also determine that the intelligent cancer drug screening results, including the cell response feature vector set requiring preprocessing, are different from the reference drug components. That is, if the similarity between the first visual recommendation result and the reference drug molecule data is less than or equal to a specified first similarity value, it will not continue to compare one or more first cell response feature vector sets and one or more reference drug component lists.

[0076] In this embodiment, the data processing system, after determining that the similarity between the first visual recommendation result and the reference drug molecule data is greater than the first similarity specified value, further determines the intelligent screening result of cancer drugs through one or more first cell response feature vector sets and one or more reference drug component directories, which can improve the reliability of the intelligent screening result of cancer drugs.

[0077] In one embodiment, one or more first cell response feature vector set catalogs include first multi-strategy results of cell response feature vector sets that require preprocessing, and one or more reference drug ingredient catalogs include reference multi-strategy results of reference drug ingredients.

[0078] Under the premise that the data processing system obtains the first multi-strategy result by optimizing the experimental data of the first microfluidic chip through multi-strategy results, the data processing system obtains the reference multi-strategy result of the reference drug component. Then, by comparing the multi-strategy result of the cell response feature vector set that needs to be preprocessed with the multi-strategy result of the reference drug component, the intelligent screening result of cancer drugs between the cell response feature vector set that needs to be preprocessed and the reference drug component can be further determined.

[0079] Therefore, in the process of executing the step of "obtaining the intelligent screening results of the cancer drugs of the cell response feature vector set and the reference drug components that need to be preprocessed by the above-mentioned one or more first cell response feature vector set catalogs and the above-mentioned one or more reference drug component catalogs", the data processing system performs one of the following steps.

[0080] 2. Under the premise that the results of the first multi-strategy mentioned above match the results of the reference multi-strategy mentioned above, it is determined that the results of the intelligent screening of cancer drugs include the same set of cell response feature vectors that need to be preprocessed as the reference drug components.

[0081] 3. If the results of the first multi-strategy mentioned above do not match the results of the reference multi-strategy mentioned above, it is determined that the results of the intelligent screening of cancer drugs include the set of cell response feature vectors that need to be preprocessed and the components of the reference drugs mentioned above.

[0082] In one embodiment, one or more first cell response feature vector set directories include a first multi-strategy result of the cell response feature vector set to be preprocessed and one or more first complete directories of the cell response feature vector set to be preprocessed, and one or more reference drug ingredient directories include a reference multi-strategy result of the reference drug ingredient and one or more reference complete directories of the reference drug ingredient.

[0083] In this embodiment, the complete directory of cell response feature vector sets includes a directory of cell response feature vector sets excluding multi-strategy results. Further, the complete directory includes one or more of the following: a drug recommendation list, cell response feature vector set types, and a directory of cell response feature vector sets. The first complete directory is the complete directory of cell response feature vector sets requiring preprocessing, and the reference complete directory is the complete directory of reference drug components.

[0084] Furthermore, the data processing system obtains one or more first complete directories of the cell response feature vector set that need to be preprocessed by performing a full directory screening process on the experimental data of the first microfluidic chip. In this embodiment, the full directory screening process is used to filter out all directories in the microfluidic chip experimental data.

[0085] In this embodiment, the data processing system performs the following steps during the process of "obtaining the intelligent screening results of the cancer drugs of the cell response feature vector set and the reference drug components that need to be preprocessed by using the above-mentioned one or more first cell response feature vector set catalogs and the above-mentioned one or more reference drug component catalogs".

[0086] 4. Under the premise that the results of the first multi-strategy mentioned above match the results of the reference multi-strategy mentioned above, the results of intelligent screening of cancer drugs for the set of cell response feature vectors that need to be preprocessed and the reference drug components are obtained through one or more of the first complete directories and one or more of the reference complete directories mentioned above.

[0087] In an alternative embodiment, the data processing system determines whether the set of cell response feature vectors to be preprocessed is the same as the reference drug component by determining whether there is a matching relationship between one or more first all directories and one or more reference all directories, thereby obtaining the intelligent screening result of cancer drugs between the set of cell response feature vectors to be preprocessed and the reference drug component.

[0088] In one possible implementation, the data processing system determines the existence matching degree of one or more first complete directories and one or more reference complete directories. If the existence matching degree is greater than a specified value, it is determined that the set of cell response feature vectors requiring preprocessing is the same as the reference drug component. If the existence matching degree is less than or equal to the specified value, it is determined that the set of cell response feature vectors requiring preprocessing is different from the reference drug component.

[0089] In this embodiment, the data processing system, after determining that the first multi-strategy result matches the reference multi-strategy result, further determines the intelligent screening result of cancer drugs through one or more first complete directories and one or more reference complete directories, which can improve the reliability of the intelligent screening result of cancer drugs.

[0090] Furthermore, assuming the first multi-strategy result matches the reference multi-strategy result, the data processing system performs a full catalog screening process on the first microfluidic chip experimental data to obtain one or more first full catalogs. After obtaining one or more first full catalogs, the data processing system uses one or more first full catalogs and one or more reference full catalogs to obtain the set of cell response feature vectors requiring preprocessing and the intelligent screening results for cancer drugs of the aforementioned reference drug components. If the data processing system determines that the first multi-strategy result does not match the reference multi-strategy result, it does not perform the full catalog screening process on the first microfluidic chip experimental data.

[0091] In one standalone embodiment, one or more reference drug ingredient directories include one or more reference complete directories of reference drug ingredients. After determining that the similarity between the first visualization recommendation result and the reference drug molecule data is greater than a first similarity specified value, the data processing system obtains one or more cell response feature vector set directories that require preprocessing by performing the following steps.

[0092] 5. Without analyzing the first multi-strategy result of the cell response feature vector set that needs to be preprocessed, perform full directory screening on the experimental data of the first microfluidic chip to obtain one or more first full directories of the cell response feature vector set that needs to be preprocessed.

[0093] If the first multi-strategy result of the cell response feature vector set that needs to be preprocessed is not obtained by optimizing the catalog of the experimental data of the first microfluidic chip, then it is impossible to determine whether the cell response feature vector set that needs to be preprocessed and the reference drug component are the same information by comparing the multi-strategy result of the cell response feature vector set that needs to be preprocessed with the multi-strategy result of the reference drug component.

[0094] Therefore, under this premise, the data processing system performs a full catalog screening process on the experimental data of the first microfluidic chip to obtain one or more first full catalogs of cell response feature vector sets that need to be preprocessed. By comparing the full catalogs of the cell response feature vector sets that need to be preprocessed with the full catalogs of the reference drug components, it can determine whether the cell response feature vector sets that need to be preprocessed and the reference drug components are the same information, thereby improving the reliability of the intelligent screening results for cancer drugs.

[0095] After completing step 5, the data processing system performs the following steps during the process of "obtaining the intelligent screening results of the cancer drugs of the cell response feature vector set and the reference drug components that need to be preprocessed by using the above-mentioned one or more first cell response feature vector set catalogs and the above-mentioned one or more reference drug component catalogs".

[0096] 6. By using one or more first complete directories and one or more reference complete directories, the set of cell response feature vectors that need to be preprocessed and the intelligent screening results of reference drug components for cancer drugs are obtained.

[0097] In this embodiment, when there is a connection between the visualized recommendation results of the cell response feature vector set that needs preprocessing and the visualized recommendation results of the reference drug component, and without analyzing the first multi-strategy result, the data processing system further determines that the cell response feature vector set that needs preprocessing is the same as the reference drug component by comparing the complete catalog of the cell response feature vector set that needs preprocessing with the complete catalog of the reference drug component, thereby improving the reliability of the intelligent screening results for cancer drugs.

[0098] In a standalone embodiment, the data processing system performs the following steps during the process of "obtaining a set of cell response feature vectors requiring preprocessing and intelligent screening results of reference drug components for cancer drugs through one or more first complete directories and one or more reference complete directories".

[0099] 7. Determine whether there is a matching relationship between the above one or more first complete directories and the above one or more reference complete directories to obtain the first matching situation.

[0100] In this embodiment, the first matching situation includes one or more first all directories and one or more reference all directories having a matching relationship, or one or more first all directories and one or more reference all directories not having a matching relationship.

[0101] In an alternative embodiment, the data processing system obtains one or more related pairs of all directories through one or more first all directories and one or more reference all directories, wherein each related pair of all directories includes a first all directory and a reference all directory, and the first all directory in the related pair of all directories and the reference all directory in the related pair of all directories represent the same all directory.

[0102] For example, one or more first complete directories include a drug recommendation list of cell response feature vector sets that need to be preprocessed and a cell response feature vector set category that needs to be preprocessed; one or more reference complete directories include a drug recommendation list of reference drug ingredients and a directory of cell response feature vector sets of reference drug ingredients. In this case, the related complete directory pairs include a drug recommendation list of reference drug ingredients and a drug recommendation list of cell response feature vector sets that need to be preprocessed.

[0103] The data processing system determines a first matching scenario if, assuming that both directories in each related directory pair are identical, the first matching scenario includes one or more first directories and one or more reference directories that have a matching relationship. Otherwise, the data processing system determines that a first matching scenario includes one or more first directories and one or more reference directories that do not have a matching relationship.

[0104] For example, there are related directories x and related directories y in one or more first directories and one or more reference directories, where the related directories x includes a drug recommendation list of reference drug components and a drug recommendation list of cell response feature vector sets that need to be preprocessed, and the related directories y includes the types of cell response feature vector sets of reference drug components and the types of cell response feature vector sets that need to be preprocessed.

[0105] If the drug recommendation list of the reference drug components is the same as the drug recommendation list of the cell response feature vector set that needs to be pretreated, and the type of the cell response feature vector set of the reference drug components is the same as the type of the cell response feature vector set of the cell response feature vector set that needs to be pretreated, then the first matching case includes one or more first all directories and one or more reference all directories having a matching relationship.

[0106] If the recommended drug list for the reference drug components and the recommended drug list for the set of cell response feature vectors requiring preprocessing are different, then the first matching scenario includes one or more first complete directories and one or more reference complete directories that do not have a matching relationship. If the types of cell response feature vector sets for the reference drug components and the types of cell response feature vector sets for the set of cell response feature vectors requiring preprocessing are different, then the first matching scenario includes one or more first complete directories and one or more reference complete directories that do not have a matching relationship.

[0107] After obtaining the first match, the data processing system determines the results of the intelligent cancer drug screening by performing one of the following steps.

[0108] 8. Under the premise that the first matching situation mentioned above includes matching one or more of the first complete directories and one or more of the reference complete directories, it is determined that the intelligent screening result of the cancer drug includes the set of cell response feature vectors that need to be preprocessed and the same as the reference drug components.

[0109] In this embodiment, the first matching scenario includes one or more first complete directories matching one or more reference complete directories, indicating that the complete directories of the cell response feature vector set requiring preprocessing match the complete directories of the reference drug components. Therefore, the data processing system determines that the cell response feature vector set requiring preprocessing is the same as the reference drug components.

[0110] 9. If the first matching condition mentioned above includes a mismatch between one or more of the first complete directories and one or more of the reference complete directories, it is determined that the intelligent screening result of the cancer drug includes a set of cell response feature vectors that need to be preprocessed that is different from the reference drug components.

[0111] In this embodiment, the first matching scenario includes one or more first complete directories not matching one or more reference complete directories, indicating that the complete directories of the cell response feature vector set requiring preprocessing do not match the complete directories of the reference drug components. Therefore, the data processing system determines that the cell response feature vector set requiring preprocessing is different from the reference drug components.

[0112] In one embodiment, one or more first complete directories and one or more reference complete directories all include quantization results. For example, one or more first complete directories include a drug recommendation list of cell response feature vector sets requiring preprocessing and a list of cell response feature vector set types requiring preprocessing. One or more first complete directories include a quantization result set, where the drug recommendation list of cell response feature vector sets requiring preprocessing contains quantization results, and the list of cell response feature vector set types requiring preprocessing also contains quantization results.

[0113] One or more reference directories include a drug recommendation list for reference drug ingredients and a directory of cellular response feature vector sets for reference drug ingredients. One or more reference directories also include a set of quantification results; the drug recommendation list for reference drug ingredients contains quantification results, and the directory of cellular response feature vector sets for reference drug ingredients also contains quantification results.

[0114] In this embodiment, the data processing system may also perform the following steps before executing step 7.

[0115] 10. Obtain a second specified similarity value, wherein the second specified similarity value is greater than the first specified similarity value.

[0116] In one implementation of obtaining a second similarity specification value, the data processing system collects the second similarity specification value.

[0117] In another implementation of obtaining the second similarity specification value, the data processing system collects the second similarity specification value.

[0118] After completing step 10, the data processing system performs one of the following steps during the execution of step 7.

[0119] 11. If the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the second similarity specified value, and the first or more first complete directories and the first or more reference complete directories meet the first matching relationship requirement or the second matching relationship requirement, then the first matching situation is determined to include the matching relationship between the first or more first complete directories and the first or more reference complete directories.

[0120] 12. If the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the second similarity specified value, and the above one or more first complete directories and the above one or more reference complete directories do not meet the above first matching relationship requirement and the second matching relationship requirement, it is determined that the above first matching situation includes the above one or more first complete directories and the above one or more reference complete directories not having a matching relationship.

[0121] If two directories representing the same directories in one or more first directories and one or more reference directories are considered to be related directories, then the related directories whose quantization results of the two directories are both greater than the specified value of the quantization result are considered as related directories with optimized quantization results, where the specified value of the quantization result is a positive integer.

[0122] For example, one or more first complete directories include a drug recommendation list of cell response feature vector sets requiring preprocessing and a list of cell response feature vector sets requiring preprocessing. One or more reference complete directories include a drug recommendation list of reference drug components and a directory of cell response feature vector sets of reference drug components. In this case, both the drug recommendation list of cell response feature vector sets requiring preprocessing and the drug recommendation list of reference drug components represent the complete directory of drug recommendation lists. That is, the related complete directory pair includes both the drug recommendation list of cell response feature vector sets requiring preprocessing and the drug recommendation list of reference drug components.

[0123] If the quantization result of the drug recommendation list for the cell response feature vector set that needs preprocessing is greater than the specified value of the quantization result, and the quantization result of the drug recommendation list for the reference drug component is also greater than the specified value of the quantization result, then the drug recommendation list for the cell response feature vector set that needs preprocessing and the drug recommendation list for the reference drug component are all directory pairs that are related to the optimized quantization result.

[0124] In this embodiment, the first requirement for a matching relationship includes: there are no directories in one or more first all directories and one or more reference all directories that represent the same all directory and whose quantization result is greater than a specified value of the quantization result. That is, the first requirement for a matching relationship includes: there are no directory pairs in one or more first all directories and one or more reference all directories that have a relationship with the optimized quantization result. For example, one or more first all directories include a drug recommendation list of cell response feature vector sets that need preprocessing and cell response feature vector set types of cell response feature vector sets that need preprocessing; one or more reference all directories include a directory of cell response feature vector sets of reference drug components. In this case, there are no related directory pairs in one or more first all directories and one or more reference all directories, therefore there are no related directory pairs with optimized quantization results in one or more first all directories and one or more reference all directories. In this case, one or more first all directories and one or more reference all directories meet the first requirement for a matching relationship. For example, one or more first complete directories include a drug recommendation list of cell response feature vector sets requiring preprocessing and a list of cell response feature vector sets requiring preprocessing. One or more reference complete directories include a drug recommendation list of reference drug ingredients and a directory of cell response feature vector sets of reference drug ingredients. In this case, both the drug recommendation list of cell response feature vector sets requiring preprocessing and the drug recommendation list of reference drug ingredients represent the complete directory of drug recommendation lists. That is, there is a related complete directory pair including both the drug recommendation list of cell response feature vector sets requiring preprocessing and the drug recommendation list of reference drug ingredients.

[0125] If the quantification result of the drug recommendation list for the cell response feature vector set requiring preprocessing is greater than the specified quantification result value, and the quantification result of the drug recommendation list for the reference drug components is less than the specified quantification result value, then there are no matching pairs of directories in one or more all directories and one or more reference all directories. Therefore, one or more first all directories and one or more reference all directories meet the first matching relationship requirement.

[0126] In this embodiment, the second requirement for the existence of a matching relationship includes: the second complete directory in one or more first complete directories is the same as the third complete directory in one or more reference complete directories, the second complete directory and the third complete directory represent the same complete directory, and the quantization result of the second complete directory and the quantization result of the third complete directory are both greater than the specified value of the quantization result.

[0127] In the second matching requirement, the second complete directory belongs to one or more first complete directories, the third complete directory belongs to one or more reference complete directories, and the second complete directory is the same as the third complete directory, that is, the second complete directory and the third complete directory are the aforementioned related complete directory pairs. The quantization results of both the second and third complete directories are greater than the specified quantization result value, that is, the second complete directory and the second and third complete directories are the aforementioned related complete directory pairs based on the optimized quantization results.

[0128] It is understandable that the second and third complete directories are merely examples. What is not understandable is the existence of only one related optimization quantization result among one or more first complete directories and one or more reference complete directories. In practical applications, the two directories in any randomly selected related optimization quantization result pair within one or more first complete directories and one or more reference complete directories should be identical. For example, one or more first complete directories might include a drug recommendation list of cell response feature vector sets requiring preprocessing and a list of cell response feature vector set types requiring preprocessing; similarly, one or more reference complete directories might include a drug recommendation list of reference drug components and a list of cell response feature vector set types for reference drug components. At this point, both the drug recommendation list for the cell response feature vector set requiring preprocessing and the drug recommendation list for the reference drug components represent the entire directory of the drug recommendation list. Similarly, both the cell response feature vector set types for the cell response feature vector set requiring preprocessing and the cell response feature vector set types for the reference drug components represent the entire directory of the cell response feature vector set types. That is, all related directory pairs include related directory pairs x and y. Specifically, related directory pair x includes the drug recommendation list for the cell response feature vector set requiring preprocessing and the drug recommendation list for the reference drug components, while related directory pair y includes the cell response feature vector set types for the cell response feature vector set requiring preprocessing and the cell response feature vector set types for the reference drug components.

[0129] If the quantification results of the drug recommendation list of the cell response feature vector set that needs preprocessing, the quantification results of the cell response feature vector set types of the cell response feature vector set that needs preprocessing, the quantification results of the drug recommendation list of the reference drug ingredient, and the quantification results of the cell response feature vector set types of the reference drug ingredient are all greater than the specified value of the quantification result, then all related directory pairs x and all related directory pairs y are all related directory pairs in the optimized quantification result.

[0130] Provided that two directories in a pair of related directories x are identical, and two directories in a pair of related directories y are identical, one or more first all directories and one or more reference all directories are determined to meet the second existence matching relationship requirement; otherwise, one or more first all directories and one or more reference all directories are determined not to meet the second existence matching relationship requirement. Specifically, two identical directories in a pair of related directories x indicate that the drug recommendation lists of the first cell response feature vector set and the second cell response feature vector set are identical; similarly, two identical directories in a pair of related directories y indicate that the cell response feature vector set types of the first cell response feature vector set and the second cell response feature vector set types are identical.

[0131] In this embodiment, the specified value of the quantization result is used to determine whether the quantization result of the entire directory is good or bad. Specifically, if the quantization result of the entire directory is greater than the specified value, it means that the quantization result of the entire directory is good, and if the quantization result of the entire directory is less than or equal to the specified value, it means that the quantization result of the entire directory is bad.

[0132] Assuming good quantization results across all directories, updating the cell response feature vector set using all directories can improve update reliability. However, if the quantization results across all directories are poor, updating the cell response feature vector set using all directories may result in anomalies. Therefore, it is possible to determine whether a matching relationship exists between one or more first all directories and one or more reference all directories by using one or more directories in the first all directory whose quantization results are greater than a specified value, and one or more directories in the reference all directory whose quantization results are greater than a specified value.

[0133] If one or more first complete directories and one or more reference complete directories do not contain any directories with related optimized quantification results, determining whether one or more first complete directories and one or more reference complete directories have a matching relationship may lead to anomalies. Since the absence of matching relationships among one or more first complete directories and one or more reference complete directories would result in updating the set of cell response feature vectors requiring preprocessing to a different set of cell response feature vectors than the reference drug component, and the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the second similarity specified value, the probability that the set of cell response feature vectors requiring preprocessing is the same as the reference drug component is relatively high. Therefore, under the premise that one or more first complete directories and one or more reference complete directories do not contain any directories with related optimized quantification results, a matching relationship is determined for one or more first complete directories and one or more reference complete directories. In this way, the data processing system, upon determining that one or more first complete directories and one or more reference complete directories meet the first matching relationship requirement, determines that the first matching situation includes one or more first complete directories matching one or more reference complete directories, which reduces the possibility of anomalies in the first matching situation, and thus reduces the possibility of anomalies in the set of cell response feature vectors requiring preprocessing.

[0134] If there are related directories in one or more first complete directories and one or more reference complete directories, then the existence of a matching relationship between one or more complete directories and one or more reference complete directories can be determined by the related directories. In an alternative embodiment, if the two complete directories in the related directories are the same, it indicates that there is no conflict between the directories in one or more first complete directories and one or more reference complete directories, thus determining that there is a matching relationship between the directories in one or more first complete directories and one or more reference complete directories. In this way, the data processing system, under the premise that it determines that one or more first complete directories and one or more reference complete directories meet the second matching relationship requirement, determines that the first matching situation includes a matching relationship between one or more first complete directories and one or more reference complete directories, which can improve the reliability of the first matching situation and thus reduce the probability of anomalies in the set of cell response feature vectors that need to be preprocessed.

[0135] Conversely, if it is determined that one or more first complete directories and one or more reference complete directories do not meet the first requirement of existing matching relationship, and one or more first complete directories and one or more reference complete directories do not meet the second requirement of existing matching relationship, the first matching situation is determined to include one or more first complete directories and one or more reference complete directories not having a matching relationship.

[0136] In a separate implementation, the data processing system further performs the following, provided that the similarity between the first visual recommendation result and the reference drug molecule data is less than or equal to a second specified similarity value.

[0137] 13. If there are no directories representing the same total directory in one or more of the above-mentioned first total directories and one or more of the above-mentioned reference total directories, and the quantization result is greater than the specified value of the above-mentioned quantization result, it is determined that the above-mentioned first matching situation includes that there is no matching relationship between the above-mentioned one or more of the first total directories and the above-mentioned one or more of the above-mentioned reference total directories.

[0138] In this embodiment, there are no directories in one or more first all directories and one or more reference all directories that represent the same all directory and whose quantization result is greater than the specified value of the quantization result. That is, there are no directories in one or more first all directories and one or more reference all directories that are related to the optimized quantization results. In this case, determining whether there is a matching relationship between one or more first all directories and one or more reference all directories may result in anomalies. Since there is a matching relationship between one or more first all directories and one or more reference all directories, it will cause the set of cell response feature vectors that need to be preprocessed to be updated to the same set of cell response feature vectors as the reference drug component. However, the similarity between the first visualization recommendation result and the reference drug molecule data is less than or equal to the second similarity specified value, indicating that the probability that the set of cell response feature vectors that need to be preprocessed is the same as the reference drug component is relatively small compared to the probability that the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the second similarity specified value. Therefore, under the premise that there are no all directory pairs in one or more first all directories and one or more reference all directories that are related to the optimized quantization results, it is determined that there is no matching relationship between one or more first all directories and one or more reference all directories. In this way, the possibility of anomalies in the set of cell response feature vectors that need to be preprocessed can be reduced.

[0139] If one or more first total directories and one or more reference total directories contain total directories whose optimization quantization results are related, then proceed to step 14.

[0140] 14. Determine whether there is a matching relationship between the fourth all directory in one or more first all directories and the fifth all directory in one or more reference all directories to obtain a second matching situation, wherein the quantization result of the fourth all directory and the quantization result of the fifth all directory are both greater than the specified value of the quantization result, and the fourth all directory and the fifth all directory represent the same all directory.

[0141] In this embodiment, the fourth complete directory belongs to one or more first complete directories, and the fifth complete directory belongs to one or more reference complete directories. Furthermore, the fourth and fifth complete directories are identical, meaning they are the aforementioned related complete directory pairs. The quantization results of both the fourth and fifth complete directories are greater than a specified quantization result value, indicating they are also related in terms of optimized quantization results. Based on the above, if one or more first complete directories and one or more reference complete directories contain related complete directory pairs with optimized quantization results, then the existence of a matching relationship between one or more complete directories and one or more reference complete directories can be determined through these related pairs. Therefore, the data processing system can determine whether a matching relationship exists between one or more complete directories and one or more reference complete directories through the second matching condition. Specifically, after obtaining the second matching condition, the data processing system determines whether a matching relationship exists between one or more complete directories and one or more reference complete directories by executing step 15 or step 16.

[0142] 15. If the second matching scenario includes the matching of the fourth and fifth directories, it is determined that the first matching scenario includes the matching relationship between one or more of the first directories and one or more of the reference directories.

[0143] 16. If the above-mentioned second matching situation includes the above-mentioned fourth complete directory and the above-mentioned fifth complete directory not matching, it is determined that the above-mentioned first matching situation includes the above-mentioned one or more first complete directories and the above-mentioned one or more reference complete directories not matching.

[0144] It is understandable that the fourth and fifth all directories are merely examples. It is not understandable that this refers to a set of all directories where only one optimized quantization result is related within one or more first all directories and one or more reference all directories. In practical applications, if one or more all directories where optimized quantization results are related exist within one or more first all directories and one or more reference all directories, the data processing system can determine the second matching condition for each such pair. Provided that all second matching conditions include matching of two all directories within the all directories where optimized quantization results are related, the first matching condition is determined to include a matching relationship between one or more first all directories and one or more reference all directories; otherwise, the first matching condition is determined to include a non-matching relationship between one or more first all directories and one or more reference all directories. For example, one or more first all directories might include a list of recommended drugs for cell response feature vector sets requiring preprocessing and a set of cell response feature vector types for cell response feature vector sets requiring preprocessing; one or more reference all directories might include a list of recommended drugs for reference drug components and a set of cell response feature vector types for reference drug components. At this point, the drug recommendation list for the cell response feature vector set that needs preprocessing and the drug recommendation list for the reference drug components both represent the entire directory of the drug recommendation list. Similarly, the cell response feature vector set types for the cell response feature vector set that needs preprocessing and the cell response feature vector set types for the reference drug components both represent the entire directory of the cell response feature vector set types. That is, all related directory pairs include related directory pairs x and y. Specifically, related directory pair x includes the drug recommendation list for the cell response feature vector set that needs preprocessing and the drug recommendation list for the reference drug components, and related directory pair y includes the cell response feature vector set types for the cell response feature vector set that needs preprocessing and the cell response feature vector set types for the reference drug components.

[0145] If the quantification results of the drug recommendation list of the cell response feature vector set that needs preprocessing, the quantification results of the cell response feature vector set types of the cell response feature vector set that needs preprocessing, the quantification results of the drug recommendation list of the reference drug ingredient, and the quantification results of the cell response feature vector set types of the reference drug ingredient are all greater than the specified value of the quantification result, then all related directory pairs x and all related directory pairs y are all related directory pairs in the optimized quantification result.

[0146] The data processing system determines whether there is a matching relationship between the drug recommendation list of the cell response feature vector set that needs preprocessing and the drug recommendation list of the reference drug component, and obtains the second matching case X of all directory pairs x that are related to the optimized quantification result. The data processing system determines whether there is a matching relationship between the types of cell response feature vector sets of the cell response feature vector set that needs preprocessing and the types of cell response feature vector sets of the reference drug component, and obtains the second matching case Y of all directory pairs y that are related to the optimized quantification result.

[0147] If, under the premise that the drug recommendation list of the cell response feature vector set requiring preprocessing in the second matching case X matches the drug recommendation list of the reference drug ingredient, and the cell response feature vector set type of the cell response feature vector set requiring preprocessing in the second matching case Y matches the cell response feature vector set type of the reference drug ingredient, then it is determined that the first matching case includes one or more first complete directories and one or more reference complete directories that have a matching relationship; otherwise, it is determined that the first matching case includes one or more first complete directories and one or more reference complete directories that do not have a matching relationship.

[0148] In one standalone embodiment, the data processing system performs one of the following steps during the execution of step 14.

[0149] 17. Under the premise that the above-mentioned fourth complete directory and the above-mentioned fifth complete directory are the same, it is determined that the above-mentioned second matching situation includes the existence of a matching relationship between the above-mentioned fourth complete directory and the above-mentioned fifth complete directory.

[0150] 18. If the above-mentioned fourth complete directory and the above-mentioned fifth complete directory are not the same, it is determined that the above-mentioned second matching situation includes the above-mentioned fourth complete directory and the above-mentioned fifth complete directory having no matching relationship.

[0151] In steps 17 and 18, the data processing system determines whether a matching relationship exists between the fourth and fifth all directories by judging whether they are the same. In other words, the data processing system determines whether a matching relationship exists between two all directories in a directory pair where the optimization quantization results are related by judging whether they are the same.

[0152] In one standalone embodiment, the data processing system performs one of the following steps during the execution of step 14.

[0153] 19. Given that the above-mentioned fourth complete directory and the above-mentioned fifth complete directory respectively represent the first drug recommendation list and the second drug recommendation list, it is found that there is a matching relationship between the drug recommendation lists of the above-mentioned first drug recommendation list and the above-mentioned second drug recommendation list.

[0154] As is known from existing technology, the collection requirements when collecting microfluidic chip experimental data may interfere with the accuracy of the microfluidic chip experimental data. One or more first complete directories are obtained by filtering the first microfluidic chip experimental data, that is, the drug recommendation list of the first cell response feature vector set is obtained by filtering the first microfluidic chip experimental data. Therefore, if the collection requirements when collecting the first microfluidic chip experimental data are inadequate, the drug recommendation list in the first microfluidic chip experimental data may be unreliable, which in turn leads to low reliability of the fourth complete directory obtained by filtering the first microfluidic chip experimental data, resulting in abnormal judgments on whether the fourth and fifth complete directories match.

[0155] In this embodiment, the drug recommendation lists of the first drug recommendation list and the second drug recommendation list have a matching relationship to correct the abnormal judgment of whether the fourth and fifth complete directories match due to poor collection requirements.

[0156] In one implementation of obtaining a matching list of drug recommendations, the drug recommendation list collected by the data processing system has matching relationships.

[0157] In another implementation of obtaining matching relationships in the drug recommendation list, the data processing system loads the drug recommendation list to find matching relationships.

[0158] After obtaining a matching relationship from the drug recommendation list, the data processing system can determine whether there is a matching relationship between the fourth and fifth complete directories by performing one of the following steps.

[0159] 20. If, based on the existence of matching relationships in the aforementioned drug recommendation lists, it is determined that the entire directory of the first drug recommendation list and the entire directory of the second drug recommendation list do not match, then the second matching situation includes the absence of matching relationships between the entire directory of the fourth list and the entire directory of the fifth list.

[0160] 21. Given that the matching relationship between the above-mentioned drug recommendation lists determines that the entire directory of the first drug recommendation list and the entire directory of the second drug recommendation list are matched, the above-mentioned second matching situation includes the matching relationship between the above-mentioned fourth and fifth directories.

[0161] Given that both the fourth and fifth complete directories represent drug recommendation lists, the data processing system determines whether there is a matching relationship between the fourth and fifth complete directories by checking the matching relationships in the drug recommendation lists, thus obtaining a second matching result, which can improve the reliability of the second matching result.

[0162] In one standalone embodiment, the data processing system performs the following steps during step 104.

[0163] 22. Under the premise that the above-mentioned one or more first cell response feature vector sets and the above-mentioned one or more reference drug ingredient sets match, the cancer drug intelligent screening results of the above-mentioned cell response feature vector sets that need to be preprocessed and the above-mentioned reference drug ingredient are obtained by using the similarity between the above-mentioned first visualization recommendation results and the above-mentioned reference drug molecule data.

[0164] In step 22, the data processing system first determines whether a matching relationship exists between one or more first cell response feature vector sets and one or more reference drug component directories. Assuming a match exists, the system determines whether the visualized recommendation results of the cell response feature vector sets requiring preprocessing are the same as the visualized recommendation results of the reference drug components, thereby obtaining the intelligent cancer drug screening results. Specifically, the intelligent cancer drug screening results for the cell response feature vector sets requiring preprocessing and the reference drug components are obtained based on the similarity between the first visualized recommendation results and the reference drug molecule data.

[0165] In an alternative embodiment, if the similarity between the first visual recommendation result and the reference drug molecule data is greater than a first specified similarity value, the data processing system determines that the intelligent screening result for cancer drugs includes a set of cell response feature vectors that require preprocessing that are the same as the reference drug components; if the similarity between the first visual recommendation result and the reference drug molecule data is less than or equal to the first specified similarity value, the data processing system determines that the intelligent screening result for cancer drugs includes a set of cell response feature vectors that require preprocessing that are different from the reference drug components.

[0166] In this embodiment, the data processing system, after determining that one or more first cell response feature vector sets and one or more reference drug component directories match, further determines the intelligent screening results of cancer drugs based on the similarity between the first visual recommendation results and the reference drug molecule data, which can improve the reliability of the intelligent screening results of cancer drugs.

[0167] Under the above premises, a computer-readable storage medium is also provided, wherein a computer program stored thereon implements the above method when it is run.

[0168] In summary, based on the above scheme, the following steps are taken: First microfluidic chip experimental data, reference drug molecule data of the reference drug component, and one or more reference drug component directories are obtained. Drug feature vector analysis is performed on the first microfluidic chip experimental data to obtain a first visual recommendation result for the set of cell response feature vectors requiring preprocessing. One or more directories of the first cell response feature vector set requiring preprocessing are obtained. By analyzing the similarity between the first visual recommendation result and the reference drug molecule data, and the matching results of one or more first cell response feature vector directories and one or more reference drug component directories, the intelligent screening result of the cancer drug between the set of cell response feature vectors requiring preprocessing and the reference drug components is obtained. This invention solves the problems of low efficiency, insufficient accuracy, and poor interpretability in traditional screening methods, providing efficient and intelligent technical support for anticancer drug development.

[0169] It should be understood that the systems and modules described above can be implemented in various ways. For example, in some embodiments, the systems and modules can be implemented by hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the methods and systems described above can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and modules of this application can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, or by a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0170] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects may be any one or a combination of the above, or any other possible beneficial effects.

[0171] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0172] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0173] Furthermore, those skilled in the art will understand that aspects of this application can be described and illustrated through several patentable types or situations, including any new and useful combination of processes, machines, products, or substances, or any new and useful improvements thereof. Accordingly, aspects of this application can be implemented entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. All of the above hardware or software may be referred to as a “data block,” “module,” “engine,” “unit,” “component,” or “system.” Furthermore, aspects of this application may manifest as a computer product located on one or more computer-readable media, the product including computer-readable program code.

[0174] Computer storage media may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and suitable combinations thereof. Computer storage media can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer storage medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or similar media, or any combination of the above media.

[0175] The computer program code required for the operation of each part of this application can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc., conventional procedural programming languages ​​such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages ​​such as Python, Ruby, and Groovy, or other programming languages. This program code can run entirely on the user's computer, or as a standalone software package on the user's computer, or partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network, such as a local area network (LAN) or wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service such as Software as a Service (SaaS).

[0176] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this application are not intended to limit the order of the processes and methods of this application. Although the foregoing disclosure has discussed some currently considered useful embodiments of the invention through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the substance and scope of the embodiments of this application. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely through software solutions, such as installing the described system on existing servers or mobile devices.

[0177] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this disclosure method does not imply that the subject matter of the application requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of the single embodiments disclosed above.

[0178] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are open to adaptive variation. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters are taken into account a specified number of significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of application in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0179] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this application, the entire contents of that patent are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this application, as well as documents that limit the broadest scope of the claims of this application (currently or subsequently appended to this application). It should be noted that if there are any discrepancies or conflicts between the descriptions, definitions, and / or terminology used in the supplementary materials of this application and the content of this application, the descriptions, definitions, and / or terminology used in this application shall prevail.

[0180] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other variations may also fall within the scope of this application. Therefore, as examples and not limitations, alternative configurations of the embodiments of this application can be considered the same as the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly described and illustrated in this application.

[0181] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. An artificial intelligence expert method for cancer drug screening based on cell-chip microarrays, characterized in that, The method includes at least: The experiment data is obtained from a first microfluidic chip, reference drug molecule data of a reference drug component, and a catalog of one or more reference drug components. The first microfluidic chip experimental data includes a set of cell response feature vectors that need to be preprocessed. Drug feature vector analysis is performed on the first microfluidic chip experimental data to obtain a first visualization recommendation result of the set of cell response feature vectors that need to be preprocessed. Obtain one or more directories of first cell response feature vector sets that require preprocessing; based on the similarity between the first visualization recommendation result and the reference drug molecule data, and the matching between the one or more directories of first cell response feature vector sets and the one or more directories of reference drug components, obtain the intelligent cancer drug screening result of the cell response feature vector sets that require preprocessing and the reference drug components.

2. The method according to claim 1, characterized in that, The process of obtaining the intelligent cancer drug screening results for the cell response feature vector set requiring preprocessing and the reference drug components by using the similarity between the first visual recommendation result and the reference drug molecule data, and the matching between the one or more first cell response feature vector set catalogs and the one or more reference drug component catalogs, includes: Provided that the similarity between the first visual recommendation result and the reference drug molecule data is greater than the first similarity specified value, the entire directory is filtered through the one or more first cell response feature vector set directories and the one or more reference drug component directories to obtain the cancer drug intelligent screening result of the cell response feature vector set that needs to be preprocessed and the reference drug component.

3. The method according to claim 2, characterized in that, Provided that the one or more first cell response feature vector set directories include the first multi-strategy results of the cell response feature vector set requiring preprocessing, and the one or more reference drug component directories include the reference multi-strategy results of the reference drug components, the step of obtaining the intelligent cancer drug screening results of the cell response feature vector set requiring preprocessing and the reference drug components through the one or more first cell response feature vector set directories and the one or more reference drug component directories includes: If the first multi-strategy result matches the reference multi-strategy result, the intelligent screening result for cancer drugs is determined to include a set of cell response feature vectors requiring pretreatment that is identical to the reference drug component; if the first multi-strategy result does not match the reference multi-strategy result, the intelligent screening result for cancer drugs is determined to include a set of cell response feature vectors requiring pretreatment that is different from the reference drug component.

4. The method according to claim 2, characterized in that, The one or more first cell response feature vector set directories include the first multi-strategy result of the cell response feature vector set to be preprocessed and one or more first complete directories of the cell response feature vector set to be preprocessed. The one or more reference drug component directories include the reference multi-strategy result of the reference drug component and one or more reference complete directories of the reference drug component. Obtaining the intelligent cancer drug screening result of the cell response feature vector set to be preprocessed and the reference drug component through the one or more first cell response feature vector set directories and the one or more reference drug component directories includes: under the premise that the first multi-strategy result matches the reference multi-strategy result, obtaining the intelligent cancer drug screening result of the cell response feature vector set to be preprocessed and the reference drug component through the one or more first complete directories and the one or more reference complete directories.

5. The method according to claim 2, characterized in that, The one or more reference drug ingredient catalogs include one or more reference complete catalogs of the reference drug ingredients; after the similarity between the first visualization recommendation result and the reference drug molecule data is greater than a first similarity specified value, the step of obtaining one or more cell response feature vector set catalogs of the cell response feature vector set that needs to be preprocessed includes: without analyzing the first multi-strategy result of the cell response feature vector set that needs to be preprocessed, performing a full catalog screening process on the first microfluidic chip experimental data to obtain one or more first complete catalogs of the cell response feature vector set that needs to be preprocessed; The step of obtaining the intelligent cancer drug screening results of the cell response feature vector set requiring preprocessing and the reference drug components through the one or more first cell response feature vector set directories and the one or more reference drug component directories includes: obtaining the intelligent cancer drug screening results of the cell response feature vector set requiring preprocessing and the reference drug components through the one or more first all directories and the one or more reference all directories.

6. The method according to claim 4 or 5, characterized in that, The process of obtaining the set of cell response feature vectors requiring preprocessing and the intelligent cancer drug screening results of the reference drug components through one or more first complete directories and one or more reference complete directories includes: Determine whether there is a matching relationship between the one or more first complete directories and the one or more reference complete directories to obtain the first matching situation; Under the premise that the first matching situation includes matching of one or more first all directories and one or more reference all directories, it is determined that the intelligent screening result of cancer drugs includes the set of cell response feature vectors that need to be preprocessed being the same as the reference drug components; If the first matching condition includes a mismatch between one or more first complete directories and one or more reference complete directories, it is determined that the intelligent screening result for cancer drugs includes a set of cell response feature vectors requiring preprocessing that is different from the reference drug components.

7. The method according to claim 6, characterized in that, The one or more first complete directories and the one or more reference complete directories all include quantization results; before determining whether the one or more first complete directories and the one or more reference complete directories have a matching relationship and obtaining the first matching situation, the method further includes: obtaining a second similarity specified value, wherein the second similarity specified value is greater than the first similarity specified value; The step of determining whether there is a matching relationship between the one or more first complete directories and the one or more reference complete directories to obtain a first matching situation includes: under the premise that the similarity between the first visualization recommendation result and the reference drug molecule data is greater than the second similarity specified value, and the one or more first complete directories and the one or more reference complete directories meet the first matching relationship requirement or the second matching relationship requirement, the first matching situation is determined to include the one or more first complete directories and the one or more reference complete directories having a matching relationship; If the similarity between the first visual recommendation result and the reference drug molecule data is greater than the second similarity specified value, and the one or more first all directories and the one or more reference all directories do not meet the first matching relationship requirement and the second matching relationship requirement, the first matching situation is determined to include the one or more first all directories and the one or more reference all directories not having a matching relationship. The first requirement for the existence of a matching relationship includes: there are no directories representing the same total directory in the one or more first total directories and the one or more reference total directories, and the quantization result is greater than the specified value of the quantization result; The second requirement for a matching relationship includes: the second complete directory in one or more first complete directories is the same as the third complete directory in one or more reference complete directories, the second complete directory and the third complete directory represent the same complete directory, and the quantization result of the second complete directory and the quantization result of the third complete directory are both greater than the specified value of the quantization result.

8. The method according to claim 7, characterized in that, Provided that the similarity between the first visual recommendation result and the reference drug molecule data is less than or equal to the second specified similarity value, the method further includes: If there are no directories representing the same total directory in one or more first total directories and one or more reference total directories, and the quantization result is greater than the specified value of the quantization result, then the first matching situation is determined to include the fact that there is no matching relationship between the one or more first total directories and the one or more reference total directories. Determine whether there is a matching relationship between the fourth all directory in one or more first all directories and the fifth all directory in one or more reference all directories to obtain a second matching situation, wherein the quantization result of the fourth all directory and the quantization result of the fifth all directory are both greater than the specified value of the quantization result, and the fourth all directory and the fifth all directory represent the same all directory. If the second matching scenario includes the matching of the fourth and fifth all directories, it is determined that the first matching scenario includes the matching relationship between the one or more first all directories and the one or more reference all directories. If the second matching condition includes the fact that the fourth all directories and the fifth all directories do not match, it is determined that the first matching condition includes the fact that one or more first all directories do not have a matching relationship with one or more reference all directories. The step of determining whether there is a matching relationship between the fourth complete directory in the one or more first complete directories and the fifth complete directory in the one or more reference complete directories to obtain the second matching situation includes: If the fourth and fifth complete directories are the same, the second matching condition is determined to include a matching relationship between the fourth and fifth complete directories; if the fourth and fifth complete directories are different, the second matching condition is determined to include a non-matching relationship between the fourth and fifth complete directories. The step of determining whether there is a matching relationship between the fourth complete directory in the one or more first complete directories and the fifth complete directory in the one or more reference complete directories to obtain the second matching situation includes: Given that the fourth and fifth all directories respectively represent the first drug recommendation list and the second drug recommendation list, it is found that the drug recommendation lists of the first drug recommendation list and the second drug recommendation list have a matching relationship; If, based on the existence of a matching relationship in the drug recommendation lists, it is determined that the first drug recommendation list and the second drug recommendation list do not match, then the second matching situation includes the fourth all-directory and the fifth all-directory not having a matching relationship; if, based on the existence of a matching relationship in the drug recommendation lists, it is determined that the first drug recommendation list and the second drug recommendation list match, then the second matching situation includes the fourth all-directory and the fifth all-directory having a matching relationship.

9. The method according to claim 1, characterized in that, The step of obtaining the intelligent cancer drug screening result of the cell response feature vector set requiring preprocessing and the reference drug components by using the similarity between the first visualization recommendation result and the reference drug molecule data, and the matching situation between the one or more first cell response feature vector set directories and the one or more reference drug component directories, includes: under the premise that the one or more first cell response feature vector set directories and the one or more reference drug component directories match, obtaining the intelligent cancer drug screening result of the cell response feature vector set requiring preprocessing and the reference drug components by using the similarity between the first visualization recommendation result and the reference drug molecule data.

10. An artificial intelligence expert system for cancer drug screening based on cell-chip microarrays, characterized in that, The method includes a processor and a memory that communicate with each other, the processor being configured to retrieve a computer program from the memory and to implement the method of any one of claims 1-9 by running the computer program.

Images