Communicating information about donor and receptor compatibility of graft

Abstract

An exemplary method includes obtaining information about a receptor of a graft and a potential donor of the graft, wherein the information includes an HLA (human leukocyte antigen) typing of the receptor and an HLA typing of the potential donor; obtaining a plurality of data sets based on the information, wherein each data set includes an indicator based on compatibility of the potential donor with the receptor of the graft; storing the plurality of data sets in a database; generating data for a user interface (UI), the data containing a representation of an indicator from one of the plurality of data sets in the database; and outputting the data for display on the display device.

Description

Technical Field

[0001] This specification generally relates to example systems and processes for conveying information about the compatibility of donors and recipients of grafts. Background Technology

[0002] The person who receives a graft (such as stem cells or a solid organ, such as a kidney or liver) is called a transplant recipient, or simply a recipient. The person who donates a graft is called a transplant donor, or simply a donor.

[0003] The better the compatibility between the donor and recipient, the lower the likelihood of the recipient rejecting the graft. One measure of compatibility is based on HLA (human leukocyte antigen) typing of the recipient and donor. Various techniques can be used to determine recipient / donor compatibility based on HLA typing. These techniques each provide different types of indicators to indicate the level of compatibility between the donor and recipient. Invention Overview

[0004] An example method is performed by one or more processing devices and includes the following operations: obtaining information about the recipient of the graft and potential donors of the graft, wherein the information includes the recipient's HLA (human leukocyte antigen) typing and the potential donor's HLA typing; obtaining multiple datasets based on the information, wherein each dataset includes indicators based on the compatibility between the potential donor and the recipient of the graft; storing the multiple datasets in a database; generating data for a user interface (UI) containing representations of the indicators from one of the multiple datasets in the database; and outputting the data for display on a display device. The method may include one or more of the following features, individually or in combination.

[0005] Indicators can be based on the compatibility of donor thymic (T) cells with recipient T cells. Indicators can be based on the compatibility of donor mucous sacs (B cells) with recipient B cells. Indicators can be based on misaligned peptides between the recipient's HLA type and the donor's HLA type.

[0006] Data sets may come from different sources. These different sources may include local sources and remote sources. Local sources may include entities from which information is obtained. Remote sources may be different from the entities from which patent information is obtained.

[0007] Information obtained may include the results of HLA typing of biological samples from recipients and potential donors.

[0008] The UI may include a table. This table may include columns for recipients and columns for potential donors. The recipient columns may include a first column containing a locus and a second column containing the recipient's allele at the corresponding locus in the first column. The potential donor columns may include a third column and one or more additional columns, the third column containing the potential donor's allele at the corresponding locus in the first column, and one or more additional columns containing indicators based on one or more of the compatibility of the donor's thymic (T) cells with the recipient's T cells or the compatibility of the donor's mucous sac (B) cells with the recipient's B cells. One or more additional indicators may be located in rows corresponding to the recipient's locus and allele or in rows corresponding to one or more serotype groups of the recipient.

[0009] Metrics may include values ​​representing the compatibility of a potential donor with the recipient of the graft. The UI may include box plots of populations containing recipients. The box plots may represent a range of values ​​for the population based on the compatibility of its members with the recipient of the graft. Values ​​for multiple potential donors may be overlaid on the box plot. Values ​​for multiple potential donors may be based on the compatibility of multiple potential donors with the recipient of the graft.

[0010] Multiple datasets may include MFI (mean fluorescence intensity) values. MFI values ​​can be based on the recipient's antigen, indicating rejection of the graft from the potential donor. UI data may include bar graphs containing MFI values ​​associated with the recipient's antigen. The bar graph may include a first axis of MFI values ​​and indices and a second axis corresponding to the recipient's antigen, indicating rejection of the graft from the potential donor.

[0011] The UI can include displaying all metrics or a single window that can be configured to scroll to reach all metrics.

[0012] Storing multiple datasets in a database can include storing each dataset in a table. Each table can include common information, such as the identity of the recipient, the identity of the potential donor, the HLA typing of the recipient, and the HLA typing of the potential donor.

[0013] One or more non-transitory machine-readable storage devices may store instructions executable by one or more processing devices to perform the following operations: obtaining information about the recipient of the graft and potential donors of the graft, wherein the information includes the recipient's HLA (human leukocyte antigen) typing and the potential donor's HLA typing; obtaining multiple datasets based on the information, wherein each dataset includes indicators based on the compatibility between the potential donor and the recipient of the graft; storing the multiple datasets in a database; generating data for a user interface (UI) containing representations of indicators from one of the multiple datasets in the database; and outputting the data for display on a display device. One or more of the following features may be included in the foregoing operations.

[0014] Indicators can be based on the compatibility of donor thymic (T) cells with recipient T cells. Indicators can be based on the compatibility of donor mucous sacs (B cells) with recipient B cells. Indicators can be based on misaligned peptides between the recipient's HLA type and the donor's HLA type.

[0015] Data sets can come from different sources. These different sources can include local sources and remote sources. Local sources can include entities from which information is obtained. Remote sources can be different from the entities from which patent information is obtained.

[0016] The information obtained may include the results of receiving HLA typing assays of biological samples from recipients and potential donors.

[0017] The UI may include a table. This table may include columns for recipients and columns for potential donors. The recipient columns may include a first column containing loci and a second column containing alleles of the recipient at the corresponding loci in the first column. The potential donor columns may include a third column and one or more additional columns, the third column containing alleles of potential donors at the corresponding loci in the first column, and one or more additional columns containing indicators based on one or more of the compatibility of donor thymic (T) cells with recipient T cells or donor mucosal (B) cells with recipient B cells. One or more additional indicators may be located in rows corresponding to recipient loci and alleles or rows corresponding to one or more serotype groups of the recipient.

[0018] Metrics may include values ​​representing the compatibility of a potential donor with the recipient of the graft. The UI may include box plots of populations containing recipients. The box plots may represent a range of values ​​for the population based on the compatibility of population members with the recipient of the graft. Values ​​for multiple potential donors may be overlaid on the box plot. Values ​​for multiple potential donors may be based on the compatibility of multiple potential donors with the recipient of the graft.

[0019] Multiple datasets may include MFI (mean fluorescence intensity) values. MFI values ​​can be based on the recipient's antigen, indicating rejection of the graft from the potential donor. UI data may include bar graphs containing MFI values ​​associated with the recipient's antigen. The bar graph may include a first axis of MFI values ​​and indices and a second axis corresponding to the recipient's antigen, indicating rejection of the graft from the potential donor.

[0020] The UI can include a single window that displays all indicators or is configured to scroll to reach all indicators.

[0021] Storing multiple datasets in a database can include storing each dataset in a table. Each table can include common information, such as the identity of the recipient, the identity of the potential donor, the HLA typing of the recipient, and the HLA typing of the potential donor.

[0022] At least a portion of the systems and processes described in this specification can be executed on one or more processing devices or controlled by executing instructions stored on one or more non-transitory machine-readable storage media on one or more processing devices. Examples of non-transitory machine-readable storage media include read-only memory, optical disc drives, storage disk drives, and random access memory (RAM). At least a portion of the systems and processes described in this specification can be implemented or controlled using a computing system including one or more processing devices and a memory storing instructions executable by the one or more processing devices to perform various control operations. The systems and processes described in this specification can be configured, for example, by designing, constructing, staging, arranging, placing, programming, operating, activating, deactivating, and / or controlling.

[0023] Two or more features described in this specification (including the overview section) may be combined to form embodiments not specifically described in this specification.

[0024] Details of one or more embodiments are set forth in the accompanying drawings and the description below. Other features and advantages will be apparent from the specification, drawings, and claims. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating operations included in an example process for conveying information about the compatibility of the donor and recipient of a graft.

[0026] Figure 2 It is a conceptual diagram illustrating how to obtain datasets containing compatible metrics from different sources.

[0027] Figure 3 This is a sample user interface (UI) used to provide information to be sent to the source to obtain the dataset.

[0028] Figure 4 This is a sample table of the UI that shows the compatibility metrics from different sources, displayed side-by-side for different donors.

[0029] Figure 5 This is another example table in the UI that shows compatibility metrics from different sources displayed side-by-side for different donors.

[0030] Figure 6 This is an example box plot showing an indicator of the compatibility of potential donors relative to a population containing recipients.

[0031] Figure 7 This is an example bar chart that combines the average fluorescence intensity (MFI) value with an index of compatibility from one or more other sources.

[0032] The same reference number indicates the same element.

[0033] Detailed description

[0034] This article describes examples of systems and processes for conveying information about the compatibility of recipients and potential donors of grafts. For example, a recipient may require a stem cell transplant or a solid organ transplant, such as a new kidney or a new liver. The systems and processes use information about the recipient and potential donor to obtain a dataset. The dataset includes indicators, such as those described herein, which are based on and can indicate the compatibility between the potential donor and recipient. The dataset may also include other information, such as the factors on which the compatibility is based.

[0035] Data sets can be obtained from multiple sources. For example, a dataset can be obtained from multiple third-party services, retrieved from local or remote storage devices, or generated locally. The dataset is stored in a database in the manner described herein, such that all or part of the dataset is linked and can be retrieved and displayed on the user interface (UI) at any time.

[0036] Metrics from different datasets from different donors, and in some cases, other information, can be displayed side-by-side with each other and alongside information about the recipient in the UI. The UI may be or include a single window displaying all metrics or configured for scrolling to reach all metrics. Thus, the UI summarizes metrics, and in some cases, summarizes other information from multiple datasets in a way that allows users (such as medical professionals) to visually compare the information and make informed decisions about which potential donors, if any, are good or best candidates to be recipients.

[0037] Figure 1 The document includes a flowchart illustrating operations included in Example Process 10, which is used to obtain a dataset from multiple sources and to store the dataset in a manner that enables the generation of a UI of the type described herein.

[0038] Process 10 may be performed on a medical diagnostic system, a general-purpose computing system exemplified herein, or a combination of a medical diagnostic system and a general-purpose computing system, or using a medical diagnostic system, a general-purpose computing system exemplified herein, or a combination of a medical diagnostic system and a general-purpose computing system, any or all of which may be referred to herein as a "system". Figure 1In this example, system 12 includes one or more processing devices 14 (e.g., one or more microprocessors) and a memory 15 for storing machine-executable instructions 16 that can be executed by the processing devices 14 to perform process 10. Computer memory (e.g., permanent storage such as one or more hard disk drives) stores a database 17 containing recipient and donor information as described herein. System 12 also includes one or more display devices 19 for displaying a UI generated by process 10 and other information.

[0039] Process 10 includes obtaining (10a) information about the recipient of the graft and information about one or more potential donors of the graft to the recipient. This information may include the recipient's HLA (human leukocyte antigen) typing and the HLA typing of each potential donor. HLA comprises gene complexes encoding cell surface proteins that regulate the human immune system. Each person's HLA typing includes HLA MHC (major histocompatibility complex) class I (A, B, C) genes and HLA MHC class II (e.g., DR, DQ, DP) genes.

[0040] HLA genes are polymorphic, meaning they can have different alleles. Alleles are variations of the nucleotide sequence of a gene at a specific location or locus on a deoxyribonucleic acid (DNA) molecule. Proteins encoded by HLA genes are also called antigens. Each person has a unique set of these antigens, half inherited from their father and half from their mother. The more similar the HLA genes of the recipient and the potential donor of the graft, the more similar their antigens, and the less likely the graft from the donor will be rejected by the recipient.

[0041] HLA typing of the recipient and donor can be obtained using any known HLA typing assay. Examples of such assays can be performed using systems from Werfen® SA, such as the MIA FORA. TM NGS MFlex system or LIFECODES® HLA SSO typing kit.

[0042] The HLA typing 20 generated by the assays for the recipient and potential donor can be stored in database 17 in association with the identities of the recipient and potential donor through this system. Alternatively, process 10 can receive (10a1) the HLA typing 20 from this system and store the HLA typing 20 in database 17 in association with the identities of the recipient and potential donor.

[0043] In some implementations, process 10 may obtain (10a) HLA typing by generating and displaying a UI. The UI may contain fields where the user can manually input the recipient and donor HLA typing. These manually input HLA typings may be received by process 10 (10a2) and stored in database 17 in association with the identities of the recipient and potential donor.

[0044] Procedure 10 can use the obtained HLA typing of the recipient and potential donor to obtain (10b) multiple datasets 21 and store the datasets 21 in database 17, as described below. Each dataset may include indicators based on the compatibility of the potential donor and recipient. Indicators may be or include any markers, shadings, colorings, values, scores, text, icons, pictures, symbols, or other indicators that can be used to express the compatibility of the potential donor and recipient.

[0045] Process 10 can obtain multiple datasets from multiple different sources. Different sources may include one or more local sources and / or one or more remote sources that are different from the local sources. Figure 2 A system 12 is shown that obtains datasets from multiple sources 22, including remote sources 22a, 22b, 22c and a local source 22d. Although four sources are shown in this example, one, two, three, five, six, seven or more sources may be present. In these examples, HLA typing 23 (which includes HLA typing 20 for graft recipients and potential donors) is sent to the sources, and the sources respond by sending corresponding datasets 24a to 24d (which may be part of dataset 21), as described below. In some embodiments, in the case of local sources, the local source may receive HLA typing from the system performing the determination, generate a dataset, and send the dataset to process 10 without first being prompted to do so by process 10.

[0046] A local source may include the same entity or system operating or under its control that performs the assay to obtain HLA typing. A local source may generate (10b1) datasets locally. For example, a local source may perform one or more processes to compare the recipient's alleles with those of a potential donor and generate one or more indicators based on the comparison. Indicators may be any indicators described herein, such as shading, color, crosshairs, or values, that are based on and indicate differences between the alleles of the potential donor and recipient, and thus indicate the compatibility of the potential donor with the recipient of the graft.

[0047] Comparisons can be based on allele names or nomenclature. As explained in "https: / / hla.alleles.org / nomenclature / naming.html" (accessed August 12, 2024), "Each HLA allele name has a unique number corresponding to up to four sets of numbers separated by colons. The length of the allele name depends on the sequence of the allele and the sequence of its closest relative. All alleles accept names of at least four digits, corresponding to the first two sets of numbers, with longer names assigned only when necessary. The numbers before the first colon describe the type, which usually corresponds to the serological antigen carried by the allele. The next set of numbers is used to list the subtype, with the numbers determining the order of the DNA sequence. The numbers of the different alleles in the two sets of numbers..." Genes must differ in one or more nucleotide substitutions that alter the amino acid sequence of the protein they encode. Alleles that differ only by synonymous nucleotide substitutions within the coding sequence (also known as silencing or non-coding substitutions) are distinguished by a third set of numbers. Alleles that differ only in sequence polymorphisms within introns or in the 5' or 3' untranslated regions of flanking exons and introns are distinguished by a fourth set of numbers. In addition to a unique allele number, an optional suffix may be added to an allele to indicate its expression status. Alleles that have been shown not to be expressed—'invalid' alleles—have been assigned the suffix 'N'. Alleles that have been shown to be expressed alternatively may have the suffixes 'L', 'S', 'C', 'A', or 'Q'.

[0048] In one example, process 10 may determine, based on allele-specific comparisons, which alleles of each potential donor at each locus are compatible with the corresponding alleles of the recipient at the same locus. Process 10 may store (10c) a dataset containing indicators in database 17, which convey information about whether each allele is compatible with the corresponding allele of the recipient at the same locus. For example, for compatible alleles, process 10 may store a marker associated with the allele. The marker may specify how the allele is represented on the UI in a certain way, for example, as a bold, horizontally cross-hatched, or shaded in a certain color (e.g., green), to indicate that the alleles are compatible. For example, for incompatible alleles, process 10 may also store a marker associated with the allele. The marker may specify how the allele is represented on the UI in a certain way, for example, as a non-bold, vertically cross-hatched, or shaded in a certain color (e.g., red), to indicate that the alleles are incompatible. The red / green or other shaded difference is based on a comparison of the donor's HLA typing with the recipient's HLA typing. In the example, if there is a match between the alleles in the donor and recipient HLA typing, the donor typing is highlighted in green or represented in the first manner (e.g., a horizontal shading line). In the example, if there is no match between the alleles in the donor and recipient HLA typing, the donor is highlighted in red or shaded in a different manner than the first manner (e.g., a vertical shading line).

[0049] In some implementations, only a portion of the allele can be displayed in the donor column. This is based on the resolution at which the donor is genotyped. A*01:01 would be a genotype with a lower resolution than A*01:01:02 or A*01:01:02:03. The UI allows for both numerical alleles (A*01:01) and higher resolutions. Regarding cross-matching alleles, if there is a resolution mismatch between the donor and recipient—for example, the donor allele is displayed at a lower resolution than the recipient allele—the process can cross-match to the lowest resolution. Thus, for example, A*01:01 with the donor's A*01:01:02:03 would be marked as a match because A*01:01 includes all higher resolutions.

[0050] Database 17 can store dataset 21 (10c) in multiple tables. In some implementations, each table includes the identities of the recipient and donor, information for obtaining the dataset (such as HLA typing of the recipient and donor), and information obtained for the dataset. For example, information obtained for the dataset may include indicators of the compatibility of the donor as a whole with the recipient or the compatibility of different traits of the donor and recipient (such as compatibility of individual alleles, T cells, or B cells). In some implementations, the information may include markers associated with each donor's allele, such as the markers described above, to shade or color each allele based on compatibility with the corresponding allele of the recipient. In some implementations, the markers may indicate how much shading or what type of coloring is applied to each indicator. In some implementations, this information may identify biological characteristics of mismatched recipients and donors, such as alleles and / or eplets.

[0051] Remote sources may include entities or systems that are not operated by or under the control of the same entity or system that generated the HLA typing. In order to obtain a dataset from a remote source, process 10 may provide information such as the HLA typing of the recipient and potential donor to each remote source.

[0052] In the example, to obtain a dataset from a remote source, process 10 can generate a window containing fields to populate the HLA typing, and, if necessary, generate additional information to provide to the remote source for obtaining the dataset. For example, refer to... Figure 3 Process 10 can generate and display a window 25 to the user of a pre-specified receptor 26 (#1601).

[0053] Window 25 contains fields where the user or system 12 can input information about the recipient or the recipient and potential donor. These fields include an HLA typing field 27 to provide the HLA typing of the recipient or the recipient and potential donor. In this example, the recipient's HLA typing can be populated based on the recipient's identity (here, #160126). In some implementations, system 12 automatically—e.g., without user prompts or input—retrieves the recipient's HLA typing from database 17 and populates the recipient's HLA typing field 17 with that information. Drop-down menus (e.g., 33) for the HLA typing fields contain any ambiguities at the loci. The user can open the drop-down menu and select different HLA pairs. These ambiguities are part of the patient typing process. The user can select the pair they wish to use to determine compatibility between the recipient and donor.

[0054] System 12 can populate the donor's HLA typing field in response to the identity of a specified donor. For example, field 29 includes a dropdown list containing a list of potential donors for the recipient. An example donor here is referred to as "sample 22". In some embodiments, the list of potential donors may include only those previously determined to be incompatible with the recipient or having a compatibility level greater than a predetermined threshold. This can be determined based on, for example, allele comparison or other processes performed locally to determine compatibility. In some embodiments, the list of potential donors may include all potential donors whose HLA typing is stored in database 17. The user or system 12 can select a potential donor from the dropdown list. In response to this selection, system 12 can automatically retrieve the HLA typing of the selected donor from database 17 and populate the donor's HLA typing field 17 with that information. As described above, the user can open the dropdown menu and select different HLA pairs for the donor.

[0055] In some implementations, window 25 may include fields that allow the user or system 12 to specify the type of graft 28 (such as stem cells or solid organs) and the population 30 or haplotype of the recipient and donor.

[0056] Users can instruct system 12 to provide information from window 25 to one or more sources by selecting a button or prompt 31. Alternatively, the system can automatically send the information once all necessary fields are filled. Information from window 25 can be sent electronically to a remote source via one or more computer networks.

[0057] In some implementations, the same window can be used or the same window can be used. Figure 3 The different windows or other types of UI shown send the same information multiple times to multiple different remote sources. Each source can be or include one or more third-party services that receive HLA typing of recipients and potential donors and provide a dataset containing indicators based on the HLA typing that convey the compatibility between the recipient and donor of the graft.

[0058] Return to reference Figure 1 Process 10 receives (10b2) a dataset from the source in response to providing the source with HLA typing and (if necessary) other information (such as the graft type and population information described above). The dataset received from the source includes compatibility indicators based on factors that can be determined from HLA typing and / or other information provided, such as the compatibility of the donor's thymic (T) cells with the recipient's T cells, the compatibility of the donor's cystic (B) cells with the recipient's B cells, or misaligned peptides between the recipient's HLA typing and the donor's HLA typing.

[0059] In some implementations, process 10 receives (10b2) multiple datasets based on different factors from multiple different sources. For example, process 10 may receive (10b2) a first dataset from a first source, which includes indicators of compatibility between donor and recipient T cells; a second dataset from a second source, which includes indicators of compatibility between donor and recipient B cells; and a third dataset from a third source, which includes indicators of compatibility between misaligned peptides based on HLA typing of the recipient and donor. In this example, the first, second, and third sources are different from each other, and the first, second, and third datasets are also different from each other. For example, the datasets may contain different information, such as different compatibility indicators.

[0060] In some implementations, process 10 receives (10b2) multiple datasets based on the same factors from multiple different sources. For example, process 10 may receive (10b2) a first dataset including indicators of compatibility between donor and recipient B cells from a first source, a second dataset including indicators of B cell compatibility from a second source, and a third dataset including indicators of B cell compatibility from a third source. In this example, the first, second, and third sources are different from each other, and the first, second, and third datasets are also different from each other. For example, the datasets may contain different information, such as different indicators of compatibility.

[0061] Process 10 may receive (10b2) any combination of the aforementioned dataset and datasets based on factors not listed herein. Process 10 may obtain datasets from any number of sources. For example, process 10 may obtain datasets from two remote sources, three remote sources, four remote sources, five remote sources, etc.

[0062] Process 10 stores (10c) the datasets 21 received from each remote source in database 17, allowing retrieval of the data from the datasets at a later time. As described above with respect to local sources, the database may contain multiple tables. In some embodiments, each table includes the identities of the recipient and donor, information sent to the remote source, such as the HLA typing of the recipient and donor, and in some cases, the population and graft type, as well as information received from the remote source. As mentioned above, the information received from the remote source may include information about the compatibility of the donor as a whole with the recipient or the compatibility of different traits between the donor and recipient, such as compatibility based on individual alleles, T cells, or B cells. In the example, the information may include tags, such as those described above.

[0063] Data sets from local and remote sources are linked in database 17 via tables. For example, the tables include the identities of donors and recipients, as well as their HLA typing. In some implementations, this information is public to all tables and can be used by system 12 to access and retrieve information from any tables required to generate the UI described herein.

[0064] exist Figure 1 In operation 10d, process 10 generates data for the UI based on one or more datasets 21 stored in database 17. To generate the UI data, process 10 requests and receives the identities of the recipient and potential donors. The identities of the recipient and potential donors can be entered by the user into system 12 via the UI (not shown). In some embodiments, system 12 may allow the user to select any potential donor whose HLA typing is stored in database 17. In some embodiments, the system may allow the user to select only those donors previously determined to be incompatible with the recipient or having a compatibility level greater than a predetermined threshold. This can be determined, for example, based on the comparison of alleles described above.

[0065] Figure 4 An example of UI 40 that can be generated (10d) according to process 10 is shown. In this example, UI 40 is a table (10d1) that includes information and metrics from a locally generated dataset and datasets received from two remote sources. The information for generating UI 40 is stored in database 17 as described above and retrieved from the database to generate the UI.

[0066] UI 40 includes information about receptor 41 in columns 42 and 43. The information includes the receptor's locus (serotype or serotype / serology) 45 and alleles 46, with each locus and its allele in the same row.

[0067] UI 40 includes information 47 about each potential donor. In this example, the source SOURCE1 52 “●” and SOURCE2 56 “■” for each potential donor are the same. In some implementations, the source may be different for different donors; for example, if a source does not provide information to a donor, information from that source may be missing from UI 40. In this example, the information type is the same for each donor, although the content of the information differs for different donors. Therefore, the information for donor 49 is described primarily.

[0068] UI 40 includes information 50 from a local source, information 51 from a first remote source 52 (SOURCE1), and information 55 from a second remote source 56 (SOURCE2). The first remote source is different from the second remote source. The information from all three sources includes indicators of donor-recipient compatibility based on different factors and expressed in different ways.

[0069] In this example, information 50 from the local source includes the alleles of the potential donor at locus 45 specified for the recipient. Thus, for example, allele 59 is located at locus 60 in the potential donor, and allele 61 is located at the same locus 60 in the recipient. In this example, allele 59 is shaded (e.g., red or a vertical shading line) to indicate that allele 59 is different from allele 61. In another example, allele 62 is shaded (e.g., green or a horizontal shading line) to indicate that allele 62 is the same as allele 64. The presence of identical alleles in the recipient and donor is an indicator of compatibility, while different alleles in the recipient and donor are indicators of incompatibility.

[0070] In this example, information 51 from remote source 52 includes an indicator of donor and recipient T cell compatibility. In this example, the indicator includes values, where value 66 is assigned to each antigen (combined allele), and where a composite value 70 is assigned to the donor. In this example, composite value 70 is the sum of the individual antigen values ​​"30", "31", and "6". Figure 4 In the example, donor 49 has a composite value of "67" and donor 72 has a composite value of "98". This means that, for the graft under consideration, in the context of T cell compatibility, donor 49 is more compatible with recipient 41 than donor 72 because the composite value of donor 49 is lower than that of donor 72. Similar relationships exist for individual antigen values. For example, antigen 75 is more compatible with the corresponding recipient antigen than antigen 76.

[0071] In this example, the indicators also include shading associated with each antigen. For example, in the context of T-cell compatibility, a darker shading indicates greater compatibility than a lighter shading. In the example of donor 72, antigen 78 is represented by the darkest shading, indicating that antigen 78 has relatively good compatibility with the receptor in the context of T-cell compatibility. Antigen 79 is represented by the lightest shading, indicating that antigen 79 has relatively poor compatibility with the receptor, at least compared to the other listed antigens, in the context of T-cell compatibility. Antigen 80 has a certain amount of shading between antigens 78 and 79, which, in the context of T-cell compatibility, means that antigen 80 has better compatibility with the receptor than antigen 79, but less compatibility than antigen 78 with the receptor.

[0072] In this example, information 55 from remote source 56 includes an indicator of B cell compatibility based on the donor and recipient. In this example, the indicator includes values ​​82 based on the recipient and donor loci or serotypes, and a composite value 84 assigned to the donor. In this example, the composite value is the sum of the individual values ​​82; however, other implementations can generate composite values ​​through other combinations of allele values. The composite value could be the number of epilet mismatches in the recipient and donor B cells. Figure 4 In the example, donor 49 has a composite value of "36", which is the sum of the values ​​"30", "4" and "2" shown in the column. Generally, lower values ​​indicate greater compatibility, while higher values ​​indicate less compatibility.

[0073] In some implementations, process 10 may generate composite values ​​locally. In some implementations, composite values ​​may be part of a dataset transmitted from a local or remote source. In some implementations, process 10 may combine metrics, such as values ​​from different sources, to generate additional metrics and present those metrics at a location in the UI.

[0074] Figure 5 Another example of a UI 90 that can be generated according to process 10 is shown. In this example, UI 90 is a table (10d1) that includes information and metrics from a locally generated dataset and datasets received from two remote sources. The information for generating UI 90 is stored in database 17 as described above and retrieved from the database to generate the UI.

[0075] UI 90 includes information about receptor 92 in columns 91 and 93. This information includes the receptor's loci (serotype or serotype / serology) and alleles, with each locus and its allele in the same row. This information can be obtained in operation 10a using the techniques described herein. UI 90 is similar to UI 40 because columns 91 and 93 provide information similar to... Figure 4 Columns 42 and 43 contain the same type of information about the receptor.

[0076] UI 90 includes information about each potential donor (DONOR1, DONOR2). The information sources (SOURCE 1 and SOURCE 2) for each potential donor are the same as those for UI 40. Furthermore, the information type is the same for each donor, although the content of the information differs between donors. Therefore, only information about donor 95 (DONOR1) is described.

[0077] In this example, information 96 from the local source includes the alleles of potential donors at the locus specified for the recipient. This information can be of the same type as the information described about UI 40 and presented in the same manner as the information described about UI 40.

[0078] In this example, the information 98 from remote source 52 includes indicators of donor and recipient T cell compatibility. In this example, the indicators include antigen values, where values ​​101 are assigned to each antigen (combined alleles). In this example, the values ​​include composite values ​​102 assigned to the donor, which may be based on a combination of allele and / or antigen values ​​as described with respect to UI 40. As in the cases above, the lower the value in this example, the greater the likelihood of donor-recipient compatibility. That is, a lower value indicates greater compatibility with its counterpart on the receptor.

[0079] The indicators also include shades associated with each allele and each antigen. In this example, the shades have the same meaning as described for UI 40. That is, a darker shade indicates greater compatibility than a lighter shade.

[0080] In this example, information 104 from remote source 56 includes an indicator of compatibility between donor and recipient B cells. In this example, the indicator includes values ​​106 based on the recipient and donor loci or serotypes, and a composite value 108 is assigned to the donor. In this example, the composite value is the sum of the individual values ​​106; however, other embodiments may generate composite values ​​through other combinations of allele values. The composite value may be the number of eplet mismatches in the recipient and donor B cells. Generally, lower values ​​indicate greater compatibility, while higher values ​​indicate less compatibility.

[0081] UI 90 also includes arrow 109, which can be selected by the user to expand column 107 to display column 110. For combinations of alleles, column 110 lists eplets 113 that are mismatched between donor and recipient B cells.

[0082] In some implementations, UI 90 can rank donors based on compatibility with the recipient. The ranking can be displayed as a list in region 111 of UI 90, where the top donor is the most compatible with the recipient, and the next lower-listed donors are less compatible. Process 10 can determine the ranking by evaluating metrics provided by each source for each donor. The donor with the fewest negative compatibility metrics can be ranked highest—that is, the most compatible with the recipient of the graft. Lower-ranked donors—i.e., those on the lower end of the list—have progressively increasing negative compatibility metrics with the recipient.

[0083] Return to reference Figure 1Process 10 outputs data (10e) to a display device (such as display device 19) to display the UI. Medical professionals can view the UI and, if necessary, scroll through it to make decisions about which potential donors (if any) are good candidates. Having all the information in a single location (as described in this document) can be advantageous because it reduces the need for medical professionals to navigate different UIs and access different sources for information. Furthermore, the UI described herein integrates information from different sources and delivers information in a manner that allows for easy comparison of information from different sources.

[0084] refer to Figure 1 and Figure 3 In some implementations, system 12 can provide a source containing only receptor HLA typing 112 (i.e., no donor HLA typing) and a population containing receptors (e.g., haplotypes). In the case of having this information but no donor HLA typing, the source returns a dataset containing information about the population. This information can be used to generate (10d2, Figure 1 Box plot.

[0085] A box plot represents a range of indices—in this example, values—on the population source based on the compatibility of population members with the recipient of the graft. In this example, lower values ​​indicate a higher level of compatibility. These values ​​can be composite values ​​generated from random members of the population as the source. Examples of such composite values ​​will be described in conjunction with UI 40 and 90.

[0086] refer to Figure 6 The box plot 114, in this example, includes a range of the mean 116, "102". Value 116 is the mean value of the compatibility between members of the population and the recipient of the graft. This range includes a first percentage, for example, the first quartile 120. Value 120 ("85") indicates that 25% of the population has greater compatibility with the recipient of the graft. This range includes a second percentage, for example, the third quartile 121 ("117"). Value 121 indicates that 75% of the population has greater compatibility with the recipient of the graft. This range also includes third and fourth percentage values ​​122 and 123, respectively, indicating that 5% and 95% of the population have greater compatibility with the recipient of the graft. In some embodiments, the third 122 and fourth 123 values ​​are not shown on the box plot but are represented graphically by lines.

[0087] To generate (10d2) data for a UI containing a boxplot, in this example, process 10 retrieves indices from database 17 from the same source that provided the data for generating the boxplot. In this example, process 10 accesses database 17 to obtain composite values ​​(indicators) for potential donors. As described herein, composite values ​​for potential donors can be based on the compatibility of multiple potential donors with the graft recipient. In some embodiments, the system may allow access to composite values ​​for any potential donor whose HLA typing is stored in the database. In some embodiments, the system may allow composite values ​​to be obtained only for those donors previously determined to be incompatible with the recipient or having a compatibility level greater than a predetermined threshold. This can be determined, for example, based on the comparison of alleles described above.

[0088] Method 10 overlays the composite values ​​of potential donors at appropriate locations on the box plot. For example, as... Figure 6 As shown, donor 49 ( Figure 4 The value "67" of donor 123 covers the first quartile 120; the value "91" of donor 123 covers the first quartile 120 and the mean 116; and donor 72 ( Figure 4 The value "98" falls between the first quartile (120) and the mean (116), but is higher than the value of donor 123. The resulting graph shows that donor 49 has the lowest value among potential donors, "67," and is therefore the best candidate for graft among potential donors. Furthermore, since less than 25% of the population may have a better value than donor 49, donor 49 is a good candidate for graft within the population.

[0089] In some implementations, process 10 may generate graphs other than box plots, such as histograms, violin plots, bar plots, scatter plots, line plots, or pie plots, which correlate the values ​​of potential donors with a population to show which potential donor is the best candidate for transplantation into the recipient.

[0090] refer to Figure 1 and 7 In some implementations, the dataset returned by a source (e.g., a local source) may include MFI (mean fluorescence intensity) values. MFI values ​​are based on the recipient's antigen and indicate rejection of the graft from a potential donor. For example, the assay may contain beads, each containing an antigen. When a sample from the recipient (e.g., blood) comes into contact with the beads, the beads fluoresce if the blood has antibodies against the antigen. Greater fluorescence indicates a stronger reaction between the sample and the antigen. The MFI value reflects the intensity of the reaction for each antigen / bead. A higher MFI value indicates lower compatibility between the recipient and a donor possessing that antigen.

[0091] Process 10 can generate (10d3, Figure 1This data is used for a single graph (e.g., a bar chart) that combines MFI values ​​with compatibility indicators from one or more other sources. For example, process 10 combines allele or antigen values ​​from one source (e.g., a remote source) to... Figure 4 The value 66 or Figure 5 The value 101) is combined with MFI values ​​from different sources (e.g., local sources). Figure 7 In the bar chart, axis 130 corresponds to the antigen. Axis 131 lists the MFI values, where the length of the bars indicates the magnitude of the MFI value. MFI values ​​exceeding a predetermined threshold can be displayed as shaded, colored (e.g., pink), or cross-hatched lines, unlike MFI values ​​below the threshold, which are displayed as shaded, colored (e.g., green), or cross-hatched lines, to identify which MFI values ​​are incompatible with donor-to-recipient transplantation and which are compatible. Bar 150 represents positive antigens (MFI values ​​above MFI threshold 151), and bar 152 represents negative antigens (MFI values ​​below the MFI threshold). In this example, the MFI threshold may be set to 750.

[0092] Process 10 combines allele / antigen values, for example Figure 5 The value 101 can originate from a source that is different from the source providing the MFI value or from the same source as the source providing the MFI value. In this example, axis 132 includes values ​​from a source (such as...). Figure 4 The axis 132 represents the range of values ​​from source 52, and points (such as point 142) represent the values ​​of the antigen from that source. In this example, axis 132 also includes the range of values ​​from different sources 160 (labeled SOURCE3), which correspond to the values ​​of SOURCE1. Label 164 allows the user to select which values ​​(from SOURCE1 or SOURCE3) to display.

[0093] By combining theoretical risk (the value of the source) with actual measurements of antibody binding strength (MFI), integrating source values ​​such as those mentioned above with MFI values ​​allows for a more nuanced understanding of immunogenicity risk. This combined approach not only helps in assessing risk but also in evaluating the potential impact of that risk based on the strength of antibody-antigen adhesion.

[0094] All or part of the systems and processes described in this specification, and their various modifications, can be executed or controlled, at least in part, by one or more computer programs tangibly embodied in one or more information carriers (such as one or more non-transitory machine-readable storage media), via one or more computers (such as System 12). The computer program can be written in any programming language, including compiled or interpreted languages, and can be deployed in any form, including as a standalone program or as a module, part, subroutine, or other unit suitable for use in a computing environment. The computer program can be deployed to execute on one computer, at one site, or distributed across multiple sites and interconnected via a network.

[0095] Actions associated with performing the processes or control test systems described herein may be performed by one or more programmable processors executing one or more computer programs to control or perform all or some of the operations described herein. All or part of the test systems and processes may be performed or controlled by dedicated logic circuitry, such as FPGAs (Field Programmable Gate Arrays) and / or ASICs (Application-Specific Integrated Circuits) or embedded microprocessors located in the instrument hardware.

[0096] Processors suitable for executing computer programs include, for example, both general-purpose microprocessors and special-purpose microprocessors, as well as any one or more processors in any type of digital computer. Typically, a processor receives instructions and data from read-only memory or random access memory, or both. The components of a computer include one or more processors for executing instructions and one or more memory area devices for storing instructions and data. Typically, a computer will also include one or more machine-readable storage media, or be operatively coupled to receive data from or transfer data to one or more machine-readable storage media, such as mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks. Non-transitory machine-readable storage media suitable for embodying computer program instructions and data include all forms of non-volatile memory areas, including, for example, semiconductor memory area devices such as EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), and flash memory memory area devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and CD-ROM (Optical Disc Read-Only Memory) and DVD-ROM (Digital Versatile Optical Disc Read-Only Memory).

[0097] As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having,” “contains,” “containing,” and any variations thereof are intended to cover non-exclusive inclusion, such that a system, technology, apparatus, structure, process, or other subject matter that includes, has, or contains elements or a list of elements described or claimed herein includes not only those elements but may also include other elements not expressly listed or inherent to such systems, technologies, apparatus, structures, processes, or other subject matter described or claimed herein.

[0098] All examples described in this article are non-restrictive.

[0099] In the description and claims provided herein, unless the context otherwise requires, the adjectives “first,” “second,” “third,” etc., do not specify priority or order. Rather, these adjectives may be used simply to distinguish the nouns they modify.

[0100] Elements from the different embodiments described can be combined to form other embodiments not previously specifically described. Elements can be excluded from the previously described system without adversely affecting their operation or the operation of the system in general. Furthermore, various individual elements can be combined into one or more individual elements to perform the functions described in this specification.

[0101] Other embodiments not specifically described in this specification are also within the scope of the appended claims.

Claims

1. A method performed by one or more processing devices, the method comprising: Obtain information about the recipient of the graft and potential donors of the graft, including the HLA (human leukocyte antigen) typing of the recipient and the HLA typing of the potential donor; Based on the information, multiple datasets are obtained, each dataset containing indicators of compatibility between the potential donor and the recipient of the graft; Store the multiple datasets in a database; Generate data for the user interface (UI), the data containing representations of metrics from one of the plurality of datasets in the database; and The data is output for display on a display device.

2. The method of claim 1, wherein the index is based on the compatibility of the donor's thymic (T) cells with the recipient's T cells.

3. The method of claim 1, wherein the index is based on the compatibility of the donor's mucosal sac (B) cells with the recipient's B cells.

4. The method of claim 1, wherein the index is based on peptides that are misaligned between the HLA typing of the receptor and the HLA typing of the donor.

5. The method of claim 1, wherein the dataset comes from different sources, the different sources including local sources and remote sources, the local source including an entity from which the information is obtained, and the remote source being different from the entity from which the patent information is obtained.

6. The method of claim 1, wherein obtaining the information comprises receiving the results of HLA typing of biological samples from the receptor and the potential donor.

7. The method of claim 1, wherein the UI comprises a table containing columns for the recipient and columns for the potential donor, the recipient columns containing a first column containing a locus and a second column containing alleles of the recipient at corresponding loci in the first column, and the potential donor columns containing a third column containing alleles of the potential donor at corresponding loci in the first column and one or more additional columns containing indicators based on one or more of the compatibility of the donor's thymic (T) cells with the recipient's T cells or the compatibility of the donor's mucous sac (B) cells with the recipient's B cells.

8. The method of claim 7, wherein the one or more additional indicators are located in rows corresponding to loci and alleles of the receptor or in rows corresponding to one or more serotype groups of the receptor.

9. The method of claim 1, wherein the index comprises a value representing the compatibility of the potential donor and recipient of the graft; and The UI includes: A box plot including the recipient population, the box plot representing a range of values ​​for the population based on the compatibility of the population members with the recipient of the graft; and The values ​​of multiple potential donors are overlaid on the box plot, and the values ​​of the multiple potential donors are based on the compatibility of the multiple potential donors with the recipient of the graft.

10. The method of claim 1, wherein the plurality of datasets comprises MFI (mean fluorescence intensity) values, the MFI values ​​being based on antigens of the receptor indicating rejection of the graft from the potential donor.

11. The method of claim 10, wherein the data of the UI comprises a bar chart containing the MFI value associated with the antigen of the receptor.

12. The method of claim 11, wherein the bar graph comprises a first axis of the MFI values ​​and indices and a second axis corresponding to an antigen of the recipient, the antigen of the recipient indicating rejection of a graft from the potential donor.

13. The method of claim 1, wherein, The UI comprises a single window that displays all the metrics or is configured to scroll to reach all the metrics.

14. The method of claim 1, wherein storing the plurality of datasets in the database comprises storing each dataset in a table, each of the tables including public information, the public information including the identity of the recipient, the identity of the potential donor, the HLA typing of the recipient, and the HLA typing of the potential donor.

15. One or more non-transitory machine-readable storage devices, said one or more non-transitory machine-readable storage devices storing instructions executable by one or more processing devices to perform operations, said operations including: Obtain information about the recipient of the graft and potential donors of the graft, including the HLA (human leukocyte antigen) typing of the recipient and the HLA typing of the potential donor; Based on the information, multiple datasets are obtained, each dataset containing indicators of compatibility between the potential donor and the recipient of the graft; Store the multiple datasets in a database; Generate data for a user interface (UI), the data containing representations of metrics from one of the plurality of datasets in the database; and The data is output for display on a display device.

16. The one or more non-transitory machine-readable storage devices of claim 15, wherein storing the plurality of datasets in the database comprises storing each dataset in a table, each of the tables including public information, the public information including the identity of the recipient, the identity of the potential donor, the HLA typing of the recipient, and the HLA typing of the potential donor.

17. One or more non-transitory machine-readable storage devices of claim 15, wherein the UI comprises a table including columns for the recipient and columns for the potential donor, the recipient column including a first column containing a locus and a second column containing an allele of the recipient at a corresponding locus in the first column, and the potential donor column including a third column containing an allele of the potential donor at a corresponding locus in the first column and one or more additional columns containing indicators based on one or more of the compatibility of thymic (T) cells in the donor with T cells in the recipient or the compatibility of mucosal sac (B) cells in the donor with B cells in the recipient.

18. One or more non-transitory machine-readable storage devices as claimed in claim 15, wherein the index comprises a value representing the compatibility of the potential donor with the recipient of the graft; and The UI includes: A box plot including the recipient population, the box plot representing a range of values ​​for the population based on the compatibility of the population members with the recipient of the graft; and The values ​​of multiple potential donors are overlaid on the box plot, and the values ​​of the multiple potential donors are based on the compatibility of the multiple potential donors with the recipient of the graft.

19. One or more non-transitory machine-readable storage devices of claim 15, wherein the plurality of datasets contains MFI (mean fluorescence intensity) values, the MFI values ​​being based on antigens of the receptor indicating rejection of grafts from the potential donor.

20. The one or more non-transitory machine-readable storage devices of claim 19, wherein the data of the UI comprises a bar graph containing MFI values ​​associated with the antigen of the receptor.

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