WO2016100638A1 - Système mis en œuvre par ordinateur et procédé permettant d'identifier des patients similaires - Google Patents

Système mis en œuvre par ordinateur et procédé permettant d'identifier des patients similaires Download PDF

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Publication number
WO2016100638A1
WO2016100638A1 PCT/US2015/066325 US2015066325W WO2016100638A1 WO 2016100638 A1 WO2016100638 A1 WO 2016100638A1 US 2015066325 W US2015066325 W US 2015066325W WO 2016100638 A1 WO2016100638 A1 WO 2016100638A1
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WIPO (PCT)
Prior art keywords
information
patient
data
patients
alteration
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PCT/US2015/066325
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English (en)
Inventor
Gaurav Singal
Mary Pat LANCELOTTA
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Foundation Medicine, Inc.
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Application filed by Foundation Medicine, Inc. filed Critical Foundation Medicine, Inc.
Priority to EP15871055.8A priority Critical patent/EP3234841A4/fr
Priority to CA2970931A priority patent/CA2970931C/fr
Priority to AU2015364605A priority patent/AU2015364605B2/en
Publication of WO2016100638A1 publication Critical patent/WO2016100638A1/fr
Priority to HK18104572.8A priority patent/HK1245444A1/zh
Priority to AU2021202244A priority patent/AU2021202244B2/en

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G16B50/10—Ontologies; Annotations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Definitions

  • a system may be provided that permits the user to locate similar patients using genomic information related to a patient's cancer. For instance, information relating to genetic alterations and the patient's tumor type may be used to identify similar patients within a database. Preferably, such information may be used to locate similar patients where treatment was successful or had some other positive outcome.
  • curated information is provided on the system to enable physicians to make informed decisions regarding the implications of the presence of specific genomic alterations.
  • Curated information includes interpretations of available information (e.g., existing therapies, clinical trials, journals, and publications) for genomic alterations that may be found in a patient's tumor as a result of the genomic analysis.
  • the genomic analysis can identify, for example, a tumor type, an affected gene, and an alteration type specific to a given patient and their cancer.
  • the available information that can be curated can be associated with, and organized by, any of the information provided in the genomic analysis (e.g., specific to tumor type, gene, and alteration). Such information may be stored in a database and accessed by physicians though one or more user interfaces.
  • the communication permits patients to be matched and identified without revealing their identities to other physician users.
  • physicians are provided a facility for communicating between physicians while not revealing contact information such that the identification of physicians with matching patients is kept confidential. Both the initial communication and responses to the inquiry may be stored within the database and associated with the particular patient and/or cancer type. After a particular communication between physicians occurs, this information may be stored in the database and accessed for future use (e.g., by another physician searching for a similar patient having a similar cancer). By providing such communication capabilities, a physician or other health care provider may more easily locate the best treatment information in a timely manner.
  • a communication system that allows physician users to discuss cases in a semi-structured manner. For instance, some questions are provided in a structured format where discrete responses are provided (e.g., best response, duration, etc.). Some questions are unstructured that permit other physician users to convey a larger clinical narrative (e.g., via any additional comments field, via questions such as "Why was the patient not treated with a therapy?” among others).
  • responses may be aggregated from among physician providers and reused by the system.
  • structured data responses from multiple providers may be aggregated and provided to a physician user within an interface.
  • such information may be presented to a physician user within a matrix of results. Such information may include, for example, de-identified information regarding similar patients identified through a matching process. The presented information may also include genomic information as well as the response information collected from other physician users.
  • patient context information may be used to perform a matching process for identifying similar patients.
  • patient context information includes information that describes a state of a particular patient with respect to his/her disease state, along with the generic state of the disease.
  • patient context information may include disease phenotype and genetic alterations.
  • disease subtypes can be arranged in disease groups depending on the clinical and functional similarity of the diseases. Such disease subtypes (e.g., tumor types) can be grouped according to expert information, creating disease ontology groups (DOGs). In a similar manner, alterations may be grouped into alteration groups that are functionally similar.
  • DOGs disease ontology groups
  • DOGs Disease ontology groups
  • AGs alteration groups
  • similar patients may be defined as those having the same disease type (or another disease type in the same DOG) and having an alteration that falls within the same alteration group (AG).
  • treatment data may be very sparse, such that an exact match based on a specific information may not yield any result.
  • diseases may be clinically similar such that patients and their outcome data for similar diseases may be grouped or pooled together, such that a search result may be determined.
  • alteration data can be generalized and therefore patient data and associated outcome data may be grouped together for the purpose of performing a similarity search.
  • a physician may be permitted (e.g., via a communication tool presented within a user interface) to contact another physician who treated or is treating the identified similar patient.
  • patient data is anonymized and only the physician contact information is provided, if offered by the responding physician.
  • the communication facility may be capable of indicating to the responding physician which similar patient triggered the communication so that the responding physician may respond appropriately.
  • the physician may be contacted by the computer system to request information about how they treated those patients and/or to share their experiences. As these physicians respond to these requests, the requests and associated responses may be stored within a database. This database of communications between physicians may be used for future treatment information that can be presented to other physicians responsive to future queries (e.g., other patient matching instances).
  • the physician has entered a response more than a predetermined amount of time, is appreciated that the patient's treatment course may have changed, and the physician may be prompted to provide updated information.
  • Other embodiments of the present invention relate to the interface used to communicate with physicians and to encourage their engagement with other physicians and the system.
  • a distributed computer system comprising a database including patient-specific pathology information relating to a plurality of patients including at least one current patient, an interface for a practitioner that provides treatment for the at least one current patient, and a matching component adapted to identify a similar patient among the plurality of patients based on a similarity between the patient-specific pathology information and patient- specific pathology information of the similar patient.
  • the patient-specific pathology information relating to the patient includes at least one of a group comprising disease phenotype information and genetic alteration information.
  • the disease phenotype information is arranged into one or more disease ontology groups, and wherein the matching component is adapted to locate the similar patient based on the one or more disease ontology groups.
  • the genetic alteration information is arranged into one or more alteration groups, and wherein the matching component is adapted to locate the similar patient based on the one or more alteration groups.
  • the interface for a practitioner is adapted to display an indication to the practitioner that the similar patient is identified.
  • the communication component includes an interface that accepts structured data from at least one of the other practitioners. In another embodiment, the communication component includes an interface that accepts response data from at least one of the other practitioners. In another embodiment, the response data includes structured and unstructured data.
  • the communication component includes an interface presents response data in a matrix of results.
  • the matrix includes de-identified information relating to the identified similar patient.
  • the matrix includes genomic data and associated response data.
  • the system includes a component that aggregates structured data among a plurality of identified similar patients and an interface that presents the aggregated structured data to the practitioner.
  • the system is adapted to collect biomarker data and is adapted to store the biomarker data in the database.
  • the database is adapted to store the patient- specific pathology information and biomarker data within a graph-based data structure.
  • the database is adapted to store information organized into a plurality of tuples of information.
  • each of the plurality of tuples of information includes at least two elements connected by a relation.
  • the system includes a component adapted to determine one or more actionable items within the graph-based data structure responsive to the biomarker data and patient- specific pathology information.
  • the plurality of tuples is organized by the system into a walkable graph representation.
  • a method comprising acts of storing, in a database, patient-specific pathology information relating to a plurality of patients including at least one current patient, presenting, to a practitioner, a computer-based interface of a distributed computer system, the practitioner providing treatment for the at least one current patient, and identifying, by the distributed computer system, a similar patient among the plurality of patients responsive to an act of determining a similarity between the patient- specific pathology information and patient- specific pathology information of the similar patient.
  • the patient- specific pathology information relating to the patient includes at least one of a group comprising disease phenotype information and genetic alteration information.
  • the disease phenotype information is arranged into one or more disease ontology groups, and wherein the matching component is adapted to locate the similar patient based on the one or more disease ontology groups.
  • the method further comprises an act of arranging genetic alteration information into one or more alteration groups, and wherein the method further comprises locating the similar patient based on the one or more alteration groups.
  • the method further comprises an act of accepting, from at least one of the other practitioners within an interface of the computer system, response data that includes structured data. In another embodiment, the method further comprises an act of accepting, from at least one of the other practitioners within an interface of the computer system, response data. In another embodiment, the response data includes structured and unstructured data. In another embodiment, the method further comprises an act of presenting, within an interface of the computer system, response data in a matrix of results. In another embodiment, the matrix includes de-identified information relating to the identified similar patient. In another embodiment, the matrix includes genomic data and associated response data.
  • FIG. 1 is a block diagram showing a system for identifying similar patients according to various aspects of the present invention
  • FIG. 3 shows an example process for creating a genomic database that may be used with various aspects of the present invention
  • FIG. 4 shows disease ontology grouping that may be performed according to one embodiment of the present invention
  • FIG. 5 shows an example process that may be performed locating similar patients using disease ontology groups according to one embodiment of the present invention
  • FIG. 9 shows yet another example system upon which various aspects of the present invention may be practiced.
  • FIG. 10 shows another system there may be used to generate data from genomic test results according to various aspects of the present invention
  • FIG. 11 illustrates one example of a user interface showing patient and treatment information according to one embodiment of the present invention
  • FIG. 12 illustrates another example of a user interface showing a connection user interface according to some embodiments of the present invention.
  • FIG. 13 illustrates yet another example of a user interface displaying a feedback view according to various aspects of the present invention.
  • genomic testing provides unique opportunities to make more informed treatment decisions, especially in the field of cancer diagnosis and therapy
  • System 100 may include one or more client systems (e.g., computer system 102A, computer system 102B) through which one or more practitioners (e.g., physician user 102A, physician user 102B) interface to the system.
  • client systems e.g., computer system 102A, computer system 102B
  • practitioners e.g., physician user 102A, physician user 102B
  • a particular physician may desire to determine treatment options for a particular patient (e.g., patient 103A).
  • system 100 may include a database of genomic information 110, including, but not limited to, alteration data including grouping information that associates related alterations.
  • Genomic information 110 may include other information, such as for example, gene information, gene associations, gene states, therapies for particular genetic states and know effects of such therapies, among other related information.
  • system 100 may include a matching engine that determines one or more similar patients as compared to a current patient being analyzed.
  • system 100 may be capable of communicating and receiving information regarding a number of patients (e.g., patients 103 A, 103B) as received from multiple sources.
  • System 100 may be adapted to communicate with other physicians (e.g., physician 101B) that treat other patients (e.g., patient 103B).
  • System 100 and its matching engine may identify other patients (e.g., patient 103B) who are similar to a current patient (e.g., patient 103A).
  • system 100 may be capable of facilitating communication between treating physicians associated with the matched patients (e.g., patient 103 A, patient 103B).
  • patient context information may be used to perform a matching process for identifying similar patients.
  • patient context information may be used to perform a matching process for identifying similar patients.
  • disease phenotype and genetic alterations may include disease phenotype and genetic alterations.
  • disease subtypes can be arranged in disease groups depending on the clinical and functional similarity of the diseases.
  • Such disease subtypes e.g., tumor types
  • DOGs disease ontology groups
  • alterations may be grouped into alteration groups that are functionally similar.
  • Disease ontology groups (DOGs) and alteration groups (AGs) can be used to locate similar patients.
  • similar patients may be defined as those having the same disease type (or another disease type in the same DOG) and having an alteration that falls within the same alteration group (AG).
  • FIG. 2 shows an example process 200 for identifying similar patients according to one embodiment of the present invention.
  • process 200 begins.
  • the patient's particular cancer is analyzed to determine one or more generic alterations present within that cancer.
  • one aspect of the invention relates to obtaining a physical sample of a patient's tumor and performing an analysis of the tumor with the objective of determining a customized treatment for that particular patient.
  • Such alteration and tumor type information may be entered into a database that includes patient information, and such information may be used to perform a matching function to determine similar patients.
  • the system may provide an indication (e.g., at block 204) of a similar patient to a user. This may be accomplished through a user interface, and may be performed automatically by the system upon the receipt of one or more signals. For instance, the system may provide the indication upon receipt of new patient information, a change in grouping information, an update of information, or any other triggering activity.
  • the system may provide a control (e.g., as in block 205) that allows the physician or other practitioner to contact another physician that is associate with the patient identified to be similar to the current patient.
  • the control may permit communication between physicians, but in one implementation, such communication may be anonymous without the need to identify a specific patient and/or physician.
  • FIG. 3 shows an example process 300 for creating a genomic database that may be used with various aspects of the present invention. Shown in FIG. 3 is an example process flow 300 for managing genomic testing information.
  • the process 300 begins at block 302 with access to genomic test results.
  • genomic test results include information specific to a patient's tumor type, one or more genes implicated by the tumor, and alteration type associated with the one or more gene.
  • the tumor type, gene, and alteration combinations for the patient's cancer are analyzed, and relevant information items are identified at 304.
  • the relevant data items can include clinical trials that match on any one or more of tumor type, gene, and alteration.
  • the relevant data items can also include therapies or references that match on tumor, gene, and/or alteration.
  • the relevant data items are stored for analysis at block 304 based on activity of curators.
  • human curators can review clinical trial information (e.g., criteria, gene/alteration target, trial therapy, trial drug) and associate that clinical trial information with tumor types, genes, and/or alterations.
  • the human curators can also review and characterize information on therapies and reference for use in, for example, process 300.
  • any relevant information item can be associated with the patient having the matching tumor type, gene, and/or alteration at 305.
  • the association(s) defined at block 305 can be used at block 306 to generate navigable data structures which can be configured to organize gene and alteration combinations and links to any associated relevant information (e.g., identified at block 304 and associated at 305).
  • the navigable data structures can be presented within a user interface display.
  • the relevant information identified at block 304 can be associated with patient records and/or specific genomic tests at block 305 based on a specified data model. Further, association of the relevant information at block 305 can include generation and storage of the associated information a data unit (e.g., information item) and the data unit can then be associated with the patient, and/or a gene or alteration in the patients genomic test results through a navigation link.
  • the navigation link can be used as part of a dynamic display for a specific gene/alteration combination. Responsive to selection of the link, the dynamic display can transition to the relevant information.
  • FIG. 4 shows disease ontology grouping that may be performed according to one embodiment of the present invention.
  • a disease ontology group 401 may be made and stored as part of a database. More particularly, patient data may be grouped and accessed by disease ontology groups that link similar diseases. For instance, behavior and/or other characteristics of particular diseases may allow them to be grouped together. For instance, certain diseases may share common information such as alterations, progression of disease state, common treatments, clinical behavior or other information that would allow them to be grouped together.
  • a more general DOG may be determined called "Breast Carcinoma" 402 which is a grouping of similar carcinomas including breast invasive ductal carcinoma 403, breast adenocarcinoma 404, and breast invasive lobular carcinoma 405.
  • Such grouping may be used as a way of grouping related patients.
  • patient data may include one or more disease types represented in a database by a relation to those disease types.
  • patients having diseases categorized within the DOG may be obtained.
  • disease ontology groups may be formed. For instance, as information is collected from various patients, studies, articles, etc., some diseases may have characteristics that may permit them to be grouped such as common treatments, similar alterations, etc. Such groupings may be performed automatically through collection of information from a number of sources and/or curated by experts who have specific knowledge of their relatedness.
  • the system may perform a query for a similar patient to the current patient entered using disease ontology groups and alteration data.
  • data may be sparse, and groupings of similar alterations and diseases may permit a query to obtain results even if the disease/alteration combination of the current client is not found.
  • the query may be a two or more dimensional query that searches for similar patients belonging to a common alteration group and having a common disease ontology group as the current patient.
  • a result may include an ordered list of patients.
  • the system may provide the ordered list of patients to the physician user
  • the patient data may be anonymized such that personally-identifiable information is masked or omitted from the physician computer interface.
  • the list may be ranked such that the most relevant information is provided.
  • information for patients having positive outcomes may be preferred over negative outcome data, such that physicians are connected with other physicians that have successfully treated similar cancers.
  • information regarding a treating physician may also be used to order results, as in one example, a physician that has successfully treated a number of patients may be preferred over a physician that has only treated one similar patient.
  • outcome data may not be included with respect to identifying similar patients, as some outcome data may be biased.
  • the system may provide controls that permit the physician user to contact other physician user(s) that treated the identified patients. For instance, tools that captively collect the communications between physicians may be provided such that information is collected and saved in the database for use with future patients.
  • the physician user caring for the current patient may be contacted. Further aspects of the present invention relate to selecting the patient for which a physician may be contacted.
  • the system may also include a number of timer and reminder functions to facilitate the communications such that the requesting physician is provided the information in a timely manner to support treatment of the patient.
  • process 500 ends, although it is appreciated that this process may be repeated many times, constantly improving the database with new data including treatments, communications and patient outcomes.
  • FIG. 6 shows an example process 600 for locating historical responses and presenting them to physician users according to one embodiment of the present invention.
  • process 600 begins.
  • a patient's cancer may be analyzed through one or more processes, including genomic testing. It is appreciated that through genomic testing of a patient's cancer, a targeted treatment for the particular cancer can be created, which is more effective and less damaging of other types of cells.
  • the diagnosed tumor type and related disease group and present alterations and related alteration group is used to locate one or more similar patients. For example, if specific patients identified have an identical disease and alterations, patients are identified and returned as a result. However, if no exact matches are found, patients belonging to the same alteration disease groups may be returned. In another embodiment, a more general search using the identified groups may be performed rather than a two-step approach.
  • the system may be adapted to display any previously related historical responses to the physician user. For instance, depending on whether a previous search was performed using similar disease and alteration combinations, there may exist existing response data within the database between physicians. It may be beneficial to store such information and provided to physicians without the necessity for contacting the treating physician again for the same information.
  • process 600 ends.
  • the system may choose the oldest TRF number in the list and display that particular case to the physician user.
  • criteria may include, for instance, a collection of data that relates to how stale information is within the database, how active the cases by collected data or when the data was last requested.
  • a predetermined number of times e.g., three times
  • FIG. 8 shows an example system upon which various aspects of the present invention may be practiced.
  • FIG. 8 shows a system 800 which may include one or more computer-based systems that receive and collect biomarker data 801 and patient specific pathology information 802.
  • System 800 includes an inference engine 803 that interprets a graph-based data model 804 to determine one or more actionable items 805.
  • actionable items may be presented to a user 806 (e.g. a physician, oncologists, or other user type).
  • Such actionable items may include recommending a patient for clinical trial, a recommendation of a particular form of treatment, or other recommendation.
  • Such a model may be a learning model in that information is being added to the system in real time, and the recommendations made by the system may also change over time. For instance, information may be added, deprecated, deleted, or updated, such as adding information relating to patients, studies, journal articles or other information. Additional information may be added as tuples to the graph-based data model. The inference engine may use such additional information to make one or more inferences regarding the data model.
  • FIG. 9 shows yet another example system upon which various aspects of the present invention may be practiced.
  • FIG. 9 shows an example embodiment of a system 900 for managing genomic testing information.
  • the system 900 can be configured to provide a single reporting source for accessing and applying available information on a patient's cancer.
  • genomic testing on the patient's cancer provides specific information the tumor, one or more genes implicated by the tumor, and one or more alterations within the genes which can be displayed by the system 900 through a web interface 901.
  • the web interface 901 can include an alteration engine (e.g., element 902) that performs any of the operations discussed below with respect to the alteration engine 1001.
  • the alteration engine can include specific component for provide specific functionality on the web interface 901.
  • the alteration engine 902 also can include a report generator component 903 configured to generate physical and/or static report for downloading through the web interface.
  • the alteration engine can also include an analytic subsystem 904 an analytic subsystem configured to identify matches information between a current patient's tumor type, gene, and/or alteration and include or identify the matching information items for display in the patient's test results.
  • the alteration engine 902 can also include a curation component 910 configured to generated curated information for use on the system.
  • the curated information can include interpreted statements regarding any one or more of genomic alterations, an implicated gene, a patient's tumor type, and/or potentially applicable therapies for a patient's cancer.
  • the curation component can be accessed by human operators
  • curators who generate and/or approve system generated interpreted statement regarding genomic alterations, an implicated gene, a patient's tumor type, and/or potentially applicable therapies.
  • the alteration engine can include an update component 912 configured to track any updates to genomic alterations and any information associated with the genomic alterations.
  • the update component 912 can identify updates information for display by the UI component 911.
  • the alteration engine components are configured to perform the function and operations discussed above with respect to the alteration engine and associated components.
  • the web interface 901 can be accessed by users (e.g., 905) over the internet.
  • the user can access the web interface from a variety of location (e.g., laboratory 915, hospital 914, and treatment facility 913).
  • the users at any one or more of 913-915 can share genomic test reports with each other.
  • the web interface 901 can be configured to provide social functions between users.
  • the web interface can limit sharing to practice groups, within treatment facilities, or within medical institutions (e.g., hospitals).
  • sharing of test results and associated genomic information on patients can create a strong community of physicians, and foster discussion about treatment. Further, as discussed above, the interface may permit identification of similar patients and foster collaboration about similar patients.
  • the web interface 901 is adapted to store genomic test information in database 921.
  • Database 921 is illustrated as a single database, but in other embodiments, database 921 can include any storage medium or organizational unit for storing and accessing genomic test results and associated information. Further embodiments can include a plurality of databases and can also include distributed data architectures. According to one embodiment, database 921 can include a variety of data records accessed by the web interface 901 to manage delivery of genomic test results and associated information.
  • the database can include information on genomic testing.
  • genomic test results are stored and associated with patient records.
  • the genomic test results can include information on genomic alterations.
  • Specific genomic alterations can be stored in database 217 and access for presenting information within a display of a patient's test report.
  • the database can include curation records stored and associated with any one or more of a tumor type, gene, and/or genomic alteration.
  • Other information may be stored, such as disease ontology groups, alteration groups, communications between physicians, outcome information, and/or any other type of information.
  • Information on clinical trials can likewise be stored as information items associated with any one or more of a tumor type, gene, and/or genomic alteration.
  • the database 921 can also store therapy information and references information and provide associated for either to any one or more of a tumor type, gene, and/or genomic alteration.
  • the database 921 can also be configured to track and store information on updates to any information within the database. In one example, updates can be flagged by other system components and the flags resolved or remove once viewed.
  • the database can store information on data views for used by web interface and/or the UI component 911. Each one of the views can be accessed and used by the web interface to present information on genomic testing and associated information to a user.
  • the system and/or web interface can be configured to capture information from external information sources for storage in database 921.
  • external data source 916 can contain information related to a patient's tumor type, gene, and/or alteration. The information from the external information can be captured and stored as records in database 921 accessible via the relationship to the tumor type, gene, and/or alteration.
  • the information stored in database 921 can include reference to the external information source.
  • clinical trial information items can include links to clinicaltrials.gov 917
  • reference information items can include links to
  • the web interface 202 can be configured to access genomic alteration information for cancer diagnoses made at a hospital or laboratory (e.g., 919).
  • the web interface can capture genomic information from EMR (electronic medical records) data to retrieve tumor type, implicated gene, and/or alteration type for storage in database 921.
  • EMR electronic medical records
  • references or links to the specific medical records can also be stored in the database.
  • the links to the medical records can be presented in a dynamic display generated on system 900.
  • associated of all the information in the database according to tumor, gene, or alteration provides insight into prescribed uses of therapies (on-label) and off- label applications for such therapies.
  • off-label used can be identified based on alteration (e.g., different tumors but same alteration - provides relation information on a potentially effective therapy the current patient' s cancer.
  • each record can be associated with a data space for an update flag. Responsive to any update to information on the database 921, the system can enter information in the data space for the update flag. Tracking updates to genomic alteration and associated information facilitates user awareness of potential significant changes in a patient report. Further, tracking of update information in the database 921 enables the system to deliver notification regarding any updates.
  • social functions can have associated records in the database. For example, permission information (e.g., who can share a report and/or who can receive a shared report) can be associated with test reports stored in database 921. Further,
  • genomic testing reports can be provided succinctly and enable the users to select the indicator to access more detailed information as needed.
  • genomic test results e.g., listings of alterations
  • actionability of the navigable data structures can be defined on available information for an FDA approved agent in the patient's tumor type, available information for an FDA approved agent in another tumor type, and/or available information for a mechanistically driven or biologically relevant clinical trial based on the alteration(s) found.
  • the ordering can be configured to focus the user on the actionable information to facilitate review of a plurality of alterations and their associated information.
  • Indicators of actionable items can be displayed based on an information source (e.g., a therapy indicator/tag references available therapy information items related to a genomic alteration, a trial tag references available clinical trial information items, and a reference tag for reference information items).
  • the indicator can be associated with a respective alteration in the plurality of alterations resulting from genomic testing.
  • the system facilitates successive selection of alterations and associated information within the plurality of alteration results, for example, using the indicators. By enabling successive selections, the system facilitates better understanding of a patient's cancer and enables more informed treatment decisions.
  • FIG. 10 there is illustrated an example of a system 1000 for managing genomic testing information using an alteration engine 1001.
  • Elements of the system 1000 can be provided using a computing system such as a computer system such as that described above with reference to FIG. 9.
  • the alteration engine 1001 can be executed on the computer system to provide the functions and operations discussed herein.
  • the alteration engine 1001 can be executed on the computer system to provide the functions and operations discussed herein.
  • the alteration engine 1001 can include additional components executed on the computer system to perform specific operations.
  • various embodiments of the alteration engine 1001 are configured to accept genomic test results 1002 and associate the genomic test results with curated information.
  • the curated informing can include detailed analysis or additional information tailored to the characteristic of the test results.
  • the test results generated for a specific patient can specify a plurality of genes and alterations found within the patient' s cancer.
  • the alteration engine 1001 can be configured to associate curated information tailored to the specific genes/alteration identified for the patient.
  • the alteration engine 1001 can be configured to generate a single source display of the test results, curated information, and any additional information (e.g., identified similar patient data) as a dynamic display 1003.
  • the dynamic display 1003 can include and organize the test results, the curated information, and the additional information to minimize the volume of data displayed to the user at any one time.
  • the dynamic display 1003 can include a plurality of views of the test results, the curated information, and the additional information.
  • the test, curated, and additional information can be organized into categories for display in a user interface.
  • the user interface can be specially configured for navigation with mobile devices.
  • the user interfaces generated by the system can also be configured to include gene and alteration information specific to a current patient being viewed.
  • the user interfaces are configured to present categorized information to facilitate understanding of the gene and alteration information for the current patient.
  • the dynamic display is presented for a specific patient selected by the user from a patient listing. Once selected, the current patient's information (e.g., name, date of birth, height, weight, sex, patient id, case id, etc.) can be provided along with information regarding the genetic testing conducted (e.g., specimen receipt date, report generation date, diagnosis (type of tumor), collection date for specimen, collection method, specimen type, etc.) as a first portion of a dynamic display 1003. If anonymized (e.g., the patient is not the user's patient) some or all of this identifying information may be masked or removed.

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Abstract

L'invention concerne un procédé, un système et une base de données qui permettent aux utilisateurs de traiter des patients ayant une altération génomique pour échanger des informations plus facilement et plus efficacement avec d'autres utilisateurs qui traitent des patients ayant des altérations génomiques similaires. Dans un exemple, un utilisateur peut être autorisé à attribuer des étiquettes d'altération génomique à des patients et à filtrer des patients sur la base des altérations génomiques. Des caractéristiques supplémentaires, permettant d''identifier automatiquement d'autres utilisateurs, et faciliter la communication avec ces utilisateurs qui ont traité des patients similaires, peuvent être prévues pour améliorer encore l'aptitude de l'utilisateur à traiter des altérations génomiques.
PCT/US2015/066325 2014-12-17 2015-12-17 Système mis en œuvre par ordinateur et procédé permettant d'identifier des patients similaires WO2016100638A1 (fr)

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EP15871055.8A EP3234841A4 (fr) 2014-12-17 2015-12-17 Système mis en oeuvre par ordinateur et procédé permettant d'identifier des patients similaires
CA2970931A CA2970931C (fr) 2014-12-17 2015-12-17 Systeme mis en oeuvre par ordinateur et procede permettant d'identifier des patients similaires
AU2015364605A AU2015364605B2 (en) 2014-12-17 2015-12-17 Computer-implemented system and method for identifying similar patients
HK18104572.8A HK1245444A1 (zh) 2014-12-17 2018-04-09 計算機執行系統及識別類似患者的方法
AU2021202244A AU2021202244B2 (en) 2014-12-17 2021-04-14 Computer-implemented system and method for identifying similar patients

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109791795A (zh) * 2016-09-29 2019-05-21 皇家飞利浦有限公司 用于协同变异选择和治疗匹配报告的方法和装置
US11126921B2 (en) 2017-04-20 2021-09-21 Koninklijke Philips N.V. Learning and applying contextual similarities between entities
US11282610B2 (en) 2016-02-02 2022-03-22 Guardant Health, Inc. Cancer evolution detection and diagnostic
US11676733B2 (en) 2017-12-19 2023-06-13 Koninklijke Philips N.V. Learning and applying contextual similarities between entities
US11756655B2 (en) 2015-10-09 2023-09-12 Guardant Health, Inc. Population based treatment recommender using cell free DNA

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020052761A1 (en) * 2000-05-11 2002-05-02 Fey Christopher T. Method and system for genetic screening data collection, analysis, report generation and access
US20090287503A1 (en) * 2008-05-16 2009-11-19 International Business Machines Corporation Analysis of individual and group healthcare data in order to provide real time healthcare recommendations
US20140336943A1 (en) * 2013-01-05 2014-11-13 Foundation Medicine, Inc. System and method for managing genomic testing results

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020052761A1 (en) * 2000-05-11 2002-05-02 Fey Christopher T. Method and system for genetic screening data collection, analysis, report generation and access
US20090287503A1 (en) * 2008-05-16 2009-11-19 International Business Machines Corporation Analysis of individual and group healthcare data in order to provide real time healthcare recommendations
US20140336943A1 (en) * 2013-01-05 2014-11-13 Foundation Medicine, Inc. System and method for managing genomic testing results

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
BARABASI ET AL.: "Network medicine: a network-based approach to human disease", NATURE REVIEWS GENETICS, vol. 12, no. 1, 2011, pages 56 - 68, XP055407343 *
HAGA ET AL.: "Developing patient-friendly genetic and genomic test reports: formats to promote patient engagement and understanding", GENOME MEDICINE, vol. 6, 31 July 2014 (2014-07-31), pages 1 - 11, XP021208811 *
See also references of EP3234841A4 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11756655B2 (en) 2015-10-09 2023-09-12 Guardant Health, Inc. Population based treatment recommender using cell free DNA
US11282610B2 (en) 2016-02-02 2022-03-22 Guardant Health, Inc. Cancer evolution detection and diagnostic
US11335463B2 (en) 2016-02-02 2022-05-17 Guardant Health, Inc. Cancer evolution detection and diagnostic
US11621083B2 (en) 2016-02-02 2023-04-04 Guardant Health, Inc. Cancer evolution detection and diagnostic
US11996202B2 (en) 2016-02-02 2024-05-28 Guardant Health, Inc. Cancer evolution detection and diagnostic
CN109791795A (zh) * 2016-09-29 2019-05-21 皇家飞利浦有限公司 用于协同变异选择和治疗匹配报告的方法和装置
US11126921B2 (en) 2017-04-20 2021-09-21 Koninklijke Philips N.V. Learning and applying contextual similarities between entities
US11875277B2 (en) 2017-04-20 2024-01-16 Koninklijke Philips N.V. Learning and applying contextual similiarities between entities
US11676733B2 (en) 2017-12-19 2023-06-13 Koninklijke Philips N.V. Learning and applying contextual similarities between entities

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CA2970931C (fr) 2023-05-23
AU2021202244B2 (en) 2023-02-16
AU2015364605B2 (en) 2021-01-28
CA2970931A1 (fr) 2016-06-23
EP3234841A1 (fr) 2017-10-25
EP3234841A4 (fr) 2018-08-29
AU2021202244A1 (en) 2021-05-13

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