Abstract: In patient cohort identification, clustering (30) of patients is performed using a patient comparison metric dependent on a set of features (24). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster (34) containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations (70, 72, 74) each plotting the sample patients and the query patient against two or more features of the modality.

Abstract: A method for assessing quality of genomic regions studied for inclusion in standardized clinical formats includes receiving data sets to be applied to a plurality of gene panels. The method also includes applying, by a processor executing instructions, standardized quality control metrics to the data sets to be applied to the plurality of gene panels; filtering, by the processor executing the instructions, each of the data sets to be applied to the plurality of gene panels to sets of variants and formatting the sets of variants in a clinical format, and outputting the sets of variants resulting from the filtering to a downstream application.

Abstract: The present disclosure describes systems configured to guide users through a sequential mapping process to extract targeted information from received clinical report documents. The systems are configured to utilize the extracted information to generate a comprehensive, flexible report data model used to process incoming clinical report documents having the same document structure. Systems are uniquely configured to map incoming reports by utilizing the source code of PDF files, including the displayed text, information that determines how the text appears, and the absolute position of the text within each document constituting a clinical report.

Abstract: A method (100) for standardizing gene nomenclature, comprising: (i) receiving (110) a source; (ii) tokenizing (120) the source; (iii) comparing (130) a first token to a prefix tree structure with a root node, edges, and leaf nodes; (iv) determining (140) which edge extending from the root node to associated first leaf nodes the first token matches; (v) updating (150) an identification pointer with the location of the first leaf node; (vi) determining (160) which of one or more edges that a second token matches; (vii) updating (170) the identification pointer with the location of the second leaf node; (viii) repeating (172) the determining (160) and updating (170) steps with subsequent tokens until a subsequent token fails to match an edge extending from a leaf node or there is no edge extending from the leaf node; and (ix) providing (180) an identification of a canonical gene name.

Abstract: A computer-implemented method for constructing a state transition graph, wherein the method includes obtaining data that includes treatment history and clinical data of a cohort of patients; and generating, by the one or more computing devices, individual treatment pathways for individual patients of the cohort of patients using the treatment history and clinical data for the individual patients; wherein the individual treatment pathways are generated using user-defined parameters including: one or more qualifying events; one or more response states to the one or more qualifying events; and one or more reversible or collapsible events. The method additionally includes constructing a state transition graph that represents multiple aligned and merged individual treatment pathways including the one or more qualifying events, the one or more response states to the one or more qualifying events and the one or more reversible or collapsible events.

Abstract: A method (100) for standardizing gene nomenclature, comprising: (i) receiving (110) a source; (ii) tokenizing (120) the source; (iii) comparing (130) a first token to a prefix tree structure with a root node, edges, and leaf nodes; (iv) determining (140) which edge extending from the root node to associated first leaf nodes the first token matches; (v) updating (150) an identification pointer with the location of the first leaf node; (vi) determining (160) which of one or more edges that a second token matches; (vii) updating (170) the identification pointer with the location of the second leaf node; (viii) repeating (172) the determining (160) and updating (170) steps with subsequent tokens until a subsequent token fails to match an edge extending from a leaf node or there is no edge extending from the leaf node; and (ix) providing (180) an identification of a canonical gene name.

Abstract: A method (100, 200, 400) for predicting a response of a tumor to immunotherapy, comprising: analyzing (120) a tumor sample; analyzing (130) a non-tumor sample obtained from the patient; identifying (140) one or more tumor-specific mutations; analyzing (150) the genetic information from the tumor sample to determine a variant allele frequency for the identified tumor-specific mutations; analyzing (160) genetic information to determine a tumor purity of the patients tumor; determining (210) a pathogenicity for the identified tumor-specific mutations; calculating (220), from: (i) the determined variant allele frequency and/or a determined allele-specific expression, exon expression, or gene expression of the one or more tumor-specific mutations; (ii) the determined tumor purity; and (iii) the determined pathogenicity, a tumor functional mutation load score; predicting (410), based on the score, a response of the patients tumor to an immunotherapy treatment; and determining (420), based on said prediction, a trea

Abstract: A method for assessing risk associated with a request from an inquirer for allele frequency from a database of genetic data, comprising: (i) generating an allele database comprising allele frequency information and request frequency information for each of a plurality of alleles; (ii) generating an inquirer database comprising allele request information about a plurality of inquirers; (iii) receiving a request for genetic data from an inquirer, comprising a request for allele frequency for one or more alleles and an identifier of the inquirer; (iv) updating the request frequency information based on the received request; (v) updating the allele request information for the requesting inquirer; (vi) calculating an allele risk score; (vii) calculating an inquirer risk score; and (viii) assessing, based on the allele risk score and the inquirer risk score, a risk associated with the received request.

Abstract: Various embodiments relate to a method and apparatus for building a pedigree for a disease based on a family tree, the method comprising the steps of receiving, by a pedigree service, a family health condition request, transmitting, by the pedigree service, a request for the family tree, transmitting, by the pedigree service, a data request for health conditions of relatives on the family tree to an access control system, verifying, by the access control system, consent of the relatives on the family tree, receiving, by the pedigree service, health conditions of the relatives from a health data storage and drawing, by the pedigree service, a pedigree for the disease based on the health conditions of the relatives.

Abstract: Methods and systems for constructing a query. The methods and systems described herein provide novel techniques for constructing queries by mapping ontologies to each other. Accordingly, systems and methods described herein may map an otherwise unmappable term to an ontology in order to capitalize on the knowledge contained therein.

Abstract: A method (100) for recruiting a patient for a clinical trial, comprising: receiving (110) a dataset comprising information about one or more clinical trials each including patient eligibility criteria; extracting (120) the patient eligibility criteria from each of the clinical trials; converting (130) the patient eligibility criteria to a standardized patient eligibility criterion using a structured clinical trial mark-up language; storing (140) the patient eligibility criterion in a database (862), each of the criterion associated with one or more clinical trials; receiving (150) patient-specific data values about a patient; querying (160) the clinical trial eligibility criteria database using the patient-specific data values to identify eligibility criterion satisfied by the patient-specific data value; identifying (170) a clinical trial associated with the one or more standardized patient eligibility criterion satisfied by a received patient-specific data value; and providing (180) a report of the identifi

Abstract: A clinical genomic data processing device includes at least one microprocessor (10) and a non-transitory storage medium (12) storing instructions to implement functions of the device. A user interface (26, 28) receives requests for execution of genomic workflows and to display output generated by the execution of the genomic workflows. A genomic workflow manager manages an asynchronous messaging queue (24) and manages the execution of the genomic workflows. Service providers (20) performs jobs associated with the genomic workflows. The genomic workflow manager communicates with the service providers by messages exchanged via the asynchronous messaging queue to manage the execution of the genomic workflows via jobs performed by the service providers.

Abstract: A system and method for providing a prioritized list of clinical trials that are relevant to a patient suffering from an illness or disease, such as cancer, are disclosed. Specifically, a method for conducting an automated, real time clinical trial search and a prioritization analysis is described. The method comprises the steps of conducting an automated full-text clinical trial search based on structuralization of clinical trial eligibility data and knowledge-based inference, initiating a query from the patient's side, and providing a prioritized list of all accessible clinical trials fulfilling a particular query. The system provides better sensitivity, precision and negative predictive value than the current most known clinical trial matching tool: clinicaltrials.gov.

Abstract: Methods and apparatus for a secure framework for storing and analyzing genomic data. Embodiments of the present invention apply persistent governance to sensitive information and to the analytics that operate upon it, managing the interaction between the two.

Abstract: A genetic sequencer (10) generates DNA reads (16) from a tissue sample of a current patient. The DNA reads are aligned (18) with a reference DNA sequence (20) to generate a DNA sequence (22) of the current patient. Variant calling (24) is performed to generate a list of genetic variants (26) contained in the DNA sequence of the current patient. Occurrences are determined of genetic variants in one or more reference databases (44) storing genetic variants of medical patients. It is determined whether genetic variants of the list of genetic variants are synonymous. Scores are assigned for genetic variants based at least on measures of correlation of the genetic variants with disease. A ranked list (32) of top-scoring genetic variants is generated based on the assigned scores, and the ranked list is displayed on a display (36).

Abstract: A method for assessing risk associated with a request from an inquirer for allele frequency from a database of genetic data, comprising: (i) generating an allele database comprising allele frequency information and request frequency information for each of a plurality of alleles; (ii) generating an inquirer database comprising allele request information about a plurality of inquirers; (iii) receiving a request for genetic data from an inquirer, comprising a request for allele frequency for one or more alleles and an identifier of the inquirer; (iv) updating the request frequency information based on the received request; (v) updating the allele request information for the requesting inquirer; (vi) calculating an allele risk score; (vii) calculating an inquirer risk score; and (viii) assessing, based on the allele risk score and the inquirer risk score, a risk associated with the received request.

Abstract: In patient cohort identification, clustering (30) of patients is performed using a patient comparison metric dependent on a set of features (24). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster (34) containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations (70, 72, 74) each plotting the sample patients and the query patient against two or more features of the modality.

Abstract: Methods and systems for visualizing gene expression data in a way that permits the comparison of different patient groups to facilitate medical applications, including cancer diagnostics and treatment planning, particularly breast cancer. The method organises gene expression data for at least one patient into a plurality of windows of a specified size, calculates an average RSEM score for all of the genes in each window and presents the average RSEM scores in a two-dimensional array, wherein one axis organises the windows by patient and the other axis organises the windows by sequence.

Abstract: Methods and apparatus for a secure framework for storing and analyzing genomic data. Embodiments of the present invention apply persistent governance to sensitive information and to the analytics that operate upon it, managing the interaction between the two.

Abstract: Clinical decision support visualization methods that use information, pathways, or inferred regulatory networks for the entire genome, transcriptome, exome, or methylome to highlight genomic activity to further the understanding of the clinical condition of a patient or to contrast different patient groups.