Abstract: A generalizable and interpretable deep learning model for predicting biomarker status and biomarker metrics from histopathology slide images is provided.

Abstract: A method and system of audibly broadcasting responses to a user based on user queries about a specific patient molecular report, the method comprising receiving an audible query from the user to a microphone coupled to a collaboration device, identifying at least one intent associated with the audible query, identifying at least one data operation associated with the at least one intent, associating each of the at least one data operations with a first set of data presented on the molecular report, executing each of the at least one data operations on a second set of data to generate response data, generating an audible response file associated with the response data and providing the audible response file for broadcasting via a speaker coupled to the collaboration device.

Abstract: The disclosure provides a method of generating an artificial fluorescent image of cells is provided.

Abstract: A system, method, and mobile device application are configured to capture, with a mobile device, a document such as a next generation sequencing (NGS) report that includes NGS medical information about a genetically sequenced patient. The method includes receiving, from a mobile device, an image of a medical document comprising NGS medical information of the patient, extracting a first region from the image, extracting NGS medical information of the patient from the first region into a structured dataset, the extracted NGS medical information including at least one RNA expression, correlating a portion of the extracted NGS medical information that includes the at least one RNA expression with summarized medical information from a cohort of patients similar to the patient, and generating, for display on the mobile device, a clinical decision support report comprising the summarized medical information.

Abstract: Systems and methods are provided for identifying a diagnosis of a cancer condition for a somatic tumor specimen of a subject. The method receives sequencing information comprising analysis of a plurality of nucleic acids derived from the somatic tumor specimen. The method identifies a plurality of features from the sequencing information, including two or more of RNA, DNA, RNA splicing, viral, and copy number features. The method provides a first subset of features and a second subset of features from the identified plurality of features as inputs to a first classifier and a second classifier, respectively. The method generates, from two or more classifiers, two or more predictions of cancer condition based at least in part on the identified plurality of features. The method combines, at a final classifier, the two or more predictions to identify the diagnosis of the cancer condition for the somatic tumor specimen of the subject.

Abstract: A system and method that receive a distance matrix for multiple patients and a patient of interest, assign a radial distance value between the patient of interest and the other patients based on the distance matrix value for each of the multiple patients, generate an angular distance value between the multiple patients based at least in part on a measure of similarity between each patient, and minimize a cost function based at least in part on the angular distance value between each patient and each other patient. Minimizing the cost function may include calculating a patient contribution to the cost function for a plurality of angular distance values and selecting the angular distance value with the smallest patient contribution. The processor also may be configured to generate and display a radar plot based on the assigned radial distance value and generated angular distance value of each patient.

Abstract: Processes are provided for detecting loss of heterozygosity of Human Leukocyte Antigen (HLA) in a subject using analysis of next generation sequencing (NGS) data. The processes include aligning NGS data and identifying unmapped and mapped reads, updating reference data, and feeding one or more sequence reads to an HLA typing process for identifying candidate HLA alleles and feeding HLA type data to a loss of heterozygosity (LOH) modeling process for determining a LOH status for each HLA allele. A report may be generated of the LOH statuses for each of HLA allele.

Abstract: Methods, systems, and software are provided for validating a somatic sequence variant in a subject having a cancer condition. Sequence reads are obtained from sequencing cell-free DNA fragments in a liquid biopsy sample of the subject. Sequence reads are aligned to a reference sequence. A variant allele fragment count and locus fragment count are identified for a candidate variant that maps to a locus in the reference sequence. The variant allele fragment count is compared against a dynamic variant count threshold for the locus. The threshold is based on a pre-test odds of a positive variant call for the locus, based on the prevalence of variants in a genomic region including the locus in a cohort of subjects having the cancer condition. The somatic sequence variant in the subject is validated, or rejected, when the variant allele fragment count for the candidate variant satisfies, or does not satisfy, the threshold.

Abstract: Disclosed herein are systems, methods, and compositions useful for profiling T cell receptor (TCR) and B cell receptor (BCR) repertoire using next-generation sequencing (NGS) methods. In certain embodiments, the methods include enriching a sample for TCR/BCR RNA sequences, and determining the TCR/BCR profile of a subject using five different oligonucleotide pools. Also disclosed herein are systems and methods for diagnosing, treating, or predicting infection, disease, medical conditions, therapeutic outcome, or therapeutic efficacy based on the TCR/BCR profile data from a subject in need thereof.

Abstract: Methods, systems, and software are provided for using organoid cultures, e.g., patient-derived tumor organoid cultures, to improve treatment predictions and outcomes.

Abstract: A computer program product includes multiple microservices for interrogating clinical records according to one or more projects associated with patient datasets obtained from electronic copies of source documents from the clinical records. A first microservice generates a user interface including a first portion displaying source documents and, concurrently, a second portion displaying structured patient data fields organized into categories for entering structured patient data derived from the source documents displayed in the first portion. Categories and their organization are defined by a template and include cancer diagnosis, staging, tumor size, genetic results, and date of recurrence. A second microservice validates abstracted patient data according to validation rules applied to the categories, validation rules being assigned to the projects and performed on the categories as they are populated.

Abstract: Disclosed herein are systems, methods, and compositions useful for determining cellular pathway disruption comprising the use of RNA expression level information. This determined level of disruption can assist in the identification of genetic variants that alter pathway activity, to correlate these variants with disease state and disease progression, and to identify those therapeutics most likely to be effective and which should be avoided.

Abstract: Techniques are provided for replacing image assays using real world data and real word evidence RNA-seq analysis for assessing biologic pathways for identifying molecular subtypes. Systems of a methods diagnose HER2 status for a patient, by identifying discordant HER2 status result between the HER2 status from immunohistochemistry (IHC) and the HER2 status from fluorescence in-situ hybridization (FISH) and diagnosing HER2 status based gene expression data.

Abstract: A method for determining tumor block sufficiency for generating one or more hematoxylin and eosin (H&E) slides by assessing an expected yield of nucleic acids for tumor cells and determining a number of H&E slide for satisfying a desired total nucleic yield is provided.

Abstract: A method for qualifying a specimen prepared on one or more hematoxylin and eosin (H&E) slides by assessing an expected yield of nucleic acids for tumor cells and providing associated unstained slides for subsequent nucleic acid analysis is provided.

Abstract: A method for predicting an expected yield of nucleic acid from tumor cells within a dissection boundary on a hematoxylin and eosin (H&E) slide is provided.

Abstract: A system and method for analyzing a data store of de-identified patient data to generate one or more dynamic user interfaces usable to predict an expected response of a particular patient population or cohort when provided with a certain treatment. The automated analysis of patterns occurring in patient clinical, molecular, phenotypic, and response data, as facilitated by the various user interfaces, provides an efficient, intuitive way for clinicians to evaluate large data sets to aid in the potential discovery of insights of therapeutic significance.

Abstract: In one aspect, the present disclosure provides a method for labeling one or more medications concurrently administered to a patient as a line of therapy. The method includes identifying medical records of the patient from a plurality of digital records, creating, from the subset of medical records, a plurality of treatment intervals including at least one medication administered to the patient and a time interval, associating medications of the one or more treatments with a respective treatment interval when the administration of the medication falls within the time interval, refining the time interval of a respective treatment interval when a treatment of the one or more treatments falls outside the time interval but within an extension period, identifying one or more potential lines of therapy from the plurality of treatment intervals, and labeling the potential line of therapy having the highest maximum likelihood estimation as the line of therapy.

Abstract: A generalizable and interpretable deep learning model for predicting biomarker status and biomarker metrics from histopathology slide images is provided.

Abstract: Systems and methods are provided for predicting metastasis of a cancer in a subject. A plurality of data elements for the subject's cancer is obtained, including sequence features comprising relative abundance values for gene expression in a cancer biopsy of the subject, optional personal characteristics about the subject, and optional clinical features related to the stage, histopathological grade, diagnosis, symptom, comorbidity, and/or treatment of the cancer in the subject, and/or a temporal element associated therewith. One or more models are applied to the plurality of data elements, determining one or more indications of whether the cancer will metastasize. A clinical report comprising the one or more indications is generated.