Abstract: Computer based methods, systems, and computer readable media for intelligently accessing various types of pharmaceutical information in a content repository and ranking drugs at the variant level, gene level, and pathway level. In some cases, drugs that target the same gene, gene variant, or biological pathway may be ranked based upon in vitro, pre-clinical, clinical, or post-clinical evidence. To determine ranking of a plurality of drugs, information pertaining to drug administration is analyzed for the drugs. For a plurality of drugs, attributes corresponding to the drug are determined, wherein the attributes include a variant or a gene targeted by the drug, and a biological pathway comprising the targeted variant or gene. The plurality of drugs are ranked according to a drug effectiveness score based on one or more of a determined efficacy, potency, or toxicity.

Abstract: Computer based methods, systems, and computer readable media for providing genomic services are provided. A request is received from a user. The request is applied to one or more from a group of a personalized data repository for the user and supporting knowledge bases, wherein the personalized data repository includes genetic test results, health/clinical information, and insurance coverage, and wherein the knowledge bases include information pertaining to genetic tests and clinical guidelines. Data from the applied request is integrated with results from service modules performing one or more from a group of content search, variation interpretation, and report generation to produce results for the request. The personalized data repository and supporting knowledge bases are updated based on the results of the request. Surveillance services are triggered based on one or more events.

Abstract: Computer-based methods, systems, and computer readable media for managing documents within a content repository or documents within the document subsets are provided. Documents within the content repository may be classified into one of a functional category and a clinical category. Documents are applied to a machine learning annotation and analysis module to automatically annotate the documents to indicate relationships between entities. A request is processed for the documents including one or more search terms, wherein the search terms pertain to one or more entities from a group of gene, gene variant, drug, cancer and a biomedical/clinical term. Documents satisfying the request are identified by comparing the one or more search terms to the annotations and specific sections of the documents, and determining a relevance of a document based on the comparison and a frequency of the one or more search terms in each of the specific sections. The identified documents are ranked according to custom techniques.

Abstract: Computer-based methods, systems, and computer readable media for managing documents within a content repository or documents within the document subsets are provided. Documents may be pre-processed to be machine readable and classified within the content repository into one or more categories, based upon a number of times classification terms appear in a specific section of the document or based on an article type tag. Document subsets may be generated based on user-defined terms. Documents may be associated with specific cancer-types, genes, gene variants and drugs by comparing relevant search terms to specific sections of the documents. A request for processing the documents may include one or more of the search terms, pertaining to one or more from a group of gene, gene variant, drug, and cancer terms.

Abstract: A computer system processes documents in a content repository. Each document of a plurality of documents is classified into one of a functional category and a clinical category. Each document is annotated using one or more corpora to generate document annotations. Documents satisfying one or more query terms are identified by comparing each query term to the document annotations. The identified documents are ranked based on a determined relevance. Guidelines are produced based on the ranking of the identified documents. Embodiments of the present invention further include a method and program product for processing documents in a content repository in substantially the same manner described above.

Abstract: Computer-based methods, systems, and computer readable media for managing documents within a content repository or documents within the document subsets are provided. Variant annotations within the documents may be normalized to a standard nomenclature. A request is processed for the documents including one or more search terms, where the search terms pertain to one or more from a group of genes/gene variants, drugs, and cancer terms. Documents are identified that satisfy the request by comparing the one or more search terms to the normalized annotations and specific sections of the documents, and determining a relevance of a document based on the comparison and a frequency of the one or more search terms in each of the specific sections. The identified documents are ranked in accordance with a priority based on the determined relevance.

Abstract: Computer based methods, systems, and computer readable media for providing genomic services are provided. A request is received from a user. The request is applied to one or more from a group of a personalized data repository for the user and supporting knowledge bases, wherein the personalized data repository includes genetic test results, health/clinical information, and insurance coverage, and wherein the knowledge bases include information pertaining to genetic tests and clinical guidelines. Data from the applied request is integrated with results from service modules performing one or more from a group of content search, variation interpretation, and report generation to produce results for the request. The personalized data repository and supporting knowledge bases are updated based on the results of the request. Surveillance services are triggered based on one or more events.

Abstract: Computer based methods, systems, and computer readable media are provided for intelligently sorting cells using machine learning. A biological cell analysis sorting machine, wherein the biological cell analysis sorting machine comprises a flow cytometry system and a cell analytics sorting system, may be configured to detect configuration issues by analyzing results of a sorting experiment performed by the biological cell analysis sorting machine. An analysis of a history of prior sorting experiments and associated configuration settings may be performed and a corpus of documents pertaining to the sorting experiment based on the detected configuration issues may be analyzed. Updated configuration settings for the biological cell analysis sorting machine based on the performed analysis may be determined, and the biological cell analysis sorting machine may be configured with the updated configuration settings to conduct a desired sorting experiment.

Abstract: Computer based methods, systems, and computer readable media for intelligently accessing various types of pharmaceutical information in a content repository and ranking drugs at the variant level, gene level, and pathway level. In some cases, drugs that target the same gene, gene variant, or biological pathway may be ranked based upon in vitro, pre-clinical, clinical, or post-clinical evidence. To determine ranking of a plurality of drugs, information pertaining to drug administration is analyzed for the drugs. For a plurality of drugs, attributes corresponding to the drug are determined, wherein the attributes include a variant or a gene targeted by the drug, and a biological pathway comprising the targeted variant or gene. The plurality of drugs are ranked according to a drug effectiveness score based on one or more of a determined efficacy, potency, or toxicity.

Abstract: A computer system processes documents in a content repository. Each document of a plurality of documents is classified into one of a functional category and a clinical category. Each document is annotated using one or more corpora to generate document annotations. Documents satisfying one or more query terms are identified by comparing each query term to the document annotations. The identified documents are ranked based on a determined relevance. Guidelines are produced based on the ranking of the identified documents. Embodiments of the present invention further include a method and program product for processing documents in a content repository in substantially the same manner described above.

Abstract: Techniques are provided for administering combination of drug treatments to a patient. Information is analyzed pertaining to individual drug treatments from structurally or functionally defined drugs, drugs with unknown functions, and corresponding effects, wherein the information includes omic data including genes, transcripts, proteins, as well as experimental data from published documents. One or more combinations of drug treatments are identified with combined effects producing a positive result, wherein the positive result is directed to a specific aspect of patient health. The identified combination of drug treatments are administered to a patient.

Abstract: Computer-based methods, systems, and computer readable media for managing documents within a content repository or documents within the document subsets are provided. Documents within the content repository may be classified into one of a functional category and a clinical category. Documents are applied to a machine learning annotation and analysis module to automatically annotate the documents to indicate relationships between entities. A request is processed for the documents including one or more search terms, wherein the search terms pertain to one or more entities from a group of gene, gene variant, drug, cancer and a biomedical/clinical term. Documents satisfying the request are identified by comparing the one or more search terms to the annotations and specific sections of the documents, and determining a relevance of a document based on the comparison and a frequency of the one or more search terms in each of the specific sections. The identified documents are ranked according to custom techniques.

Abstract: Computer-based methods, systems, and computer readable media for managing documents within a content repository or documents within the document subsets are provided. Variant annotations within the documents may be normalized to a standard nomenclature. A request is processed for the documents including one or more search terms, where the search terms pertain to one or more from a group of genes/gene variants, drugs, and cancer terms. Documents are identified that satisfy the request by comparing the one or more search terms to the normalized annotations and specific sections of the documents, and determining a relevance of a document based on the comparison and a frequency of the one or more search terms in each of the specific sections. The identified documents are ranked in accordance with a priority based on the determined relevance.

Abstract: According to embodiments of the present invention, methods, systems and computer readable media are provided for extracting related medical information from various sources to produce a medical evaluation. Genomic information provided from a patient tumor sample is analyzed to determine the presence of one or more mutations in the tumor sample. Hierarchical matching is performed to match the one or more mutations from the patient sample to curated structured data derived from literature. One or more of a prognosis, diagnosis, or predisposition is evaluated based on the matching, wherein the one or more mutations is predictive of a prognosis for a type of tumor, and is a diagnostic marker of a type of tumor. When a pathogenic mutation is detected for a predisposition, a report is generated regarding whether the pathogenic mutation is associated with hereditary cancer.