Abstract: According to an embodiment, provided is a method of managing a state after automatically injecting medicine, including: installing, by a first user terminal, a drug injection program received from a management server thereon; receiving, by the first user terminal, at least one from usage data of a drug injection device, a drug injection message, a biometric value measurement message, and a device state message from a controller via the drug injection program; receiving, by the first user terminal, an input of a risk alarm setting information from a user and transmitting the risk alarm setting information to the controller; receiving, by the first user terminal, a risk signal corresponding to the risk alarm setting information from the controller; and determining, by the first user terminal, a manager according to the risk signal, and transmitting a risk alarm message to a terminal of the manager according to the risk signal or a risk management center.

Abstract: Provided herein are methods and systems of molecular profiling of diseases, such as cancer. In some embodiments, the molecular profiling can be used to identify treatments for a disease, such as treatments that were not initially identified as a treatment for the disease or not expected to be a treatment for a particular disease.

Abstract: The present invention provides processes for calculating phased genomic sequences of the fetal genome using fetal DNA obtained from a maternal sample. The processes and systems of the present invention utilize novel technological and computational approaches to detect fetal genomic sequences and determine the phased heritable genomic sequences. The invention could be used, e.g., to identify in utero deleterious mutations carried by the parents and inherited by a fetus within a particular heritable genomic region.

Abstract: A computer-implemented method for training a predictive model to predict a probability that an initial state of a subject will develop a subsequent state. The method includes receiving sequence reads, grouping the sequencing reads into families, constructing a molecular state vector for subjects, storing ordered pairs of vectors, and training the predictive model based on the ordered pairs of vectors. The system supports training the predictive model on a genetic profile of a tumor, a patient profile, and/or treatment profiles.

Abstract: The invention disclosed herein generally relates to methods of assessing and monitoring tumor load through analysis of tumor DNA in cancer patients. Quantitative measures derived from cell-free DNA and germline DNA are used to assess and monitor tumor load. By assessing and monitoring tumor load, cancer may be detected in a subject. The tumor load of a subject may be assessed at a number of different time points to monitor a progression, regression, or recurrence of cancer in a subject.

Abstract: The present invention discloses an automated sterility testing assembly that has a plug actuator and a processor configured to determine that at least one pump is finished drawing a pharmaceutical product and a rinsing fluid into a fluid inlet of a test container via tubing. The tubing fluidly couples a needle to the fluid inlet of the test container with the needle being configured to pierce a closure of a first container. The test container is configured to receive the pharmaceutical fluid and bacterial growth media to facilitate testing sterility of the pharmaceutical fluid. The processor causes the plug actuator to couple a plug to the fluid outlet of the test container based on the determination that drawing the rinsing fluid is finished.

Abstract: The disclosed computerized system and method facilitates predicting the onset of diabetes or symptom progression in those patients already suffering from the disease. The computerized system and method applies steps to segment the population by predefined member characteristics. Once segmented, the computerized system and method applies a plurality of prediction models to the segmented population data to provide a ranking of members of the population that indicates the likelihood of onset or progression of diabetes for each member.

Abstract: Systems, methods, and computer programs for analyzing genetic sequence data is disclosed. In one aspect, the system can include one or more of a first integrated circuit, with each first integrated circuit forming a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of a sequence analysis pipeline. Additionally, the system can include one or more second integrated circuits, with each second integrated circuit forming a field programmable gate array (FPGA). The FPGA can be configured by firmware to arrange a set of hardwired digital logic circuits to perform a second set of genomic processing stages of the sequence analysis pipeline, the set of hardwired digital logic circuits of each FPGA being arranged as a set of processing engines to perform the second set of genomic processing stages.

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: Provided herein are methods and systems of molecular profiling of diseases, such as cancer. In some embodiments, the molecular profiling can be used to identify treatments for a disease, such as treatments that were not initially identified as a treatment for the disease or not expected to be a treatment for a particular disease.

Abstract: Biomarkers and methods using the biomarkers for the prediction of the recurrence risk of cancer in a patient are provided.

Abstract: Methods for targeting a tumor antigen for immunotherapy based on HLA allele type and the mutations present in the tumor antigen are presented. A patient's HLA allele type and a tumor antigen derived from a mutation in cancer driver gene can be matched with a majority allele type having a minimum affinity to the same tumor antigen or with those of a plurality of patients with a history of cancer treatment. Upon matching, a cancer treatment against the tumor antigen can be selected and administered to the patient to achieve a desired effect.

Abstract: A system, method and apparatus for executing a sequence analysis pipeline on genetic sequence data includes an integrated circuit formed of a set of hardwired digital logic circuits that are interconnected by physical electrical interconnects. One of the physical electrical interconnects forms an input to the integrated circuit connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits are arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired digital logic circuits to perform one or more steps in the sequence analysis pipeline on the reads of genomic data. Each subset of the hardwired digital logic circuits is formed in a wired configuration to perform the one or more steps in the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a sequence analysis pipeline on genetic sequence data includes a integrated circuit formed of a set of hardwired digital logic circuits that are interconnected by physical electrical interconnects. One of the physical electrical interconnects forms an input to the integrated circuit connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits are arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired digital logic circuits to perform one or more steps in the sequence analysis pipeline on the reads of genomic data. Each subset of the hardwired digital logic circuits is formed in a wired configuration to perform the one or more steps in the sequence analysis pipeline.

Abstract: Methods and systems are provided for identifying drug compounds for targeting proteins in tissue cells. Such a method includes providing a neural network model which comprises an attention-based protein encoder and a molecular decoder. The protein encoder is pretrained in an autoencoder architecture to encode an input protein sequence into an output vector in a latent space representing proteins. The molecular decoder is pretrained in an autoencoder architecture to generate compound data, defining a compound molecule, from an input vector in a latent space representing molecules. The protein encoder and molecular decoder are coupled such that the input vector of the molecular decoder is dependent on the output vector of the protein encoder for an input protein sequence.

Abstract: A method for generating digital setups for an orthodontic treatment path. The method includes receiving a digital 3D model of teeth, performing interproximal reduction (IPR) on the model and, after performing the IPR, generating an initial treatment path with stages including an initial setup, a final setup, and a plurality of intermediate setups. The method also includes computing IPR accessibility for each tooth at each stage of the initial treatment path, applying IPR throughout the initial treatment path based upon the computed IPR accessibility, and dividing the initial treatment path into steps of feasible motion of the teeth resulting in a final treatment path with setups corresponding with the steps. The setups can be used to make orthodontic appliances, such as clear tray aligners, for each stage of the treatment path.

Abstract: Methods and apparatus for obtaining representations of proteins and small molecule drugs for synthesis; wherein input queries into trained mixed modality protein and natural language models are augmented with relevant query-related documents. In one embodiment, the relevant query-related documents are obtained by maximum inner product search of an embedding latent vector space into which the query and the documents are projected. The top-k most relevant documents to the query are then combined with the query as input into the trained mixed modality language model. In one embodiment, the mixed modality model is an autoregressive multicapitate transformer whose decoder output heads correspond to the represented modalities. The method returns mixed modality output representations of proteins or small molecule drugs for synthesis or manufacture.

Abstract: A method for nucleic acid sequencing includes receiving a plurality of observed or measured signals indicative of a parameter observed or measured for a plurality of defined spaces; determining, for at least some of the defined spaces, whether the defined space comprises one or more sample nucleic acids; processing, for at least some of the defined spaces, the observed or measured signal to improve a quality of the observed or measured signal; generating, for at least some of the defined spaces, a set of candidate sequences of bases for the defined space using one or more metrics adapted to associate a score or penalty to the candidate sequences of bases; and selecting the candidate sequence leading to a highest score or a lowest penalty as corresponding to the correct sequence for the one or more sample nucleic acids in the defined space.

Abstract: The present disclosure provides methods for determining a probability that after any of a number of therapeutic interventions, an initial state of a subject, such as somatic cell mutational status of a subject with cancer, will develop a subsequent state. Such probabilities can be used to inform a health care provider as to particular courses of treatment to maximize probability of a desired outcome for the subject.

Abstract: Time-series data formed by acquiring values indicating amounts or states of a plurality of biological materials for each biological material at a plurality of time points is prepared, the plurality of biological materials are divided into a plurality of groups on the basis of temporal variations of time-series data of the respective biological materials, representative time-series data indicating a state of each group is generated on the basis of time-series data of at least one biological material included in each group, and dependencies between the groups are estimated on the basis of the representative time-series data of each group.