Abstract

The present disclosure provides methods involving the use of modified magnetic beads for molecular archiving of nucleic acid molecules isolated from a biological sample, such as cell-free DNA (cfDNA). The modified magnetic bead compositions disclosed herein efficiently captured nucleic acid molecules (e.g., DNA) via electrostatic catalysis to generate nucleic acid libraries for iterative molecular analysis.

IPC Classes  ?

• C12Q 1/6806 - Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay
• C12Q 1/6811 - Selection methods for production or design of target specific oligonucleotides or binding molecules
• C12Q 1/6844 - Nucleic acid amplification reactions

Abstract

The presently disclosed subject matter provides antibodies or antigen-binding fragments thereof that bind to L1CAM and methods of using such antibodies or antigen-binding fragments thereof. The presently disclosed subject further provides immunoconjugates comprising anti-L1CAM antibodies or antigen-binding fragments thereof and methods of using such immunoconjugates.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 47/68 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the non-active ingredient being a modifying agent the modifying agent being an antibody, an immunoglobulin or a fragment thereof, e.g. an Fc-fragment
• A61P 35/00 - Antineoplastic agents
• G01N 33/68 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving proteins, peptides or amino acids

Abstract

The presently disclosed subject matter provides for antigen-recognizing receptors that specifically target B7-H3 and cells comprising such B7-H3-targeted antigen-recognizing receptors. The presently disclosed subject matter further provides uses of the B7-H3-targeted antigen-recognizing receptors for treatment.

IPC Classes  ?

• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens
• A61P 35/00 - Antineoplastic agents
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells

Abstract

The present disclosure is directed to leucine zipper-based sorting systems adapted to facilitate the expression and coordination of polypeptide sequences capable of improving the function of CAR T cells. The systems enable the generation of T cells engineered to express multiple combinations of CARs (multi-CAR), safety-switches, switch receptors, and/or cytokines.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens
• A61P 35/02 - Antineoplastic agents specific for leukemia
• A61P 37/04 - Immunostimulants
• C07K 14/725 - T-cell receptors
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C12N 5/00 - Undifferentiated human, animal or plant cells, e.g. cell linesTissuesCultivation or maintenance thereofCulture media therefor
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• C12N 9/64 - Proteinases derived from animal tissue, e.g. rennin

Abstract

We have discovered that administering anti-ceramide antibody treats and prevents an array of diseases mediated by cytolytic T lymphocyte (CTLs)-induced killing and by damage to endothelial microvasculture, including radiation-induced GI syndrome, Graft vs. Host diseases, inflammatory diseases and autoimmune diseases. We have also discovered new anti-ceramide monoclonal antibodies, that have therapeutic use preferably in humanized form to treat or prevent these diseases.

IPC Classes  ?

• A61K 31/55 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having seven-membered rings, e.g. azelastine, pentylenetetrazole
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C07K 16/40 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against enzymes
• C07K 16/44 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material not provided for elsewhere

Abstract

Presented herein are systems and methods of generating frames across time from sequence data using machine learning (ML) models. A computing system coupled with memory can retrieve a sequence dataset comprising a plurality of identifiers generated using a gene segment from a subject at a first time. Each identifier of the plurality of identifiers can have an alphanumeric character indicating a base type at a respective position in the gene segment. The computing system can convert the plurality of the identifiers of the sequence dataset to generate a first frame comprising a first plurality of coordinates for the gene segment at the first time. The computing system can provide the first frame as an input to a ML model. The computing system can generate, based on providing the input to the ML model, a second frame comprising a second plurality of coordinates for the gene segment at a second time.

IPC Classes  ?

• G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• G16B 30/00 - ICT specially adapted for sequence analysis involving nucleotides or amino acids
• G06N 20/00 - Machine learning
• G06T 7/00 - Image analysis
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• C12Q 1/6874 - Methods for sequencing involving nucleic acid arrays, e.g. sequencing by hybridisation [SBH]

Abstract

Presented herein are systems and methods relating to imputing metabolite information. A method includes receiving a first and second metabolite dataset, normalizing, the first dataset and the second dataset, transforming, the normalized first and second datasets, and aggregating the normalized first dataset and the normalized second dataset to generate a first metabolite matrix, the first metabolite matrix missing a first relative abundance value. The method includes decomposing the first metabolite matrix into a second metabolite matrix and a third metabolite matrix to factorize the first metabolite matrix and generating a fourth metabolite matrix that is the product of the second metabolite matrix and the third metabolite matrix, wherein the fourth metabolite matrix including an imputed first relative abundance value.

IPC Classes  ?

• G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks

Abstract

Provided are compounds for activating TFEB, the compounds being according to Formula (I) or Formula (II) as well as pharmaceutical compositions including such compounds and methods for using the compounds for the treatment of diseases and disorders.

IPC Classes  ?

• C07D 243/06 - Heterocyclic compounds containing seven-membered rings having two nitrogen atoms as the only ring hetero atoms having the nitrogen atoms in positions 1 and 4
• C07D 243/08 - Heterocyclic compounds containing seven-membered rings having two nitrogen atoms as the only ring hetero atoms having the nitrogen atoms in positions 1 and 4 not condensed with other rings
• A61K 31/496 - Non-condensed piperazines containing further heterocyclic rings, e.g. rifampin, thiothixene or sparfloxacin
• A61K 31/33 - Heterocyclic compounds

Abstract

The present technology relates to methods, computing devices, and systems for predicting the fitness of mutant p53 based on the loss of transcription factor function and immunogenicity of a particular TP53 mutation. The fitness of mutant p53 may be used to determine whether a patient will benefit from a particular anti-cancer therapy such as immune checkpoint inhibitor therapy, adoptive T-cell therapy, or prophylactic cancer vaccine therapy.

IPC Classes  ?

• G16H 20/17 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• G16B 15/30 - Drug targeting using structural dataDocking or binding prediction
• G16B 20/10 - Ploidy or copy number detection
• G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• G16B 20/50 - Mutagenesis

Abstract

Presented herein is a sensor platform which can be used for the detection of arbitrary molecules of interest or for clinical diagnosis using test solutions. The sensor may include an array of environmentally sensitive fluorescent reporter probes. Each probe is placed on a separate pixel or several pixels of the sensor array and has a different coating, such that it responds slightly differently to environmental stimuli than every other pixel upon addition of the test solution.

IPC Classes  ?

• G01N 21/64 - FluorescencePhosphorescence
• G01N 33/53 - ImmunoassayBiospecific binding assayMaterials therefor
• G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer
• G01N 33/58 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving labelled substances
• G01N 33/84 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving inorganic compounds or pH
• B82Y 20/00 - Nanooptics, e.g. quantum optics or photonic crystals
• G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• G01N 21/77 - Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator

Abstract

The present disclosure provides methods for accurately predicting the risk of recurrence and metastases in lung cancer (e.g., lung adenocarcinoma) patients using ctDNA and 'spread through air spaces' (STAS) biomarkers.

IPC Classes  ?

• G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
• G06N 20/00 - Machine learning
• G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
• G16B 30/00 - ICT specially adapted for sequence analysis involving nucleotides or amino acids
• G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• G16H 10/60 - 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
• G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture

Abstract

Presented herein are systems, methods, and non-transient computer readable media for determining predicted response scores of subjects. A computing system may identify a first feature set for a first subject to be administered with immunotherapy to address a condition. The first feature set may include one or more of: (i) a first radiological feature identified in a tomogram of a section associated with the condition in the first subject, (ii) a first immunohistochemistry (IHC) feature derived from an image of a sample associated with the first subject, and (iii) a first genomic feature obtained from gene sequencing of the first subject for genes associated with the condition. The computing system may apply the first feature set to a model. The computing system may determine, from applying the first feature set to the model, a predicted score identifying a response to the immunotherapy to be administered to the first subject.

IPC Classes  ?

• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G06T 7/00 - Image analysis
• G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Aspects of the disclosure provide compositions and methods for reversible expression of a target gene. In some aspects, the disclosure provides nucleic acids comprising multiple pairs of recombinase sites, each pair having first and second members flanking an inverted expression cassette encoding a target gene.

IPC Classes  ?

• C12N 9/22 - Ribonucleases
• C12N 15/67 - General methods for enhancing the expression

Abstract

Provided herein are chimeric innate receptor (OR) fusion proteins that enhance the persistence of NK and NK-like T cells in response to AML antigens, such as CD33. The OR fusion proteins of the present technology are useful in methods for treating cancer, such as AML. The OR fusion proteins of the present technology are useful in methods for treating AML.

IPC Classes  ?

• A61K 40/42 - Cancer antigens
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants

Abstract

The present application is directed to multiplex intein-based methods and compositions for the generation engineered cells expressing modular polypeptides, for example CARs and CCRs.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens

Abstract

The present disclosure relates to compounds according to Formula I: or a pharmaceutically acceptable salt thereof, as well as compositions including such compounds and uses thereof. As evidenced by this application, these compounds and compositions are suitable for, among other things, treating cancer.

IPC Classes  ?

• C07F 5/02 - Boron compounds
• A61K 47/68 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the non-active ingredient being a modifying agent the modifying agent being an antibody, an immunoglobulin or a fragment thereof, e.g. an Fc-fragment
• A61K 47/69 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the conjugate being characterised by physical or galenical forms, e.g. emulsion, particle, inclusion complex, stent or kit
• A61P 35/00 - Antineoplastic agents

Abstract

Presented herein are systems, devices, and methods for shortwave infrared (SWIR) fluorescence imaging. The device may include a housing defining an aperture, an optical component having a first end structured to be optically coupled with the aperture of housing, a second end structured to be distal from the housing, the second end configured to accept at least a portion of light having a SWIR wavelength emitted by a fluorophore in at least a target area of an object, and a body configured to convey the light from the second end to the first end, and a sensor disposed within the housing, the sensor optically coupled with the optical component via the aperture, the sensor configured to convert the light to an electrical signal corresponding to the light.

IPC Classes  ?

• G01N 21/64 - FluorescencePhosphorescence
• G01N 21/359 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light

Abstract

Presented herein is an imaging technique named nonstop gated cone-beam computer tomograph (CBCT), for guiding free-breathing respiratory gating radiotherapy of thoracic and abdominal cancer patients (e.g., lung, liver, pancreas). The nonstop gated CBCT technique reduces the data acquisition time to 1 minute and decreases the imaging dose by >40% while simultaneously retaining high quality images was developed. This is done by allowing the gantry to rotate continuously and having the kV x-ray beam on when the patient breathing signal is within the respiratory gate and the x-ray beam off when it is out of the respiratory gate. A machine learning model can be used to reconstruct high-quality CBCT images from the acquired data.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• G06T 11/00 - 2D [Two Dimensional] image generation
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
• G06N 20/00 - Machine learning
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

The present disclosure provides chimeric cell-penetrating polypeptides, barcodes, conjugates comprising a cargo moiety and a chimeric cell-penetrating polypeptide described herein, alone or in combination with a barcode of the present technology, and methods of using the conjugates to monitor delivery of the cargo moiety into target tissues or cells.

IPC Classes  ?

• C07K 14/47 - Peptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from animalsPeptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from humans from vertebrates from mammals
• A61K 47/64 - Drug-peptide, drug-protein or drug-polyamino acid conjugates, i.e. the modifying agent being a peptide, protein or polyamino acid which is covalently bonded or complexed to a therapeutically active agent

Abstract

Presented herein are systems and methods of determining density values from mammograms. A computing system may identify a first mammogram of a first breast region of a first subject. The first mammogram may have a first region of interest (ROI) corresponding to a first dense area of the first breast region. The computing system may apply the first mammogram to a machine learning (ML) model to generate a first segmentation map identifying the first ROI within the first mammogram. The computing system may determine a density value for the first dense area of the first breast region based on the first segmentation map.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/11 - Region-based segmentation
• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment

Abstract

The present disclosure relates generally to compositions comprising an antibody-drug conjugate comprising an anti-TROP-2 antibody or antigen binding fragment thereof and methods for using the same to treat diffuse pleural mesothelioma (DPM).

IPC Classes  ?

• A61K 47/68 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the non-active ingredient being a modifying agent the modifying agent being an antibody, an immunoglobulin or a fragment thereof, e.g. an Fc-fragment
• C07K 16/30 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• A61P 35/00 - Antineoplastic agents

Abstract

Presented herein are systems and methods for determining scores related to metastatic recurrence of cancers in subjects using multimodal machine learning (ML) architectures. A computing system may obtain, for a subject at risk of recurrence of cancer, a dataset comprising at least one of: (i) a biomedical image of a tissue sample from an organ associated with the cancer or (ii) a text report identifying a plurality of characteristics of a tumor associated with the cancer. The computing system may apply an ML architecture to at least one of the biomedical image or the text report of the dataset. The computing system may determine, based on applying the ML architecture, a score indicating a likelihood of recurrence associated with cancer in the subject. The computing system may generate a classification of the subject for administration of a therapy for the cancer, in accordance with the score.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• G06T 7/00 - Image analysis
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• G06V 10/771 - Feature selection, e.g. selecting representative features from a multi-dimensional feature space
• G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• G06N 3/02 - Neural networks
• G06N 20/00 - Machine learning
• G06F 18/211 - Selection of the most significant subset of features
• G06F 18/25 - Fusion techniques
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

The presently disclosed subject matter provides novel T cell receptors (TCRs) that target an EWSR1/WT1 fusion protein. The presently disclosed subject matter further provides cells comprising such TCRs, and methods of using such cells for treating cancers associated with EWSR1/WT1 fusion protein.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/15 - Natural-killer [NK] cellsNatural-killer T [NKT] cells
• A61K 40/32 - T-cell receptors [TCR]
• A61K 40/42 - Cancer antigens
• A61P 35/00 - Antineoplastic agents
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• C07K 16/32 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against translation products from oncogenes
• C12N 15/86 - Viral vectors
• C12N 15/88 - Introduction of foreign genetic material using processes not otherwise provided for, e.g. co-transformation using microencapsulation, e.g. using liposome vesicle

Abstract

Systems and methods for HDR brachytherapy planning can include obtaining patient specific data of a patient, and determining, using the patient specific data, an optimization problem to solve for a single-fraction HDR monotherapy plan including an objective function to be optimized subject to one or more first constraints on radiation doses within one or more OAR regions and a second constraint on radiation doses within the PTV. The systems and methods can include optimizing the objective function subject to the one or more first constraints and the second constraint, determining whether the first single-fraction HDR monotherapy plan satisfies the first and second constraints, updating a bound value of the second constraint based on whether the first single-fraction HDR monotherapy plan satisfies the first and second constraints, and optimizing the objective function subject to the one or more first constraints and the second constraint with the updated bound value.

IPC Classes  ?

• A61N 5/10 - X-ray therapyGamma-ray therapyParticle-irradiation therapy

Abstract

Presented herein are systems, methods, and non-transient computer readable media for determining risk scores using multimodal feature sets. A computing system may identify a first feature set for a first subject at risk of a condition. The first feature set may include (i) a first radiological feature derived from a tomogram of a section associated with the condition within the first subject, (ii) a first histologic feature acquired using a whole slide image of a sample having the condition from the first subject, and (iii) a first genomic feature obtained from gene sequencing of the first subject for genes associated with the condition. The computing system may apply the first feature set to a model. The computing system may determine, from applying the first feature set to the model, a predicted risk score of the condition for the first subject.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• G06T 7/00 - Image analysis
• G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection

Abstract

Presented herein is a pipeline, integrating deep learning and language models to improve efficiency and accuracy in radiologist's workflow, as well as generate robust structured data abstracting patient's MRIs. A universally compatible pipeline can be integrated across major clinical platforms and shared with various institutions, marking a pivotal step towards reducing radiologist human error.

IPC Classes  ?

• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
• G06V 10/40 - Extraction of image or video features
• G06N 20/00 - Machine learning
• G06V 10/00 - Arrangements for image or video recognition or understanding

Abstract

The presently disclosed subject matter provides cells, compositions and methods for enhancing immune responses toward tumor antigens. It relates to cells comprising a first antigen-recognizing receptor that targets CD70. These cells have improved activity and/or efficiency.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• C07K 14/725 - T-cell receptors
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells

Abstract

Presented herein are systems and methods of determining predicted outcomes of subjects with cancer from biomedical images. A computing system may identify a biomedical image of a tissue sample from a subject with cancer. The biomedical image may have (i) a first region of interest (ROI) corresponding to viable tumor and (ii) a second ROI corresponding to necrotic tumor in the tissue sample. The computing system may apply a machine learning model to the biomedical image to determine (i) a first segment identifying the first ROI and (ii) a second segment identifying the second ROI. The computing system may determine a ratio between a first size of the first segment associated with the viable tumor and a second size of the second segment associated with the necrotic tumor. The computing system may generate a value indicative of a predicted outcome of the cancer in the subject using the ratio.

IPC Classes  ?

• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G06T 7/00 - Image analysis
• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The presently disclosed subject matter provides cells, compositions and methods for enhancing immune responses toward tumor antigens. It relates to cells comprising a first antigen-recognizing receptor (e.g., a chimeric antigen receptor (CAR)) and a second antigen-recognizing receptor (e.g., a TCR-like fusion molecule). These cells have improved activity and/or efficiency.

IPC Classes  ?

• A61K 40/42 - Cancer antigens
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• C07K 14/725 - T-cell receptors
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants

Abstract

The presently disclosed subject matter provides for chimeric receptors that target ADGRE2 and chimeric receptors that target CLEC12A. The presently disclosed subject matter also provides for cells comprising the ADGRE2-targeted chimeric receptors, cells comprising the CLEC12A-targeted chimeric receptors, and cells comprising the ADGRE2-targeted chimeric receptors and the CLEC12A-targeted chimeric receptors. The presently disclosed subject matter further provides uses of such cells for treating tumors, e.g., AML.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 38/00 - Medicinal preparations containing peptides
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens
• A61P 35/00 - Antineoplastic agents
• A61P 35/02 - Antineoplastic agents specific for leukemia
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• C07K 14/725 - T-cell receptors

Abstract

A neoantigen model discrimination method to determine if the immune system can discriminate it from “self” by estimating if a neoantigen has sufficient antigenic distance from its wild-type peptide to differentially bind the MHC or activate a T cell. In one embodiment, a model can be integrated to estimate the fitness of tumor clones as the aggregate of the cost due to T cells recognizing high quality neoantigens offset by the gain from mutations in canonical oncogenes. In an additional embodiment, a model can be used to rationally identify antigens that either elicit desired, or prevent undesired responses of any immunologically based medicine.

IPC Classes  ?

• G16H 20/17 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
• C12Q 1/6881 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for tissue or cell typing, e.g. human leukocyte antigen [HLA] probes
• G16B 20/10 - Ploidy or copy number detection
• G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection

Abstract

Provided herein are compositions, kits, and methods for manufacturing cells for adoptive cell therapy comprising engineered immune cells that overexpress Glucose Transporter 5 (GLUTS).

IPC Classes  ?

• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/42 - Cancer antigens
• A61P 35/00 - Antineoplastic agents
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells

Abstract

The present technology relates generally to compounds, compositions, and methods useful for treating, preventing, and/or ameliorating pathogenic cellular proliferation, angiogenesis, cancer, metastatic disease, and/or a pathogenic vascular proliferative disease in a subject.

IPC Classes  ?

• C07C 217/62 - Compounds containing amino and etherified hydroxy groups bound to the same carbon skeleton having etherified hydroxy groups bound to carbon atoms of at least one six-membered aromatic ring and amino groups bound to acyclic carbon atoms or to carbon atoms of rings other than six-membered aromatic rings of the same carbon skeleton with amino groups linked to the six-membered aromatic ring, or to the condensed ring system containing that ring, by carbon chains not further substituted by singly-bound oxygen atoms linked by carbon chains having at least three carbon atoms between the amino groups and the six-membered aromatic ring or the condensed ring system containing that ring
• A61K 31/137 - Arylalkylamines, e.g. amphetamine, epinephrine, salbutamol, ephedrine
• A61K 31/343 - Heterocyclic compounds having oxygen as the only ring hetero atom, e.g. fungichromin having five-membered rings with one oxygen as the only ring hetero atom, e.g. isosorbide condensed with a carbocyclic ring, e.g. coumaran, bufuralol, befunolol, clobenfurol, amiodarone
• A61K 31/444 - Non-condensed pyridinesHydrogenated derivatives thereof containing further heterocyclic ring systems containing a six-membered ring with nitrogen as a ring hetero atom, e.g. amrinone
• A61P 35/00 - Antineoplastic agents
• A61P 35/04 - Antineoplastic agents specific for metastasis
• C07C 211/52 - Compounds containing amino groups bound to a carbon skeleton having amino groups bound to carbon atoms of six-membered aromatic rings of the carbon skeleton having amino groups bound to only one six-membered aromatic ring the carbon skeleton being further substituted by halogen atoms or by nitro or nitroso groups
• C07D 213/38 - Radicals substituted by singly-bound nitrogen atoms having only hydrogen or hydrocarbon radicals attached to the substituent nitrogen atom
• C07D 317/58 - Radicals substituted by nitrogen atoms

Abstract

Presented herein are systems, methods, and non-transient computer readable media for determining radiation therapy dosages to administer. A computing system may identify a first dataset comprising: (i) a biomedical image derived from a first sample to be administered with radiotherapy and (ii) an identifier corresponding to an organ from which the first sample is obtained. The computing system may apply, to the first dataset, a machine learning (ML) model comprising a plurality of weights trained using a plurality of second datasets in accordance with a moment loss for each of a plurality of organs. The computing system may determine, from applying the first dataset to the ML model, a radiation therapy dose to administer to the sample from which the biomedical image is derived. The computing system may store an association between the first dataset and the radiation therapy dose.

IPC Classes  ?

• A61N 5/10 - X-ray therapyGamma-ray therapyParticle-irradiation therapy
• G06N 20/00 - Machine learning
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

Abstract

The presently disclosed subject matter provides anti-CD40 antibodies or antigen-binding fragments thereof, anti-CD40 Fc fusion proteins (e.g., scFv-Fc fusion proteins binding to CD40), cells comprising the anti-CD antibodies or antigen-binding fragments thereof, cells comprising the anti-CD40 Fc fusion proteins, compositions comprising such cells, and methods of using such cells and compositions for diagnosis and therapies.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61P 35/00 - Antineoplastic agents

Abstract

The presently disclosed subject matter provides novel T cell receptors (TCRs) that target a mutated RAS protooncogene. The presently disclosed subject matter further provides cells comprising such TCRs, and methods of using such cells for treating cancers associated with RAS.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/15 - Natural-killer [NK] cellsNatural-killer T [NKT] cells
• A61K 40/32 - T-cell receptors [TCR]
• A61K 40/42 - Cancer antigens
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• C07K 14/73 - CD4
• C07K 16/40 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against enzymes
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• C12N 15/86 - Viral vectors

Abstract

The present disclosure provides compositions comprising IFNE and methods of using the same to treat cancer and/or enhancing responsiveness to immune checkpoint blockade therapy in a patient in need thereof. Also disclosed herein are compositions including tandem bicistronic expression cassettes, and methods of using the same to generate large genomic deletions and/or knock-in gene alterations.

IPC Classes  ?

• A61K 48/00 - Medicinal preparations containing genetic material which is inserted into cells of the living body to treat genetic diseasesGene therapy
• A61K 38/21 - Interferons
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61P 35/00 - Antineoplastic agents
• C12N 9/22 - Ribonucleases
• C12N 15/11 - DNA or RNA fragmentsModified forms thereof
• C12N 15/90 - Stable introduction of foreign DNA into chromosome

Abstract

The presently disclosed subject matter provides methods for improving the production of cells comprising an antigen-recognizing receptor (e.g., a chimeric antigen receptor (CAR) or a TCR like fusion molecule). The methods disclosed herein can improve the activity and/or efficiency of the cells.

IPC Classes  ?

• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• A61K 40/11 - T-cells, e.g. tumour infiltrating lymphocytes [TIL] or regulatory T [Treg] cellsLymphokine-activated killer [LAK] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens
• A61P 35/00 - Antineoplastic agents
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C07K 16/30 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells

Abstract

The present disclosure provides methods for simultaneously identifying dynamic and disease-associated RNA binding protein (RBP)-RNA interaction (PRI) sites at single nucleotide resolution across the entire transcriptome. The methods disclosed herein recapitulates PRI profiles obtained with several distinct conventional PRI methods in a single assay at efficiencies that are improved by orders of magnitude, and permit the identification of the specific RBP bound at a PRI.

IPC Classes  ?

• C12N 15/10 - Processes for the isolation, preparation or purification of DNA or RNA
• C12N 9/12 - Transferases (2.) transferring phosphorus containing groups, e.g. kinases (2.7)
• C12N 9/22 - Ribonucleases
• C12N 9/50 - Proteinases
• C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganismsCompositions thereforProcesses of preparing such compositions involving nucleic acids
• G01N 33/52 - Use of compounds or compositions for colorimetric, spectrophotometric or fluorometric investigation, e.g. use of reagent paper
• B01D 15/38 - Selective adsorption, e.g. chromatography characterised by the separation mechanism involving specific interaction not covered by one or more of groups , e.g. affinity, ligand exchange or chiral chromatography

Abstract

The present disclosure provides methods for determining whether a cancer patient with homologous recombination deficiency will benefit from treatment with PARP inhibitors or platinum agents. These methods are based on screening a cancer patient for the presence of templated insertions (TINS), including direct-repeat templated insertions (drTINS) and inverted templated insertions (iTINS).

IPC Classes  ?

• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• A61K 31/166 - Amides, e.g. hydroxamic acids having aromatic rings, e.g. colchicine, atenolol, progabide having the carbon atom of a carboxamide group directly attached to the aromatic ring, e.g. procainamide, procarbazine, metoclopramide, labetalol
• A61K 31/282 - Platinum compounds
• A61K 31/4184 - 1,3-Diazoles condensed with carbocyclic rings, e.g. benzimidazoles
• A61K 31/454 - Non-condensed piperidines, e.g. piperocaine containing further heterocyclic ring systems containing a five-membered ring with nitrogen as a ring hetero atom, e.g. pimozide, domperidone
• A61K 31/502 - PyridazinesHydrogenated pyridazines ortho- or peri-condensed with carbocyclic ring systems, e.g. cinnoline, phthalazine
• A61K 31/5025 - PyridazinesHydrogenated pyridazines ortho- or peri-condensed with heterocyclic ring systems
• A61K 31/506 - PyrimidinesHydrogenated pyrimidines, e.g. trimethoprim not condensed and containing further heterocyclic rings
• A61K 31/55 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having seven-membered rings, e.g. azelastine, pentylenetetrazole
• A61K 33/243 - PlatinumCompounds thereof
• A61P 35/00 - Antineoplastic agents

Abstract

Disclosed is an approach to large-scale combination drug screens. Example versions employ an active learning platform as part of an orthogonal approach that includes conducting experiments dynamically in batches. Each batch may be designed to be maximally informative based on the results of previous experiments. Example designs have been demonstrated to discover highly effective and synergistic combinations of therapeutics. The disclosed approach provides for models that can identify a panel of top therapeutics ("drug") combinations for various diseases. Results demonstrate that adaptive experiments enable large-scale unbiased combination drug screens with a relatively small number of experiments, thereby powering a new wave of combination drug discoveries.

IPC Classes  ?

• C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganismsCompositions thereforProcesses of preparing such compositions involving nucleic acids
• A61K 31/33 - Heterocyclic compounds
• G06F 18/22 - Matching criteria, e.g. proximity measures
• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
• A61P 35/02 - Antineoplastic agents specific for leukemia
• A61P 43/00 - Drugs for specific purposes, not provided for in groups

Abstract

Presented herein are systems and methods of detecting retinoblastoma using images of eyes. The systems and methods include identifying a first image of at least one first eye of a first subject prior to administration of treatment for retinoblastoma, the at least one eye having a structure of interest corresponding to an abnormality, applying the first image to a machine learning (ML) model established using a training dataset including examples, each of the examples identifying a respective second image of at least one second eye of a second subject and a respective second classification identifying one of presence or absence of retinoblastoma in the at least second eye, determining from applying the ML model, a first classification identifying one of presence or absence of retinoblastoma in the at least one first eye, and storing using one or more data structures, an association between the first subject and the classification.

IPC Classes  ?

• A61B 3/14 - Arrangements specially adapted for eye photography
• A61B 3/12 - Objective types, i.e. instruments for examining the eyes independent of the patients perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
• G06N 3/08 - Learning methods
• G06V 40/19 - Sensors therefor
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Provided herein are compositions, kits, and methods for manufacturing cells for adoptive cell therapy comprising engineered monocytes or engineered monocyte-derived macrophages that overexpress ID3 for the treatment of cancer.

IPC Classes  ?

• C07K 14/47 - Peptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from animalsPeptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from humans from vertebrates from mammals
• C12N 15/85 - Vectors or expression systems specially adapted for eukaryotic hosts for animal cells
• C12N 5/00 - Undifferentiated human, animal or plant cells, e.g. cell linesTissuesCultivation or maintenance thereofCulture media therefor
• A61K 38/17 - Peptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from animalsPeptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from humans
• A61K 40/17 - MonocytesMacrophages
• A61P 35/00 - Antineoplastic agents

Abstract

The present technology generally relates to improved processes for the preparation of (2-(4-(4-(4-(4-aminostyryl)-3-methoxystyryl)phenyIsulfonyl)piperazin- 1 -yljethanol (11), as well as novel intermediates employed in the process, which may be useful as a nen e visualization agent for fluorescence image-guided surgery. The present technology also relates to novel radiolabeled analogs of 11 and compositions, which may have a number of uses, including use as a nerve visualization agent. Also, methods for their synthesis are also included. The present technology further relates to methods of imaging nerves in a surgical field by contacting a surgical site of a subject with a pharmaceutical composition comprising novel radiolabeled analogs of 11 and compositions.

IPC Classes  ?

• A61K 49/06 - Nuclear magnetic resonance [NMR] contrast preparationsMagnetic resonance imaging [MRI] contrast preparations
• A61K 49/08 - Nuclear magnetic resonance [NMR] contrast preparationsMagnetic resonance imaging [MRI] contrast preparations characterised by the carrier
• A61K 51/02 - Preparations containing radioactive substances for use in therapy or testing in vivo characterised by the carrier
• A61K 51/04 - Organic compounds

Abstract

The present disclosure provides methods for predicting responsiveness to IL-2 therapy in patients diagnosed with or suffering from melanoma. These methods are based on screening for expression of membranous MHC class I in tumor cells of untreated lesions.

IPC Classes  ?

• A61K 38/20 - Interleukins
• A61P 35/04 - Antineoplastic agents specific for metastasis
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• G01N 33/68 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving proteins, peptides or amino acids

Abstract

Disclosed herein are compositions including cytotoxic innate lymphoid cells (ILCs), methods for preparing ILCs for adoptive cell therapy, and methods of using ILCs to treat cancer.

IPC Classes  ?

• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61P 35/00 - Antineoplastic agents
• C12N 15/85 - Vectors or expression systems specially adapted for eukaryotic hosts for animal cells

Abstract

Described herein are compositions including killer innate-like T cells (ILTCks), methods for preparing IL TCks for adoptive cell therapy, an methods of using IL TCks to treat cancer. Further, wherein an engineered killer innate-like T cell (ILTCk) comprises a non-endogenous expression vector including a mammalian IL-15 nucleic acid sequence or a mammalian STAT5B nucleic acid sequence is disclosed.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 38/20 - Interleukins
• A61K 40/15 - Natural-killer [NK] cellsNatural-killer T [NKT] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61K 40/42 - Cancer antigens
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61P 35/00 - Antineoplastic agents
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• C12N 15/86 - Viral vectors
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer

Abstract

The present disclosure relates to compounds according to Formula (I), Formula (I) or a pharmaceutically acceptable salt and/or solvate thereof, compositions including such compounds, and methods useful for treating, preventing, and/or ameliorating a CDK4 and/or CDK6-mediated disorder, disease, or condition (e.g., cancer such as breast cancer) in a subject. The present disclosure relates to compounds according to Formula (I), Formula (I) or a pharmaceutically acceptable salt and/or solvate thereof, compositions including such compounds, and methods useful for treating, preventing, and/or ameliorating a CDK4 and/or CDK6-mediated disorder, disease, or condition (e.g., cancer such as breast cancer) in a subject.

IPC Classes  ?

• A61K 31/519 - PyrimidinesHydrogenated pyrimidines, e.g. trimethoprim ortho- or peri-condensed with heterocyclic rings
• A61P 35/00 - Antineoplastic agents
• C07D 471/04 - Ortho-condensed systems

Abstract

The presently disclosed subject matter provides methods for identifying subjects that are responsive or non-responsive to certain adoptive cell therapies or compositions comprising the same. In addition, methods for identifying subjects that have an increased likelihood or a reduced likelihood to response to certain adoptive cell therapies or compositions comprising the same are also provided. Moreover, the presently disclosed subject matter provides cells and compositions comprising a CD19-targeted chimeric receptor.

IPC Classes  ?

• A61P 35/02 - Antineoplastic agents specific for leukemia
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer

Abstract

The present disclosure provides methods for overcoming tazemetostat resistance in patients diagnosed with or suffering from sarcomas. In some embodiments, the methods of the present technology include administering tazemetostat in combination with an ATR inhibitor, a CDK4/6 inhibitor or an AURK inhibitor.

IPC Classes  ?

• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• A61K 31/5377 - 1,4-Oxazines, e.g. morpholine not condensed and containing further heterocyclic rings, e.g. timolol
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer

Abstract

The disclosure provides methods of preventing or treating Type 2 diabetes in a mammalian subject, reducing risk factors associated with Type 2 diabetes, and/or reducing the likelihood or severity of Type 2 diabetes. The methods comprise administering to the subject an effective amount of an inhibitor of PTEN expression and/or activity.

IPC Classes  ?

• C12N 15/113 - Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides
• A61P 3/10 - Drugs for disorders of the metabolism for glucose homeostasis for hyperglycaemia, e.g. antidiabetics
• G01N 33/573 - ImmunoassayBiospecific binding assayMaterials therefor for enzymes or isoenzymes

Abstract

The present disclosure provides compositions for inducing intratumoral CD4 T cell::CD8 T cell::APC triads and methods for using the same to enhance the efficacy of immune checkpoint blockade (ICB) therapy, vaccines, and/or adoptive T cell transfer (ACT) to treat cancer in a subject in need thereof.

IPC Classes  ?

• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 39/12 - Viral antigens
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61K 47/64 - Drug-peptide, drug-protein or drug-polyamino acid conjugates, i.e. the modifying agent being a peptide, protein or polyamino acid which is covalently bonded or complexed to a therapeutically active agent
• A61P 35/00 - Antineoplastic agents
• C12N 7/00 - Viruses, e.g. bacteriophagesCompositions thereofPreparation or purification thereof

Abstract

Disclosed herein are systems and methods based on tumor infiltrating leukocyte (TIL) fractal geometry to predict clinical implications in breast cancer samples. Using machine learning techniques, an algorithmic classifier is constructed and trained on a cohort of tumor images (e.g. radiographic, immunohistochemical (IHC), and H&E images) to discriminate between TILs and cancer cells, and breast cancer samples are classified based on TIL fractal geometry/anatomic distribution in the tumor stroma. Fractal geometry-directed reassessment of classifications may prompt tumor type reclassification resulting in altered cancer therapy.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G06T 7/00 - Image analysis
• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture

Abstract

The presently disclosed subject matter provides methods and compositions for enhancing immune responses toward tumor and pathogen antigens. It relates to fusion polypeptide that can be expressed in cells (e.g., immunoresponsive cells comprising an antigen-recognizing receptor) to improve the activity and/or efficiency of the cells.

IPC Classes  ?

• C07K 14/54 - Interleukins [IL]
• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 38/20 - Interleukins
• A61P 35/00 - Antineoplastic agents
• A61P 35/02 - Antineoplastic agents specific for leukemia

Abstract

The presently disclosed subject matter provides for antigen-recognizing receptors that specifically target DLL3 and cells comprising such DLL3-targeted antigen-recognizing receptors. The presently disclosed subject matter further provides uses of the DLL3-targeted antigen-recognizing receptors for treatment.

IPC Classes  ?

• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 9/51 - Nanocapsules
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• C07K 16/30 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells
• C12N 15/86 - Viral vectors
• A61K 38/20 - Interleukins
• A61P 35/00 - Antineoplastic agents
• C07K 14/54 - Interleukins [IL]

Abstract

Presented herein are systems and methods for determining a likelihood of responsiveness of a subject suffering from cancer to an anti-cancer therapy. A computing system may construct, based on ribonucleic acid (RNA) sequence data, a network. In the network, each node may be associated with a RNA expression and each edge may identify a weight metric between RNA expression levels for a pair of nodes. The computing system may perform, for a plurality of iterations, a diffusion operation throughout the network. The computing system may determine a curvature metric for each iteration using the weight metric defined by each edge or node of the network. The computing system may select a critical iteration based on a difference of curvature metrics. The computing system may apply a plurality of features of the network to a model to generate a score indicating the likelihood of responsiveness of the subject to the anti-cancer therapy.

IPC Classes  ?

• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• A61P 35/00 - Antineoplastic agents
• G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer
• G06N 3/08 - Learning methods
• G06N 20/00 - Machine learning
• G16C 20/70 - Machine learning, data mining or chemometrics
• G16H 10/60 - 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
• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Abstract

The present disclosure provides methods for treating acute myelogenous leukemia (AML) in a subject in need thereof comprising administering to the subject an effective amount of an anti-PD-L1 antibody or antigen binding fragment thereof and cytokine induced memory-like natural killer (CIMN) cells.

IPC Classes  ?

• A61K 39/395 - AntibodiesImmunoglobulinsImmune serum, e.g. antilymphocytic serum
• A61K 40/15 - Natural-killer [NK] cellsNatural-killer T [NKT] cells
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61P 35/02 - Antineoplastic agents specific for leukemia
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes

Abstract

The presently disclosed subject matter provides methods and compositions for enhancing immune responses toward tumor and pathogen antigens. It relates to chimeric receptors that can be expressed in cells (e.g., NK cells) to improve the activity of the cells.

IPC Classes  ?

• C12N 5/0783 - T cellsNK cellsProgenitors of T or NK cells
• C12N 5/10 - Cells modified by introduction of foreign genetic material, e.g. virus-transformed cells
• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 39/395 - AntibodiesImmunoglobulinsImmune serum, e.g. antilymphocytic serum
• C07K 19/00 - Hybrid peptides

Abstract

e.g.e.g.e.g., venetoclax). Kits for use in practicing the methods are also provided.

IPC Classes  ?

• A61K 31/4192 - 1,2,3-Triazoles
• A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
• A61P 35/02 - Antineoplastic agents specific for leukemia
• C12N 15/113 - Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides
• C12Q 1/6827 - Hybridisation assays for detection of mutation or polymorphism
• C12Q 1/6841 - In situ hybridisation
• C12Q 1/686 - Polymerase chain reaction [PCR]
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer

Abstract

e.g.e.g., cancer).

IPC Classes  ?

• C07K 14/715 - ReceptorsCell surface antigensCell surface determinants for cytokinesReceptorsCell surface antigensCell surface determinants for lymphokinesReceptorsCell surface antigensCell surface determinants for interferons
• A61K 38/20 - Interleukins
• A61K 40/31 - Chimeric antigen receptors [CAR]
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure provides (i) methods of improving hematopoietic stem cell transplantation using anti-ceramide antibodies or antigen-binding fragments thereof, for treating various non-malignant and malignant diseases; and (ii) compositions for such treatments.

IPC Classes  ?

• C07K 16/44 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material not provided for elsewhere
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• C12N 5/077 - Mesenchymal cells, e.g. bone cells, cartilage cells, marrow stromal cells, fat cells or muscle cells
• A61K 35/28 - Bone marrowHaematopoietic stem cellsMesenchymal stem cells of any origin, e.g. adipose-derived stem cells

Abstract

Disclosed herein are methods and compositions related to the treatment, prevention, and/or amelioration of cancer in a subject in need thereof. In particular, the present technology relates to the use of a MVAΔE3LΔE5R-hFlt3L-OX40LΔWR199-IL-12 virus, a MVAΔE5R-hFlt3L-OX40L virus (MQ710), a MVAΔE3LΔE5R-hFlt3L-OX40LΔWR199 virus (MQ832), a MVAΔE3LΔE5R-hFlt3L-OX40LΔWR199-IL-12ΔC12L virus (MQ953), a MVAΔE3LΔE5R-hFlt3L-OX40LΔWR199-IL-12ΔC12L-hG-CSF virus (MQ954), a MVAΔE3LΔE5R-hFlt3L-OX40LΔWR199-IL-12ΔC12L-hG-CSF-ΔNlL-hIL-7 virus (MQ955), or combinations thereof, and optionally G-CSF, IL-7, and/or one or more immune checkpoint blockade inhibitors as an immunotherapeutic composition, in methods for treating a solid tumor wherein the solid tumor is resistant to immune checkpoint blockade inhibitor treatment, methods for treating a tumor in a subject in need thereof wherein the subject has a deficient adaptive immune system response, and methods for altering the tumor immune microenvironment (TIME) in a tumor in a subject in need thereof.

IPC Classes  ?

• A61K 35/768 - Oncolytic viruses not provided for in groups
• A61K 38/18 - Growth factorsGrowth regulators
• A61P 35/00 - Antineoplastic agents
• A61P 37/02 - Immunomodulators
• C07K 14/52 - CytokinesLymphokinesInterferons
• C12N 15/09 - Recombinant DNA-technology

Abstract

The present technology relates generally to compositions that specifically recognize and bind to SIRPα polypeptides. The compositions of the present technology are useful in methods for enhancing the anti -turn or activity of monoclonal antibody therapy in a subject in need thereof.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C07K 16/32 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against translation products from oncogenes
• C12N 15/85 - Vectors or expression systems specially adapted for eukaryotic hosts for animal cells
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure relates generally to immunoglobulin-related compositions (e.g., antibodies or antigen binding fragments thereof) that can bind to and neutralize the activity of GPA33 protein. The antibodies of the present technology are useful in methods for detecting and treating an GPA33 -positive cancer in a subject in need thereof.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C07K 16/32 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against translation products from oncogenes
• C07K 16/46 - Hybrid immunoglobulins
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure provides lesional dosimetry methods for predicting the radioisotope activity required to deliver a therapeutic dose of radiation to induce an anti-tumor response in tumor lesions in a subject in need thereof. Specifically implemented is a computer-implemented dosimetry method comprising: detecting, in a single-time-point medical image of a patient, for each cancerous lesion of the patient, an indicator of a surrogate of a radiotherapeutic compound. The medical images captured within a predetermined time range following administration of the surrogate to the patient. Using each indicator, determining an uptake metric corresponding to uptake of the surrogate by each corresponding cancerous lesion. Generating, based on the predetermined time range and the uptake metric, using a dosimetry biomarker based on uptake of the surrogate by subjects in a cohort of subjects, a radiation dose prediction for administration of the radiotherapeutic compound to the patient. Resulting in providing the radiation dose prediction for subsequent use by a healthcare professional in determining a treatment protocol for treating the cancerous lesions of the patient using the radiotherapeutic compound.

IPC Classes  ?

• A61N 5/10 - X-ray therapyGamma-ray therapyParticle-irradiation therapy
• G06T 7/00 - Image analysis
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture

Abstract

Described herein are amorphous and crystalline forms of the androgen receptor modulator 4-[7-(6-cyano-5-trifluoromethylpyridin-3-yl)-8-oxo-6-thioxo-5,7-diazaspiro[3.4]oct-5-yl]-2-fluoro-N-methylbenzamide. Also described are pharmaceutical compositions suitable for administration to a mammal that include the androgen receptor modulator, and methods of using the androgen receptor modulator, alone and in combination with other compounds, for treating diseases or conditions that are associated with androgen receptor activity.

IPC Classes  ?

• C07D 401/04 - Heterocyclic compounds containing two or more hetero rings, having nitrogen atoms as the only ring hetero atoms, at least one ring being a six-membered ring with only one nitrogen atom containing two hetero rings directly linked by a ring-member-to-ring- member bond

Abstract

The present disclosure provides methods for treating cancer and/or delaying or decreasing cytokine release syndrome in a patient in need thereof comprising administering an effective amount of dexamethasone and an effective amount of tumor-specific T cell engaging multi-specific antibodies. Kits for use in practicing the methods are also provided.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 31/573 - Compounds containing cyclopenta[a]hydrophenanthrene ring systemsDerivatives thereof, e.g. steroids substituted in position 17 beta by a chain of two carbon atoms, e.g. pregnane or progesterone substituted in position 21, e.g. cortisone, dexamethasone, prednisone or aldosterone
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure relates to non-steroid selective androgen receptor modulator (SARM) compounds of Formula (I): or a pharmaceutically acceptable salt and/or solvate thereof, as well as compositions and uses thereof.

IPC Classes  ?

• A61K 31/395 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins
• A61K 31/015 - Hydrocarbons carbocyclic
• A61K 31/025 - Halogenated hydrocarbons carbocyclic
• A61K 31/045 - Hydroxy compounds, e.g. alcoholsSalts thereof, e.g. alcoholates

Abstract

The present disclosure provides methods for enhancing the efficacy of immunotherapy (e.g., immune checkpoint blockade or adoptive cell therapeutic composition) in a cancer patient comprising administering an effective amount of at least one agent that inhibits the expression and/or activity of PCBP2.

IPC Classes  ?

• A61K 39/395 - AntibodiesImmunoglobulinsImmune serum, e.g. antilymphocytic serum
• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61P 35/00 - Antineoplastic agents
• A61P 37/04 - Immunostimulants
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants

Abstract

The approach disclosed herein can provide a closed-loop physical supply chain using a precision vessel. An example vessel includes an outer shell and an inner chamber that fits therein. The inner chamber includes a first compartment to removably house a product, and a second compartment with environmental control mechanisms. An enclosed layer, which may be secured to or integrated with the inner chamber, includes a controller and a communication interface to communicate with devices external to the precision vessel. Multiple sensors that monitor the first compartment send signals to the controller of the enclosed layer. A locking mechanism, when engaged, secures the outer shell to the inner chamber, and when disengaged, unlocks the outer shell from the inner chamber to thereby provide access to the first compartment and the product therein. The vessel can track its conditions and locations, and requires verification prior to disengaging the locking mechanism.

IPC Classes  ?

• B01L 3/00 - Containers or dishes for laboratory use, e.g. laboratory glasswareDroppers
• B01L 7/00 - Heating or cooling apparatusHeat insulating devices
• B65D 25/02 - Internal fittings
• B65D 79/02 - Arrangements or devices for indicating incorrect storage or transport
• B65D 81/18 - Containers, packaging elements, or packages, for contents presenting particular transport or storage problems, or adapted to be used for non-packaging purposes after removal of contents providing specific environment for contents, e.g. temperature above or below ambient

Abstract

Presented herein are systems and methods for magnetic resonance fingerprinting with increased volumetric coverage using deep learning reconstruction. Fingerprinting techniques enable obtaining quantitative molecular information using a scanner in a non-invasive way. However, existing techniques for slice acquisition result in limited spatial coverage. In a single size approach, the pulse sequence can include a full saturation train. The pulse saturation train can excite a single slice. After a delay to allow the magnetization to recover, the pulse saturation train excites the magnetization again with another saturation pulse with different saturation powers. The magnetization is repeated that over a certain length of acquisitions. The magnetization can generate the fingerprint from which to extract the underlying quantitative parameters. Instead of exciting a single slice and allowing it to recover, the present disclosure can excite multiple slices to increase the spatial coverage without increasing the scan time.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G01R 33/483 - NMR imaging systems with selection of signal or spectra from particular regions of the volume, e.g. in vivo spectroscopy
• G01R 33/56 - Image enhancement or correction, e.g. subtraction or averaging techniques
• G06N 3/045 - Combinations of networks
• G06N 3/08 - Learning methods

Abstract

The present disclosure provides prophylactic methods for using an immune checkpoint inhibitor to prevent neoplasia in a Lynch Syndrome subject that lacks detectable tumors and has not received a prior anti-cancer therapy such as immunotherapy. In some embodiments, the Lynch Syndrome subject does not harbor germline mutations in POLE or POLDI and/or comprises a hereditary mismatch repair deficient (dMMR) germline mutation.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61P 35/00 - Antineoplastic agents
• C07K 16/30 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells
• C07K 16/40 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against enzymes

Abstract

The present disclosure is directed to systems and methods for determining measures of tumors from biomedical images. A computing system can receive (i) a first biomedical image derived via a computed tomography (CT) scan of an organ associated with a tumor in a subject and (ii) a second biomedical image derived via a positron emission tomography (PET) scan of the organ. The computing system can determine, from the first biomedical image, a region of interest (ROI) corresponding to the organ associated with the tumor in the subject. The computing system can identify a portion in the second biomedical image corresponding to the ROI. The computing system can generate a plurality of measures of the tumor in the subject based on one or more contours of the portion. The computing system can store an association between the subject and the plurality of measures of the tumor.

IPC Classes  ?

• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 6/42 - Arrangements for detecting radiation specially adapted for radiation diagnosis
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• G06T 7/11 - Region-based segmentation
• G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• G06T 7/60 - Analysis of geometric attributes

Abstract

The presently disclosed subject matter provides methods for improving production of cells comprising an antigen-recognizing receptor (e.g., a chimeric antigen receptor (CAR) or a TCR like fusion molecule). The methods disclosed herein can improve the activity and/or efficiency of the cells.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C12N 5/078 - Cells from blood or from the immune system
• G01N 33/543 - ImmunoassayBiospecific binding assayMaterials therefor with an insoluble carrier for immobilising immunochemicals
• G01N 33/553 - Metal or metal coated
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61P 35/00 - Antineoplastic agents

Abstract

The present technology relates to methods for treating, preventing, and/or ameliorating Alzheimer's disease, in a subject in need thereof. In particular aspects, the present technology relates to the use of MAPK inhibitors to treat, prevent, and/or ameliorate Alzheimer's disease.

IPC Classes  ?

• A61K 31/5377 - 1,4-Oxazines, e.g. morpholine not condensed and containing further heterocyclic rings, e.g. timolol
• A61K 31/166 - Amides, e.g. hydroxamic acids having aromatic rings, e.g. colchicine, atenolol, progabide having the carbon atom of a carboxamide group directly attached to the aromatic ring, e.g. procainamide, procarbazine, metoclopramide, labetalol
• A61K 31/18 - Sulfonamides
• A61K 31/365 - Lactones
• A61K 31/404 - Indoles, e.g. pindolol
• A61K 31/4184 - 1,3-Diazoles condensed with carbocyclic rings, e.g. benzimidazoles
• A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
• A61K 31/44 - Non-condensed pyridinesHydrogenated derivatives thereof
• A61K 31/4412 - Non-condensed pyridinesHydrogenated derivatives thereof having oxo groups directly attached to the heterocyclic ring
• A61K 31/4418 - Non-condensed pyridinesHydrogenated derivatives thereof having a carbocyclic ring directly attached to the heterocyclic ring, e.g. cyproheptadine
• A61K 31/4439 - Non-condensed pyridinesHydrogenated derivatives thereof containing further heterocyclic ring systems containing a five-membered ring with nitrogen as a ring hetero atom, e.g. omeprazole
• A61K 31/4523 - Non-condensed piperidines, e.g. piperocaine containing further heterocyclic ring systems
• A61K 31/4709 - Non-condensed quinolines containing further heterocyclic rings
• A61K 31/496 - Non-condensed piperazines containing further heterocyclic rings, e.g. rifampin, thiothixene or sparfloxacin
• A61K 31/505 - PyrimidinesHydrogenated pyrimidines, e.g. trimethoprim
• A61K 31/506 - PyrimidinesHydrogenated pyrimidines, e.g. trimethoprim not condensed and containing further heterocyclic rings
• A61K 31/517 - PyrimidinesHydrogenated pyrimidines, e.g. trimethoprim ortho- or peri-condensed with carbocyclic ring systems, e.g. quinazoline, perimidine
• A61K 31/519 - PyrimidinesHydrogenated pyrimidines, e.g. trimethoprim ortho- or peri-condensed with heterocyclic rings
• A61P 25/28 - Drugs for disorders of the nervous system for treating neurodegenerative disorders of the central nervous system, e.g. nootropic agents, cognition enhancers, drugs for treating Alzheimer's disease or other forms of dementia

Abstract

Provided and featured are novel recombinant T cell receptors (TCRs) that target a mutated tumor suppressor TP53. Also provided are cells comprising such TCRs, and methods of using the recombinant TCRs and cells expressing the recombinant TCRs for treating cancers associated with mutated TP53.

IPC Classes  ?

• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 38/04 - Peptides having up to 20 amino acids in a fully defined sequenceDerivatives thereof
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure provides methods for improving in vivo survival of midbrain dopamine (mDA) neurons (e.g., in vitro differentiated mDA neurons) by suppressing p53-mediated apoptosis of mDA neurons. The present disclosure further provides methods for treating a subject (e.g., a subject suffering from neurodegeneration of midbrain dopamine neurons, and/or a neurodegenerative disease), comprising administering to the subject one or more mDAs, wherein p53-mediated apoptosis of the one or more mDA neurons is suppressed.

IPC Classes  ?

• A61K 35/50 - PlacentaPlacental stem cellsAmniotic fluidAmnionAmniotic stem cells
• A61P 25/28 - Drugs for disorders of the nervous system for treating neurodegenerative disorders of the central nervous system, e.g. nootropic agents, cognition enhancers, drugs for treating Alzheimer's disease or other forms of dementia
• C12N 5/0793 - Neurons
• C12N 5/0797 - Stem cellsProgenitor cells

Abstract

Provided are age-modulated cells and method for making age-modulated cells. The aging and rejuvenation processes can be induced for young, aged, mature and/or immature cells, such as a somatic cell, a stem cell, a stem cell-derived somatic cell, including an induced pluripotent stem cell-derived cell, by contacting cells with one or more age-inducing or rejuvenating agent. Methods described by the present disclosure can produce age-appropriate cells from a somatic cell or a stem cell, such as an old cell, young cell, immature cell, and/or a mature cell. Such age-modified cells constitute model systems for the study of late-onset diseases and/or disorders.

IPC Classes  ?

• C07D 405/10 - Heterocyclic compounds containing both one or more hetero rings having oxygen atoms as the only ring hetero atoms, and one or more rings having nitrogen as the only ring hetero atom containing two hetero rings linked by a carbon chain containing aromatic rings
• C12N 5/077 - Mesenchymal cells, e.g. bone cells, cartilage cells, marrow stromal cells, fat cells or muscle cells
• C07D 239/70 - Heterocyclic compounds containing 1,3-diazine or hydrogenated 1,3-diazine rings condensed with carbocyclic rings or ring systems
• C07C 15/60 - Cyclic hydrocarbons containing only six-membered aromatic rings as cyclic part substituted by unsaturated hydrocarbon radicals polycyclic condensed containing three rings

Abstract

The present technology relates generally to lipid nanoparticles including a therapeutic agent and a sulfolipid targeting P-selectin or a ganglioside targeting Galectin-3 for treating or preventing a disease in a subject.

IPC Classes  ?

• A61K 9/51 - Nanocapsules
• A61K 9/00 - Medicinal preparations characterised by special physical form
• A61K 9/19 - Particulate form, e.g. powders lyophilised
• B82Y 5/00 - Nanobiotechnology or nanomedicine, e.g. protein engineering or drug delivery
• A61K 31/7032 - Compounds having saccharide radicals attached to non-saccharide compounds by glycosidic linkages attached to a polyol, i.e. compounds having two or more free or esterified hydroxy groups, including the hydroxy group involved in the glycosidic linkage, e.g. monoglucosyl-diacylglycerides, lactobionic acid, gangliosides
• A61K 47/10 - AlcoholsPhenolsSalts thereof, e.g. glycerolPolyethylene glycols [PEG]PoloxamersPEG/POE alkyl ethers
• A61K 47/60 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the non-active ingredient being a modifying agent the modifying agent being an organic macromolecular compound, e.g. an oligomeric, polymeric or dendrimeric molecule obtained otherwise than by reactions only involving carbon-to-carbon unsaturated bonds, e.g. polyureas or polyurethanes the organic macromolecular compound being a polyoxyalkylene oligomer, polymer or dendrimer, e.g. PEG, PPG, PEO or polyglycerol
• A61P 35/00 - Antineoplastic agents
• A61P 37/06 - Immunosuppressants, e.g. drugs for graft rejection

Abstract

The presently disclosed subject matter provides antibodies or antigen-binding fragments thereof that bind to chimeric receptors (e.g., CAR, HIT, etc.). In certain embodiments, the presently disclosed antibodies or antigen-binding fragments thereof are anti-idiotype antibodies or antigen -binding fragment thereof. In certain embodiments, the presently disclosed antibodies or antigen binding fragments thereof bind to an antigen-binding domain (e.g., an extracellular antigen-binding domain of a CAR).

IPC Classes  ?

• C07K 16/42 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against immunoglobulins (anti-idiotypic antibodies)
• A61K 39/395 - AntibodiesImmunoglobulinsImmune serum, e.g. antilymphocytic serum

Abstract

The invention provides compounds, methods, pharmaceutical compositions, and kits for the treatment of proliferative disorders such as cancer. In one aspect, the methods comprise compounds that inhibit the activity of protein kinases, such as cell division cycle (Cdc) kinase. In another aspect, the methods comprise compounds that inhibit Cdc7 and/or Dbf4 activity. In another aspect, the methods comprise compounds that exhibit anti-proliferative properties useful in treating diseases such as cancer. Compounds useful for any of the methods include compounds of the Formula (A) or (B): The invention provides compounds, methods, pharmaceutical compositions, and kits for the treatment of proliferative disorders such as cancer. In one aspect, the methods comprise compounds that inhibit the activity of protein kinases, such as cell division cycle (Cdc) kinase. In another aspect, the methods comprise compounds that inhibit Cdc7 and/or Dbf4 activity. In another aspect, the methods comprise compounds that exhibit anti-proliferative properties useful in treating diseases such as cancer. Compounds useful for any of the methods include compounds of the Formula (A) or (B): The invention provides compounds, methods, pharmaceutical compositions, and kits for the treatment of proliferative disorders such as cancer. In one aspect, the methods comprise compounds that inhibit the activity of protein kinases, such as cell division cycle (Cdc) kinase. In another aspect, the methods comprise compounds that inhibit Cdc7 and/or Dbf4 activity. In another aspect, the methods comprise compounds that exhibit anti-proliferative properties useful in treating diseases such as cancer. Compounds useful for any of the methods include compounds of the Formula (A) or (B): or pharmaceutically acceptable salts thereof. Exemplary compounds of Formula (A) or (B) include granaticin A, granaticin B, dihydrogranaticin A, dihydrogranaticin B, medermycin, and actinorhodin.

IPC Classes  ?

• A61K 31/365 - Lactones
• A61K 9/00 - Medicinal preparations characterised by special physical form
• A61K 31/122 - Ketones having the oxygen atom directly attached to a ring, e.g. quinones, vitamin K1, anthralin
• A61K 31/352 - Heterocyclic compounds having oxygen as the only ring hetero atom, e.g. fungichromin having six-membered rings with one oxygen as the only ring hetero atom condensed with carbocyclic rings, e.g. cannabinols, methantheline
• A61N 5/10 - X-ray therapyGamma-ray therapyParticle-irradiation therapy
• C07D 493/08 - Bridged systems
• C07D 493/18 - Bridged systems
• C09B 13/02 - Oxyketone dyes of the naphthalene series, e.g. naphthazarin
• C09B 61/00 - Dyes of natural origin prepared from natural sources
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer

Abstract

The present disclosure relates generally to methods for accurately predicting the risk of cancer-associated venous thromboembolism (CAT) and/or preventing CAT in cancer patients using proteomic biomarkers.

IPC Classes  ?

• G01N 33/68 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving proteins, peptides or amino acids
• A61P 7/02 - Antithrombotic agentsAnticoagulantsPlatelet aggregation inhibitors
• C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganismsCompositions thereforProcesses of preparing such compositions involving nucleic acids
• G01N 33/86 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving blood coagulating time
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer

Abstract

The present disclosure relates generally to anti-PD-L1 immunoglobulin-related compositions (e.g., antibodies or antigen binding fragments thereof) comprising IL-15-IL-15Rα fusion polypeptides and uses thereof. In some embodiments, the anti-PD-L1 antibodies comprising IL-15-IL-15Rα fusion polypeptides are useful for treating cancer and improving responsiveness to immune checkpoint blockade (ICB) therapy in a subject in need thereof.

IPC Classes  ?

• A61K 39/395 - AntibodiesImmunoglobulinsImmune serum, e.g. antilymphocytic serum
• A61K 47/68 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the non-active ingredient being a modifying agent the modifying agent being an antibody, an immunoglobulin or a fragment thereof, e.g. an Fc-fragment
• A61P 35/00 - Antineoplastic agents
• C12N 15/85 - Vectors or expression systems specially adapted for eukaryotic hosts for animal cells
• C12N 5/10 - Cells modified by introduction of foreign genetic material, e.g. virus-transformed cells
• C07K 16/30 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants from tumour cells

Abstract

The present disclosure provides methods for determining whether a cancer patient with homologous recombination deficiency will benefit from treatment with PARP inhibitors or platinum agents. These methods are based on screening a cancer patient for the presence of reciprocal structural variants (SVs) that comprise pairs of distant intra- or inter-chromosomal loci that contain exchanged genomic material.

IPC Classes  ?

• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• A61K 31/166 - Amides, e.g. hydroxamic acids having aromatic rings, e.g. colchicine, atenolol, progabide having the carbon atom of a carboxamide group directly attached to the aromatic ring, e.g. procainamide, procarbazine, metoclopramide, labetalol
• A61K 33/243 - PlatinumCompounds thereof
• A61P 35/00 - Antineoplastic agents
• C12Q 1/6827 - Hybridisation assays for detection of mutation or polymorphism
• C12Q 1/6869 - Methods for sequencing

Abstract

The present invention relates to adenovirus E4ORF1 gene and to endothelial cells engineered to express the E4ORF1 gene. The present invention also relates to uses of the E4ORF1 gene, and cells expressing the E4ORF1 gene, and to compositions comprising the E4ORF1 gene, or comprising cells expressing the E4ORF1 gene.

IPC Classes  ?

• C12N 5/0735 - Embryonic stem cellsEmbryonic germ cells
• C07K 14/005 - Peptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from viruses
• C12N 5/071 - Vertebrate cells or tissues, e.g. human cells or tissues
• C12N 5/0789 - Stem cellsMultipotent progenitor cells
• C12N 5/09 - Tumour cells
• C12N 15/113 - Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides

Abstract

The present technology provides anti-Thyroid Stimulating Hormone Receptor (TSHR) multi-specific (e.g., bispecific) immunoglobulin-related compositions and methods of using the same to treat TSHR-associated pathologies including, but not limited to, thyroid cancers, T-ALL (T lineage acute lymphoblastic leukemia), multiple myeloma and Grave's disease. Kits for use in practicing the methods are also provided.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61P 35/00 - Antineoplastic agents
• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• C07K 16/32 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against translation products from oncogenes

Abstract

The present disclosure provides, in some embodiments, methods for culturing and expanding hematopoietic stem cells (HSPCs) comprising a genomic modification associated with clonal hematopoiesis (CH). These cultured and expanded HSPCs are used, in some embodiments, to identify genes that promote CH, to identify inhibitors of CH, and to inhibit CH.

IPC Classes  ?

• G01N 33/50 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing
• C12N 5/0789 - Stem cellsMultipotent progenitor cells
• C12N 9/22 - Ribonucleases
• C12N 15/10 - Processes for the isolation, preparation or purification of DNA or RNA
• C12N 15/11 - DNA or RNA fragmentsModified forms thereof

Abstract

The present disclosure provides methods and systems for selecting therapies for a protein structure based on structural distances among open reading frames (ORFs) encoding diverse proteins using information theory.

IPC Classes  ?

• G16B 15/00 - ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
• G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
• G01N 33/68 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving proteins, peptides or amino acids
• G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage

Abstract

The present disclosure relates generally to methods and systems for predicting pre¬ operative lung ablation in lung cancer patients in need thereof and the application of machine learning to perform microwave lung ablation with accurate margins to prevent local tumor recurrence.

IPC Classes  ?

• A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
• G06N 3/08 - Learning methods
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• A61B 18/00 - Surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body

Abstract

The presently disclosed subject matter provides cells comprising a Fas ligand (FasL) polypeptide and a cFLIP polypeptide. In certain embodiments, the cells further comprise an antigen-recognizing receptor (e.g., a chimeric antigen receptor (CAR) or a T cell receptor (TCR), or a TCR like fusion molecule). Also provided are uses of the cells for cell lysis of target cells expressing Fas, and for treating diseases or disorders, e.g., tumors.

IPC Classes  ?

• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• C07K 14/47 - Peptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from animalsPeptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from humans from vertebrates from mammals
• C07K 14/705 - ReceptorsCell surface antigensCell surface determinants
• C12N 5/078 - Cells from blood or from the immune system
• C12N 15/88 - Introduction of foreign genetic material using processes not otherwise provided for, e.g. co-transformation using microencapsulation, e.g. using liposome vesicle

Abstract

Described embodiments provide systems and methods for anonymizing image data. A computing system can obtain a medical image of a subject, the medical image comprising a set of slices and being associated with a set of metadata regarding the medical image and the subject. The computing system may identify, based on the set of metadata, one or more regions of interest (ROIs) of the subject in the medical image, the ROIs corresponding with a condition to be evaluated by a clinician. The computing system may select, based on the ROIs, a modification technique to apply to the medical image, wherein selecting the modification technique comprises determining an image segment that is situated outside of the identified ROIs, the image segment comprising a distinguishing feature of the subject. The computing system may generate a modified image by applying the modification technique to the medical image to render the distinguishing feature indistinguishable.

IPC Classes  ?

• G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
• G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
• G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions

Abstract

The present disclosure provides methods for treating cancer in a subject in need thereof comprising administering to the subject an effective amount of inhibitors of LINE- 1 (LI) activity or ADAR1 inhibitors based on TP53 mutation status. The methods of the present technology increase immunogenic SINE-derived dsRNA levels, thus triggering an effective immune response. Also disclosed herein are methods for selecting cancer patients for combination therapy with (i) LI inhibitors or AD ARI inhibitors and (ii) immune checkpoint blockade (ICB) inhibitors based on TP53 mutation status.

IPC Classes  ?

• A61K 45/06 - Mixtures of active ingredients without chemical characterisation, e.g. antiphlogistics and cardiaca
• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure provides vaccine compositions comprising recombinant SS 18 : : SSX fusion peptide epitopes and at least one cancer-testis antigen (CTA) epitope, or nucleic acids (e.g., mRNA, cDNA) encoding the same, and methods for using the same to treat sarcoma (e.g., synovial sarcoma) in a subject in need thereof.

IPC Classes  ?

• A61K 39/00 - Medicinal preparations containing antigens or antibodies
• A61K 38/10 - Peptides having 12 to 20 amino acids
• C07K 7/08 - Linear peptides containing only normal peptide links having 12 to 20 amino acids
• C07K 14/47 - Peptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from animalsPeptides having more than 20 amino acidsGastrinsSomatostatinsMelanotropinsDerivatives thereof from humans from vertebrates from mammals
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure provides methods, devices, and systems for determining the retrotransposon (RT) burden, RT expression and fitness of mutant p53 in a subject. The RT burden, RT RNA expression and fitness of mutant p53 may be used to determine whether a subject is at risk for cancer and will benefit from a particular anti -cancer therapy such as immune checkpoint inhibitor therapy, adoptive cell therapy, or prophylactic cancer vaccine therapy.

IPC Classes  ?

• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• A61K 35/17 - LymphocytesB-cellsT-cellsNatural killer cellsInterferon-activated or cytokine-activated lymphocytes
• G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer
• A61P 35/00 - Antineoplastic agents

Abstract

e.g.e.g., immune checkpoint blockade therapy), adoptive cell therapy, chemotherapy, or radiation therapy and the like. Also disclosed herein are methods of using the polymeric nanoparticle compositions of the present technology to improve tissue function after organ transplantation, hip replacement etc. In some embodiments, the polymeric nanoparticles described herein have an affinity to P-selectin and comprise a senolytic or senomorphic drug.

IPC Classes  ?

• A61K 31/4965 - Non-condensed pyrazines
• A61K 31/5375 - 1,4-Oxazines, e.g. morpholine
• A61K 47/26 - Carbohydrates, e.g. sugar alcohols, amino sugars, nucleic acids, mono-, di- or oligo-saccharidesDerivatives thereof, e.g. polysorbates, sorbitan fatty acid esters or glycyrrhizin
• A61K 47/38 - CelluloseDerivatives thereof
• A61K 47/42 - ProteinsPolypeptidesDegradation products thereofDerivatives thereof, e.g. albumin, gelatin or zein
• A61K 9/51 - Nanocapsules
• A61P 25/28 - Drugs for disorders of the nervous system for treating neurodegenerative disorders of the central nervous system, e.g. nootropic agents, cognition enhancers, drugs for treating Alzheimer's disease or other forms of dementia
• A61P 35/00 - Antineoplastic agents
• A61P 9/10 - Drugs for disorders of the cardiovascular system for treating ischaemic or atherosclerotic diseases, e.g. antianginal drugs, coronary vasodilators, drugs for myocardial infarction, retinopathy, cerebrovascula insufficiency, renal arteriosclerosis

Abstract

The presently disclosed subject matter provides antibodies or antigen-binding fragments thereof that bind to DLL3 and methods of using such antibodies or antigen-binding fragments thereof same.

IPC Classes  ?

• C07K 16/28 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans against receptors, cell surface antigens or cell surface determinants
• A61K 51/10 - Antibodies or immunoglobulinsFragments thereof
• A61P 35/00 - Antineoplastic agents

Abstract

The present disclosure provides methods and compositions for treating or preventing a gastrointestinal inflammatory disease in a subject in need thereof comprising administering to the subject a therapeutically effective amount of an agent that increases alpha¬ ketoglutarate (aKG) expression and/or activity.

IPC Classes  ?

• C12P 7/50 - Polycarboxylic acids having keto groups, e.g. 2-ketoglutaric acid
• A61K 39/395 - AntibodiesImmunoglobulinsImmune serum, e.g. antilymphocytic serum
• G01N 33/50 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing
• C12Q 1/32 - Measuring or testing processes involving enzymes, nucleic acids or microorganismsCompositions thereforProcesses of preparing such compositions involving oxidoreductase involving dehydrogenase
• A61P 1/04 - Drugs for disorders of the alimentary tract or the digestive system for ulcers, gastritis or reflux esophagitis, e.g. antacids, inhibitors of acid secretion, mucosal protectants
• C07K 16/18 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from animals or humans
• C12N 5/071 - Vertebrate cells or tissues, e.g. human cells or tissues

Abstract

This invention is directed to anti-cancer treatments and methods of use thereof.

IPC Classes  ?

• C12N 9/00 - Enzymes, e.g. ligases (6.)ProenzymesCompositions thereofProcesses for preparing, activating, inhibiting, separating, or purifying enzymes
• A61P 35/00 - Antineoplastic agents
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• G01N 33/50 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing

Abstract

The presently disclosed subject matter provides antibodies that mimic TCR recognition of HPV-derived epitopes presented by HLA class I molecules, antigen-recognizing receptors that target HPV-derived epitopes presented by HLA class I molecules, and methods of using such antibodies.

IPC Classes  ?

• C07K 16/08 - Immunoglobulins, e.g. monoclonal or polyclonal antibodies against material from viruses
• A61K 47/68 - Medicinal preparations characterised by the non-active ingredients used, e.g. carriers or inert additivesTargeting or modifying agents chemically bound to the active ingredient the non-active ingredient being chemically bound to the active ingredient, e.g. polymer-drug conjugates the non-active ingredient being a modifying agent the modifying agent being an antibody, an immunoglobulin or a fragment thereof, e.g. an Fc-fragment

Abstract

The present disclosure provides methods for determining whether a cancer patient will benefit from treatment with an ATR inhibitor or CHK1 inhibitor. These methods are based on screening a cancer patient for gene rearrangements in FET. Also disclosed herein are methods for enhancing sensitivity to ATR inhibitor/CHKl inhibitor therapy in cancer patients comprising administering to the subject an effective amount of an ATM inhibitor.

IPC Classes  ?

• A61K 31/5377 - 1,4-Oxazines, e.g. morpholine not condensed and containing further heterocyclic rings, e.g. timolol
• A61P 35/00 - Antineoplastic agents
• C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
• G01N 33/68 - Chemical analysis of biological material, e.g. blood, urineTesting involving biospecific ligand binding methodsImmunological testing involving proteins, peptides or amino acids
• A61K 31/4402 - Non-condensed pyridinesHydrogenated derivatives thereof only substituted in position 2, e.g. pheniramine, bisacodyl