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Analysis

1.WO/2021/011434METHODS AND SYSTEMS FOR AUTHENTICATING GOODS AND SERVICES USING ELECTRONIC ANALYSIS OF ANALYTE ENCODED COMPOSITIONS
WO 21.01.2021
Int.Class C12Q 1/68
CCHEMISTRY; METALLURGY
12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
QMEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
1Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
68involving nucleic acids
Appl.No PCT/US2020/041739 Applicant VILLWOCK, Thomas Inventor VILLWOCK, Thomas
Methods for product authentication, which include: providing an article having a substrate with an analyte encoded composition; obtaining a sample of the composition; applying the sample to a test device to obtain test results, analyzing test results from the test device using an electronic device communicatively connected to an authentication authority, wherein the electronic device transmits the test device code and the test results to the authentication authority and confirms or denies authentication after comparison to an authentication database of authentic test results.
2.WO/2021/009300DIGITAL ASSISTANT TO SUPPORT PRODUCT DEVELOPMENT
WO 21.01.2021
Int.Class G16C 20/30
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
30Prediction of properties of chemical compounds, compositions or mixtures
Appl.No PCT/EP2020/070176 Applicant BASF SE Inventor BRANDL, Ferdinand Paul
In order to facilitate product development, such as pharmaceutical product development, a computer implemented method and an apparatus are proposed that enable formulators to develop robust drug formulations in a cost- and time-efficient manner. To start the development process, the user selects the preferred dosage form (e.g., granules, pellets, capsules, tablets etc.), defines a target profile (e.g., amount of active ingredient per unit, size of dosage form, mechanical strength of dosage form, desired release behaviour etc.) and enters key characteristics of the active ingredient (e.g., true density, particle size distribution data, bulk and tapped density, angle of repose, compressibility and compactibility profile etc.). The identity (e.g., chemical name or structure) of the active ingredient is not necessarily disclosed. The apparatus processes the provided data and calculates key parameters of the AI (e.g., particle size, powder density, powder flow and tabletability). Similar key parameters are calculated for common pharmaceutical excipients and stored in the apparatus. The apparatus then selects all relevant excipients and suggests a suitable manufacturing process. Combinations of active ingredients and excipients qualify as drug formulation if the predicted properties comply with the defined target profile. The following aspects can be considered: solubility and permeability of the active ingredient, dissolution of the active ingredient, probability to pass the content uniformity criteria, flowability of the powder blend, tabletability of the powder blend, mechanical strength and size of the tablet, compatibility of active ingredients and excipients etc.
3.WO/2021/004021DATA MANAGEMENT SYSTEM IN DRUG DEVELOPMENT PROCESS, AND USE METHOD THEREFOR
WO 14.01.2021
Int.Class G16C 20/50
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
50Molecular design, e.g. of drugs
Appl.No PCT/CN2019/126993 Applicant SHENZHEN JINGTAI TECHNOLOGY CO., LTD. Inventor CHEN, Yongpan
A data management system in drug development process, and a use method therefor, comprising: a user module, a development pipeline management module, a virtual filter module, an AI model management module, a visualization module, and an analysis module. The development pipeline management module separates data of each of a plurality of development pipelines. A preset virtual filter method and a conformation generator are integrated into the virtual filter module. An AI pharmaceutical molecule generation model is integrated into the AI model management module, and AI model training and utilization functions are provided in same. The visualization module represents a data set of each molecule as a circle. The analysis module is used to analyze and record a filter result from the virtual filter module. The method is able to batch filter molecules of approximately an order of magnitude of one million by means of various modeling methods, thus still being able to ensure development efficiency under a condition of a large increase in the order of magnitude of the number of molecules.
4.WO/2021/005332IDENTIFYING ONE OR MORE COMPOUNDS FOR TARGETING A GENE
WO 14.01.2021
Int.Class G16H 50/70
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
50ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
70for mining of medical data, e.g. analysing previous cases of other patients
Appl.No PCT/GB2020/051549 Applicant BENEVOLENTAI TECHNOLOGY LIMITED Inventor SELLWOOD, Matthew
A computer-implemented method of identifying a tool compound is provided. The method comprises: searching a database for first candidate compounds that each target one or more first target genes; generating a first fingerprint for each first candidate compound by: searching the database for genes associated with the first candidate compound, and predicting genes associated with the first candidate compound; and filtering the first candidate compounds using the first fingerprints to identify a first optimum compound for targeting the one or more first target genes.
5.WO/2021/004020SYSTEM AND METHOD FOR USE IN USER INTERACTION IN COMPLEX WEB3D SCENE
WO 14.01.2021
Int.Class G16C 20/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
20Identification of molecular entities, parts thereof or of chemical compositions
Appl.No PCT/CN2019/126991 Applicant SHENZHEN JINGTAI TECHNOLOGY CO., LTD. Inventor HAN, Fei
A system and a method for use in user interaction in a complex web3D scene, relating to the field of chemistry computing. The system comprises a receiving module, a transmitting module, and a 3D model module. The receiving module is used to receive molecular data. The transmitting module is used to parse the received molecular data and then simultaneously transmit same to two branch modules, comprising a first branch module and a second branch module. The first branch module serves as a view layer unit, and is used to process browser rendering and 3D model construction, data produced by said branch module eventually appearing on a page of the browser. The second branch module serves as a data layer unit, and is used to process service logic related to 3D pickup, and to construct, for atoms, covalent bonds, and the like in the molecular data, a list of index information for the relevant models. The 3D model module is used to construct a one-to-one correspondence relationship between colors and 3D models, and all 3D models needing to be picked up will have one unique index in the data layer. For visualized picking up of molecules in web3D, the described system can reduce the computational costs of model data for the relatively little rendering of the display model (stick model) of the molecules.
6.WO/2021/005982TYPE ESTIMATION MODEL GENERATION SYSTEM AND TYPE ESTIMATION SYSTEM
WO 14.01.2021
Int.Class G10K 15/04
GPHYSICS
10MUSICAL INSTRUMENTS; ACOUSTICS
KSOUND-PRODUCING DEVICES;  METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
15Acoustics not otherwise provided for
04Sound-producing devices
Appl.No PCT/JP2020/023774 Applicant NTT DOCOMO, INC. Inventor TANAKA Shigeki
The present invention aims to appropriately classify users on the basis of songs used. A model generation system 10 included in a recommendation server 1 is a type estimation model generation system that generates type estimation models used in type estimation regarding which of a plurality of types a user belongs. The model generation system for type estimation comprises: a training data acquisition unit 11 that obtains time series information for training, which is training data used in machine learning and indicates time series information pertaining to a plurality of songs that have been used, and type information for training, which indicates the type that the user who used the plurality of songs belongs to; and a model generation unit 12 that, once information on the basis of the time series information for training has been entered into a type estimation model, in song units and in the time series order, performs machine learning using the information on the basis of the type information for learning, as outputs for the type estimation model, and generates a type estimation model.
7.WO/2021/003834SMALL-MOLECULE DRUG CYTOCHROME P450 METABOLISM LOCUS PREDICTION METHOD
WO 14.01.2021
Int.Class G16C 20/50
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
50Molecular design, e.g. of drugs
Appl.No PCT/CN2019/104543 Applicant SHENZHEN JINGTAI TECHNOLOGY CO., LTD. Inventor CHEN, Ping
Disclosed is a small-molecule drug cytochrome P450 metabolism locus prediction method. A machine learning model WhichCyp based on a support vector machine classifier is used for predicting a substrate with small molecules belonging to one or multiple subtypes of the cytochrome P450 enzyme subtypes 1A2, 2C9, 2C19, 2D6 and 3A4; by means of a machine learning model based on a convolutional neural network, prediction and sorting are conducted on the corresponding subtype of the cytochrome P450 enzyme and metabolism loci of small-molecule drugs; calculation and evaluation are conducted on the thermodynamic and dynamic interaction of a complete cytochrome P450 enzyme system and complete molecules; high-precision MMGBSA calculation is conducted on each conformation, and the binding energy of different small-molecule conformations and a cytochrome P450 enzyme is obtained; the process is trained by means of a collected small-molecule training set until the prediction accuracy is greater than 80 percent. Accordingly, the accuracy of prediction is improved.
8.20210000998REMOTE SMELL TECHNOLOGY
US 07.01.2021
Int.Class A61L 9/12
AHUMAN NECESSITIES
61MEDICAL OR VETERINARY SCIENCE; HYGIENE
LMETHODS OR APPARATUS FOR STERILISING MATERIALS OR OBJECTS IN GENERAL; DISINFECTION, STERILISATION, OR DEODORISATION OF AIR; CHEMICAL ASPECTS OF BANDAGES, DRESSINGS, ABSORBENT PADS, OR SURGICAL ARTICLES; MATERIALS FOR BANDAGES, DRESSINGS, ABSORBENT PADS, OR SURGICAL ARTICLES
9Disinfection, sterilisation or deodorisation of air
015using gaseous or vaporous substances, e.g. ozone
04using substances evaporated in the air without heating
12Apparatus, e.g. holders, therefor
Appl.No 16643637 Applicant University of North Texas Inventor Guido Fridolin VERBECK

The present application relates to systems, methods, and computer-readable media for providing generating odors. In aspects, the disclosed methods may include generating, by a chemistry dispersion element, a signal configured to act upon a surface of a chemistry reservoir to disperse an odorous substance retained within the chemistry reservoir. The chemistry reservoir and the chemistry dispersion element may be disposed within a housing. The method also includes generating, by an air pump, a volume of air, and transporting, by an airflow pathway, the volume of air from the air pump to an air outlet. The volume of air passes through at least a portion of the housing as it flows through the airflow pathway from the air pump to the air outlet, and transports at least a portion of the odorous substance dispersed by the chemistry reservoir within the housing to the air outlet.

9.20210005287Computer Device for Detecting an Optimal Candidate Compound and Methods Thereof
US 07.01.2021
Int.Class G16C 20/50
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
20Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
50Molecular design, e.g. of drugs
Appl.No 16336549 Applicant GE Healthcare Bio-Sciences Corp. Inventor Emmanuel Israel Fuentes

The invention relates to a method for a computer device, for detecting an optimal candidate compound based on a plurality of samples comprising a cell line and one or more biomarkers, and a plate map configuration, wherein the plate map configuration is providing locations of samples comprising cell lines exposed to one or more biomarkers and different concentrations of a candidate compound forming at least one concentration gradient, the candidate compound being comprised in a plurality of candidate compounds, said method comprising generating (310) phenotypic profiles of each concentration gradient of each of the plurality of candidate compounds at a plurality of successive points in time to form a plurality of compound profiles, wherein generating phenotypic profiles comprises the steps obtaining (312) image data depicting each sample comprised in the concentration gradient, generating (314) a class-label and a class for each cell of the samples based on the image data, detecting (320) the optimal candidate compound by evaluating a comparison criterion on the plurality of compound profiles. Furthermore, the invention also relates to corresponding computer device, a computer program, and a computer program product.

10.WO/2021/001859METHOD AND SYSTEM FOR OPTIMIZATION OF AGGLOMERATION OF ORES
WO 07.01.2021
Int.Class G16C 60/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
60Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
Appl.No PCT/IN2020/050585 Applicant TATA CONSULTANCY SERVICES LIMITED Inventor SINGH, Kuldeep
Agglomeration process in agglomeration plants is quite sensitive to changes in input feed material characteristics. End-to-end optimization of the agglomerate process by combining all the units is difficult due to unique complexities and challenges associated with combining the individual process outputs. A method and system for optimizing the operation of an agglomeration plant has been provided. The system performs real time optimization on integrated wet agglomeration and thermal agglomeration process which subsequently increases the plant productivity and agglomerate quality and minimizes the operating cost and emissions from the plant. The optimization process involves various steps such as receiving data, pre-processing of data, prediction using physics-based and data-driven models of agglomeration plant, and optimization execution and configuration. The process also involves continuous monitoring of model performance and self-learning of the models in case of a performance drift. The system is also configured to estimate the key performance parameters of agglomeration plant.