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Analysis

1 / 3,743
1.WO/2025/238437CURRICULUM LEARNING IN FINER SPECTRUM INFERENCE
WO - 20.11.2025
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/IB2025/053755 Applicant INTERNATIONAL BUSINESS MACHINES CORPORATION Inventor SHINOHARA, Hajime
A curriculum learning method yields finer spectrum inference by abstracted an original training dataset. The abstracted training dataset is supplemented with interpolated data points, to create an interpolated abstracted dataset for initial or intermediate machine learning. The final spectrum inference by the training machine learning model is a finer spectrum inference than obtained by individual learning.
2.WO/2025/240177SYSTEM AND METHOD FOR STABILIZING THE OPERATION OF FACILITIES USING HYDROGEN PRODUCED BY LOW CARBON SOURCES
WO - 20.11.2025
Int.Class C01C 1/04
CCHEMISTRY; METALLURGY
01INORGANIC CHEMISTRY
CAMMONIA; CYANOGEN; COMPOUNDS THEREOF
1Ammonia; Compounds thereof
02Preparation or separation of ammonia
04Preparation of ammonia by synthesis
 Appl.No PCT/US2025/028085 Applicant KELLOGG BROWN & ROOT LLC Inventor PACHPANDE, Sunil Nivrutti
A system and a method for stabilizing hydrogen flow to a downstream process in a facility determining a hydrogen density and pressure profiles in the hydrogen storage unit for different target net hydrogen flows at different time intervals of a time horizon of a renewable power availability profile, determining an operating target net hydrogen flow of a hydrogen feed to the downstream process, determining a target direct hydrogen flow of a hydrogen feed and a target stored hydrogen flow of a hydrogen feed to the downstream process, and controlling the operation of the downstream process based on the operating target hydrogen flows.
3.WO/2025/238271METHOD AND SYSTEM FOR CHEMICALLY ACCURATE QUANTUM COMPUTING
WO - 20.11.2025
Int.Class G16C 10/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
10Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like
 Appl.No PCT/EP2025/063730 Applicant QUBIT PHARMACEUTICALS Inventor TRAORE, Diata
The invention relates to a computer implemented method (100) for computing quantum-enhanced chemical property of a chemical system comprising the following steps: - Providing a Hamiltonian (120) of the chemical system subject of the quantum-enhanced chemical computing; - Providing a basis set (130) for the chemical system; - Preparing an initial quantum state (140), on the quantum computation means (10), to represent the chemical system according to the Hamiltonian and using the provided basis set; - Applying, on the quantum computation means (10), a quantum solver (150) on the prepared quantum state in the basis set; and - Computing, on classical computation means (40), a density-based basis-set correction (160) to modify the density-dependent terms in the Hamiltonian
4.WO/2025/238628METHOD AND SYSTEM FOR UTILIZING ARTIFICIAL INTELLIGENCE TO IDENTIFY COMPOUNDS FOR USE IN COMBINATION THERAPY
WO - 20.11.2025
Int.Class G16C 20/70
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
70Machine learning, data mining or chemometrics
 Appl.No PCT/IB2025/055197 Applicant WITHROW, Mike Inventor WITHROW, Mike
A system and method are herein disclosed. The system and method use a generative AI agent to analyze and identify synergistic blends of natural compounds for combination therapies by leveraging an array of specialized modes to access data from a multitude of sources including patient medical history (including test results, drug history, and imaging) to improve the efficacy of compounds, including traditional medicine, in line with combination therapy principles, aimed at: enhanced efficacy, decreased toxicity, improved dosage, and reduced drug resistance. In this way, the generative AI agent determines cross-therapeutic similarities and/or dissimilarities between pharmaceutical, naturopathic, homeopathic, and nutraceutical compounds along a plurality of compound property vectors such as efficiency, efficacy, toxicity, effects, side-effects, chemistry, pharmacology, pharmacokinetics, mechanisms of action, and pharmacodynamics, thereby enabling the proposition of cross-disciplinary and transdisciplinary therapeutic analyses and the identification of synergistic effects in combination therapies.
5.WO/2025/238429IRREDUCIBLE CARTESIAN TENSORS FOR MACHINE LEARNING PROPERTIES OF BIOLOGICAL MATTER AND MATERIALS
WO - 20.11.2025
Int.Class G16B 15/30
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
15ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
30Drug targeting using structural data; Docking or binding prediction
 Appl.No PCT/IB2025/052665 Applicant NEC LABORATORIES EUROPE GMBH Inventor ZAVERKIN, Viktor
A computer-implemented, machine learning method for predicting molecular properties includes embedding an atomic system of a molecule using irreducible Cartesian tensors. Interactions between rotation-equivariant features are computed using a message passing neural network trained to apply equivariant convolutions defined by an irreducible Cartesian tensor product of the irreducible Cartesian tensors. Many-body features of the molecule are computed using the message passing neural network based on the irreducible Cartesian tensor product. The molecular properties for the molecule are predicted based on the many-body features. The method has applications including, but not limited to, use cases in computational biology and medical Al and healthcare for optimizing vaccine design or supporting decision making in diagnosis and treatment of patients.
6.WO/2025/240664DRUG DEVELOPMENT AND DRUG ACTIVITY DETERMINATION FOR CHRONIC LIVER DISEASE, NASH, ADIPOSITY, AND DIABETES
WO - 20.11.2025
Int.Class G16B 35/10
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
35ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
10Design of libraries
 Appl.No PCT/US2025/029437 Applicant FORESITE LABS, LLC Inventor BLACK, Mary Helen
The present disclosure relates to systems, methods and computer program products for drug development for chronic liver disease (CLD) or non-alcoholic steatohepatitis (NASH) using in silico techniques. An aspect of the disclosure is directed to an in silico method for determining drug activity of a plurality of drug targets by determining biomarker stratifier effects, calculating a biomarker stratifier score for a chosen disease phenotype; and calculating a pharmacomimetic genetic score using molecular biomarker stratifier data.
7.WO/2025/236070AI-ASSISTED SOIL COMPACTION SYSTEM AND METHODS
WO - 20.11.2025
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/CA2025/050457 Applicant COMPACTICA SYSTEMS INC. Inventor ALLEN, Scott
System and methods for modeling, planning, and monitoring soil compaction. Laboratory test and historical data establish an historical baseline. A predictive baseline is computed from the historical baseline and a predictive site model. During the soil compaction of a calibration area, a predictive compaction model is computed from providing compaction scores obtained from standard tests, loose measurement maps and a compacted vibration map. During the soil compaction vibration data is used in conjunction with the predictive compaction to compute a compaction value. Upon detecting that the compaction value is within the target compaction threshold, an operator is notified.
8.WO/2025/239144ENERGY PREDICTION DEVICE FOR CATALYTIC REACTION, REACTION RATE PREDICTION DEVICE FOR CATALYTIC REACTION, ENERGY PREDICTION METHOD FOR CATALYTIC REACTION, REACTION RATE PREDICTION METHOD FOR CATALYTIC REACTION, ENERGY PREDICTION PROGRAM FOR CATALYTIC REACTION, AND REACTION RATE PREDICTION PROGRAM FOR CATALYTIC REACTION
WO - 20.11.2025
Int.Class G16C 20/10
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
10Analysis or design of chemical reactions, syntheses or processes
 Appl.No PCT/JP2025/015497 Applicant ENEOS HOLDINGS, INC. Inventor YAYAMA, Yoshihiro
The energy prediction device for a catalytic reaction according to the present invention comprises: a regression model generation unit that generates a regression model for predicting the energy of a three-dimensional structure on the basis of the three-dimensional structure of an intermediate body and a transition state of the reactant generated in a process of generating a product from a reactant by a catalytic reaction in which a plurality of elementary reactions progressing in stages are repeated, and the energy of the three-dimensional structure; and an energy prediction unit that predicts the energy of the three-dimensional structure using the regression model.
9.WO/2025/240509LIGATION OF POLYNUCLEOTIDES BY LIGASES AND SCREENING METHODS THEREOF
WO - 20.11.2025
Int.Class C12Q 1/25
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
25involving enzymes not classifiable in groups C12Q1/26-C12Q1/7097
 Appl.No PCT/US2025/029185 Applicant CODEXIS, INC. Inventor BIMM, Alexander, Jacob
The present disclosure provides a method of predicting a reaction condition activity profile of a ligase for a ligase substrate by Gaussian Process Regression using activity data obtained for different reaction conditions. Further provided is a method of screening a plurality of ligases for activity on a ligase substrate for identifying ligases active on the ligase substrate.
10.WO/2025/234376METHOD FOR PREDICTING AND ANALYZING PHYSICAL PROPERTIES OF RUBBER MATERIAL
WO - 13.11.2025
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/JP2025/016319 Applicant SUMITOMO RUBBER INDUSTRIES, LTD. Inventor ITO, Wakana
The present invention provides a method for predicting physical properties of a rubber material having high prediction accuracy. The present invention pertains to a method for predicting physical properties of a rubber material that is being continuously produced.
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