Patents by Inventor Matthias BAL

Matthias BAL has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11995557
    Abstract: The invention is machine learning based method of, or system configured for, identifying candidate, small, drug-like molecules, in which a tensor network representation of molecular quantum states of a dataset of small, drug-like molecules is provided as an input to a machine learning system, such as a neural network system. The machine learning method or system may is itself configured as a tensor network. A training dataset may be used to train the machine learning system, and the training dataset is a tensor network representation of the molecular quantum states of small drug-like molecules.
    Type: Grant
    Filed: May 30, 2018
    Date of Patent: May 28, 2024
    Assignee: KUANO LTD.
    Inventors: Vid Stojevic, Noor Shaker, Matthias Bal
  • Publication number: 20230386610
    Abstract: A protein language natural language processing (NLP) system is trained to predict binding affinity. Amino acids of proteins are tokenized and masked. A first neural network is trained on TCR sequences and epitope sequences in an unsupervised or self-supervised manner. The information obtained from the first phase of training is applied in a subsequent training operation via transfer learning, to a second neural network. An annotated compact dataset is used to fine-tune the second neural network in a second phase of training, and in a supervised manner, to predict biophysiochemical properties of proteins, including TCR-epitope binding.
    Type: Application
    Filed: May 22, 2023
    Publication date: November 30, 2023
    Applicant: GLAXOSMITHKLINE BIOLOGICALS SA
    Inventors: Gurpreet SINGH, Ahmed ESSAGHIR, Paul SMYTH, Matthias BAL, Nanda Kumar SATHIYAMOORTHY
  • Publication number: 20220383992
    Abstract: There is provided a method for a machine learning based method of analysing drug-like molecules by representing the molecular quantum states of each drug-like molecule as a quantum graph, and then feeding that quantum graph as an input to a machine learning system.
    Type: Application
    Filed: July 17, 2019
    Publication date: December 1, 2022
    Inventors: Hagen TRIENDL, Matthias BAL, Jarvist Moore FROST, Lawrence PHILLIPS, Agisilaos CHANTZIS, Graham SIMPSON, Vic STOJEVIC, Noor SHAKER, Michael GRAIG, Usman BASHIR, Mariana MANN
  • Publication number: 20210398621
    Abstract: There is provided a quantum circuit based system configured to model infinite-size systems, in which one or more quantum circuits are configured as an infinite tensor network representation of quantum states of effectively infinite physical or chemical systems.
    Type: Application
    Filed: November 7, 2019
    Publication date: December 23, 2021
    Inventors: Vid STOJEVIC, Matthias BAL, Andrew GREEN
  • Publication number: 20210081804
    Abstract: The invention is machine learning based method of, or system configured for, identifying candidate, small, drug-like molecules, in which a tensor network representation of molecular quantum states of a dataset of small, drug-like molecules is provided as an input to a machine learning system, such as a neural network system. The machine learning method or system may is itself configured as a tensor network. A training dataset may be used to train the machine learning system, and the training dataset is a tensor network representation of the molecular quantum states of small drug-like molecules.
    Type: Application
    Filed: May 30, 2018
    Publication date: March 18, 2021
    Inventors: Vid STOJEVIC, Noor SHAKER, Matthias BAL