Patents Assigned to Peptilogics, Inc.
  • Publication number: 20220059196
    Abstract: In one aspect, a method for pre-clinical validation of an effectiveness of a candidate drug compound is disclosed. The method may include receiving, at a processing device, a signal that comprises at least two wavelengths that are each associated with a respective biomarker, wherein the signal is received subsequent to administering the candidate drug compound to a proxy organism, such organism including at least two assays configured to reveal the respective biomarkers. The method also may include analyzing the signal to obtain the at least two wavelengths, and detecting, based on an analysis of the at least two wavelengths, whether each of the respective biomarkers are present.
    Type: Application
    Filed: August 16, 2021
    Publication date: February 24, 2022
    Applicant: Peptilogics, Inc.
    Inventors: Francis Lee, Jonathan D. Steckbeck, Hannes Holste
  • Publication number: 20210366581
    Abstract: A method is disclosed for using an artificial intelligence engine to generate candidate drug compounds, wherein the method comprises: generating candidate drug compounds comprising sequences via a creator module of the artificial intelligence engine. The method includes generating, via a descriptor module, a respective description for each of the candidate drug compounds at nodes in a knowledge graph, wherein the knowledge graph comprises a multi-dimensional representation of the candidate drug compounds and the respective description comprises drug compound structural information, drug compound activity information, and drug compound semantic information.
    Type: Application
    Filed: June 4, 2021
    Publication date: November 25, 2021
    Applicant: Peptilogics, Inc.
    Inventors: Francis Lee, Jonathan D. Steckbeck, Hannes Holste
  • Publication number: 20210304854
    Abstract: A method is disclosed for using an artificial intelligence engine to generate candidate drug compounds, wherein the method comprises: generating candidate drug compounds comprising sequences via a creator module of the artificial intelligence engine. The method includes generating, via a descriptor module, a respective description for each of the candidate drug compounds at nodes in a knowledge graph, wherein the knowledge graph comprises a multi-dimensional representation of the candidate drug compounds and the respective description comprises drug compound structural information, drug compound activity information, and drug compound semantic information.
    Type: Application
    Filed: June 4, 2021
    Publication date: September 30, 2021
    Applicant: Peptilogics, Inc.
    Inventors: Francis Lee, Jonathan D. Steckbeck, Hannes Holste
  • Publication number: 20210295955
    Abstract: An artificial intelligence engine architecture for generating candidate drugs is disclosed. In one embodiment, a method includes generating, via a creator module, a candidate drug compound including a sequence of a candidate drug compound, including the candidate drug compound as a node in a knowledge graph; generating, via a descriptor module, a description of the candidate drug compound at the node in the knowledge graph, wherein the description comprises drug compound structural information, drug compound activity information, and drug compound semantic information; based on the description, performing, via a scientist module, a benchmark analysis of a parameter of the creator module; and modifying, based on the benchmark analysis, the creator module to change the parameter in a desired way during a subsequent benchmark analysis.
    Type: Application
    Filed: June 4, 2021
    Publication date: September 23, 2021
    Applicant: Peptilogics, Inc.
    Inventors: Francis Lee, Jonathan D. Steckbeck, Hannes Holste
  • Publication number: 20210249108
    Abstract: An artificial intelligence engine for generating drug compounds is disclosed. In one embodiment, a method may include generating a biological context representation of a set of drug compounds. The biological context representation includes a first data structure having a first format. The method may also include translating, by the artificial intelligence engine, the first data structure having the first format to a second data structure having a second format. The method may also include generating, based on the second data structure having the second format, a set of candidate drug compounds. The method may also include classifying a candidate drug compound from the set of candidate drug compounds as a selected candidate drug compound.
    Type: Application
    Filed: January 29, 2021
    Publication date: August 12, 2021
    Applicant: PEPTILOGICS, INC.
    Inventors: Francis LEE, Jonathan D. STECKBECK, Hannes HOLSTE
  • Patent number: 11049590
    Abstract: An artificial intelligence engine architecture for generating candidate drugs is disclosed. In one embodiment, a method includes generating, via a creator module, a candidate drug compound including a sequence of a candidate drug compound, including the candidate drug compound as a node in a knowledge graph; generating, via a descriptor module, a description of the candidate drug compound at the node in the knowledge graph, wherein the description comprises drug compound structural information, drug compound activity information, and drug compound semantic information; based on the description, performing, via a scientist module, a benchmark analysis of a parameter of the creator module; and modifying, based on the benchmark analysis, the creator module to change the parameter in a desired way during a subsequent benchmark analysis.
    Type: Grant
    Filed: May 8, 2020
    Date of Patent: June 29, 2021
    Assignee: Peptilogics, Inc.
    Inventors: Francis Lee, Jonathan D. Steckbeck, Hannes Holste