Patents by Inventor Nathan A. Hotaling

Nathan A. Hotaling 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).

  • USING MACHINE LEARNING AND/OR NEURAL NETWORKS TO VALIDATE STEM CELLS AND THEIR DERIVATIVES (2-D CELLS AND 3-D TISSUES) FOR USE IN CELL THERAPY AND TISSUE ENGINEERED PRODUCTS
    Publication number: 20230154215
    Abstract: A method is provided for non-invasively predicting characteristics of one or more cells and cell derivatives. The method includes training a machine learning model using at least one of a plurality of training cell images representing a plurality of cells and data identifying characteristics for the plurality of cells. The method further includes receiving at least one test cell image representing at least one test cell being evaluated, the at least one test cell image being acquired noninvasively and based on absorbance as an absolute measure of light, and providing the at least one test cell image to the trained machine learning model. Using machine learning based on the trained machine learning model, characteristics of the at least one test cell are predicted. The method further includes generating, by the trained machine learning model, release criteria for clinical preparations of cells based on the predicted characteristics of the at least one test cell.
    Type: Application
    Filed: November 9, 2022
    Publication date: May 18, 2023
    Applicant: The United States of America,as represented by the Secretary,Department of Health and Human Services
    Inventors: Kapil Bharti, Nathan A. Hotaling, Nicholas J. Schaub, Carl G. Simon
  • Using machine learning and/or neural networks to validate stem cells and their derivatives (2-D cells and 3-D tissues) for use in cell therapy and tissue engineered products
    Patent number: 11531844
    Abstract: A method is provided for non-invasively predicting characteristics of one or more cells and cell derivatives. The method includes training a machine learning model using at least one of a plurality of training cell images representing a plurality of cells and data identifying characteristics for the plurality of cells. The method further includes receiving at least one test cell image representing at least one test cell being evaluated, the at least one test cell image being acquired non-invasively and based on absorbance as an absolute measure of light, and providing the at least one test cell image to the trained machine learning model. Using machine learning based on the trained machine learning model, characteristics of the at least one test cell are predicted. The method further includes generating, by the trained machine learning model, release criteria for clinical preparations of cells based on the predicted characteristics of the at least one test cell.
    Type: Grant
    Filed: March 15, 2019
    Date of Patent: December 20, 2022
    Assignee: The United States of America, as represented by the Secretary, Department of Health & Human Services
    Inventors: Kapil Bharti, Nathan A. Hotaling, Nicholas J. Schaub, Carl G. Simon
  • USING MACHINE LEARNING AND/OR NEURAL NETWORKS TO VALIDATE STEM CELLS AND THEIR DERIVATIVES (2-D CELLS AND 3-D TISSUES) FOR USE IN CELL THERAPY AND TISSUE ENGINEERED PRODUCTS
    Publication number: 20210117729
    Abstract: A method is provided for non-invasively predicting characteristics of one or more cells and cell derivatives. The method includes training a machine learning model using at least one of a plurality of training cell images representing a plurality of cells and data identifying characteristics for the plurality of cells. The method further includes receiving at least one test cell image representing at least one test cell being evaluated, the at least one test cell image being acquired non-invasively and based on absorbance as an absolute measure of light, and providing the at least one test cell image to the trained machine learning model. Using machine learning based on the trained machine learning model, characteristics of the at least one test cell are predicted. The method further includes generating, by the trained machine learning model, release criteria for clinical preparations of cells based on the predicted characteristics of the at least one test cell.
    Type: Application
    Filed: March 15, 2019
    Publication date: April 22, 2021
    Applicant: The United States of America, as represented by the Secretary, Department of Health & Human Services
    Inventors: Kapil BHARTI, Nathan A. HOTALING, Nicholas J. SCHAUB, Carl G. SIMON
  • KITS AND METHODS FOR DETERMINING PHYSIOLOGIC LEVEL(S) AND/OR RANGE(S) OF HEMOGLOBIN AND/OR DISEASE STATE
    Publication number: 20190212345
    Abstract: Diagnostic kits and methods configured to rapidly and non-invasively determine physiologic levels of hemoglobin. A diagnostic kit may include a chamber pre-filled with an indicator, the indicator solution including a tetramethylbenzidine (TMB) solution, the indicator being configured to change color; a collection device configured to collect a test sample from a subject. The kit may also include a hemoglobin physiologic level identifier legend, the legend indicating 1) at least one color of the indicator and 2) a physiologic level and/or range of the hemoglobin and/or disease state associated with the color.
    Type: Application
    Filed: March 14, 2019
    Publication date: July 11, 2019
    Inventors: Wilbur A. LAM, Morgan Byrd, Erika Tyburski, Michael L. Mckinnon, Siobhan O'Connor, Nathan A. Hotaling
  • Kits and methods for determining physiologic level(s) and/or range(s) of hemoglobin and/or disease state
    Patent number: 10234466
    Abstract: Diagnostic kits and methods configured to rapidly and non-invasively determine physiologic levels of hemoglobin. A diagnostic kit may include a chamber pre-filled with an indicator, the indicator solution including a tetramethylbenzidine (TMB) solution, the indicator being configured to change color; a collection device configured to collect a test sample from a subject. The kit may also include a hemoglobin physiologic level identifier legend, the legend indicating 1) at least one color of the indicator and 2) a physiologic level and/or range of the hemoglobin and/or disease state associated with the color.
    Type: Grant
    Filed: March 15, 2013
    Date of Patent: March 19, 2019
    Inventors: Wilbur A. Lam, Morgan Byrd, Erika Tyburski, Michael L. McKinnon, Siobhan O'Connor, Nathan A. Hotaling
  • KITS AND METHODS FOR DETERMINING PHYSIOLOGIC LEVEL(S) AND/OR RANGE(S) OF HEMOGLOBIN AND/OR DISEASE STATE
    Publication number: 20150140670
    Abstract: Diagnostic kits and methods configured to rapidly and non-invasively determine physiologic levels of hemoglobin. A diagnostic kit may include a chamber pre-filled with an indicator, the indicator solution including a tetramethylbenzidine (TMB) solution, the indicator being configured to change color; a collection device configured to collect a test sample from a subject. The kit may also include a hemoglobin physiologic level identifier legend, the legend indicating 1) at least one color of the indicator and 2) a physiologic level and/or range of the hemoglobin and/or disease state associated with the color.
    Type: Application
    Filed: March 15, 2013
    Publication date: May 21, 2015
    Inventors: WIlbur A. Lam, Morgan Byrd, Erika Tyburski, Michael L. McKinnon, Siobhan O'Connor, Nathan A. Hotaling