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公开(公告)号：US20230053902A1
公开(公告)日：2023-02-23
申请号：US17690876
申请日：2022-03-09
Inventor： J. Christopher Love , Kerry R. Love , Laura Crowell , Alan Stockdale , Richard Dean Braatz , Amos Enshen Lu , Steven Cramer , Steven Timmick , Nicholas Vecchiarello , Chaz Goodwine , Craig A. Mascarenhas
Abstract: Aspects of the present disclosure relate to systems and methods for manufacturing biologically-produced pharmaceutical products. Some of the systems described herein comprise an upstream component comprising a bioreactor and at least one filter (e.g., a filter probe) integrated with a downstream component comprising a purification module comprising at least a first partitioning unit and a second partitioning unit. In some embodiments; these integrated biomanufacturing systems may be operated under continuous or conditions and may be capable of efficiently producing pure, high-quality pharmaceutical products.
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公开(公告)号：US20220137149A1
公开(公告)日：2022-05-05
申请号：US17218829
申请日：2021-03-31
Applicant: Toyota Research Institute, Inc. , The Board of Trustees of the Leland Stanford Junior University , Massachusetts Institute of Technology
Inventor： William C. Chueh , Bruis van Vlijmen , William E. Gent , Vivek Lam , Patrick K. Herring , Chirranjeevi Balaji Gopal , Patrick A. Asinger , Benben Jiang , Richard Dean Braatz , Xiao Cui , Gabriel B. Crane
IPC: G01R31/3842 , G01R31/392 , G01R31/36 , G01R31/367 , B60L58/16 , G06N20/00
Abstract: System, methods, and other embodiments described herein relate to improving the estimation of battery life. In one embodiment, a method includes measuring electrochemical data of a battery cell associated with an electrochemical reaction triggered by a test during a diagnostic cycle. The method also includes determining a feature associated with the degradation of the battery cell from the electrochemical data. The method also includes predicting an end-of-life (EOL) of the battery cell by using the feature in a machine learning (ML) model.
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公开(公告)号：US20190070564A1
公开(公告)日：2019-03-07
申请号：US16120200
申请日：2018-08-31
Applicant: Massachusetts Institute of Technology
Inventor： J. Christopher Love , Craig A. Mascarenhas , Amos Enshen Lu , Richard Dean Braatz
Abstract: Aspects of the present disclosure relate to filtration systems and methods for production of biologically-produced products, which may include pharmaceutical and/or protein products. Certain biomanufacturing systems described herein comprise a bioreactor (e.g., a perfusion bioreactor, a chemostat) and a filter probe comprising a filter bundle comprising a plurality of hollow fibers (e.g., longitudinally aligned hollow fibers). According to some embodiments, a center-to-center distance between any two hollow fibers within the fiber bundle at one or more points along a length of the fiber bundle is relatively large (e.g., greater than or equal to an average outer diameter of the hollow fibers of the fiber bundle, greater than or equal to 1.1 times a minimum diameter of the two hollow fibers). In some embodiments, the hollow fibers within the fiber bundle are arranged in an array (e.g., a hexagonal, linear, annular, or square array).
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公开(公告)号：US11226374B2
公开(公告)日：2022-01-18
申请号：US16161852
申请日：2018-10-16
Applicant: The Board of Trustees of the Leland Stanford Junior University , Massachusetts Institute of Technology
Inventor： Kristen Ann Severson , Richard Dean Braatz , William C. Chueh , Peter M. Attia , Norman Jin , Stephen J. Harris , Nicholas Perkins
IPC: G01R31/3842 , G01R31/36 , H01M10/44 , H01M10/48 , H01M10/0525
Abstract: A method of using data-driven predictive modeling to predict and classify battery cells by lifetime is provided that includes collecting a training dataset by cycling battery cells between a voltage V1 and a voltage V2, continuously measuring battery cell voltage, current, can temperature, and internal resistance during cycling, generating a discharge voltage curve for each cell that is dependent on a discharge capacity for a given cycle, calculating, using data from the discharge voltage curve, a cycle-to-cycle evolution of cell charge to output a cell voltage versus charge curve Q(V), generating transformations of ΔQ(V), generating transformations of data streams that include capacity, temperature and internal resistance, applying a machine learning model to determine a combination of a subset of the transformations to predict cell operation characteristics, and applying the machine learning model to output the predicted battery operation characteristics.
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公开(公告)号：US10987636B2
公开(公告)日：2021-04-27
申请号：US16120200
申请日：2018-08-31
Applicant: Massachusetts Institute of Technology
Inventor： J. Christopher Love , Craig A. Mascarenhas , Amos Enshen Lu , Richard Dean Braatz
Abstract: Aspects of the present disclosure relate to filtration systems and methods for production of biologically-produced products, which may include pharmaceutical and/or protein products. Certain biomanufacturing systems described herein comprise a bioreactor (e.g., a perfusion bioreactor, a chemostat) and a filter probe comprising a filter bundle comprising a plurality of hollow fibers (e.g., longitudinally aligned hollow fibers). According to some embodiments, a center-to-center distance between any two hollow fibers within the fiber bundle at one or more points along a length of the fiber bundle is relatively large (e.g., greater than or equal to an average outer diameter of the hollow fibers of the fiber bundle, greater than or equal to 1.1 times a minimum diameter of the two hollow fibers). In some embodiments, the hollow fibers within the fiber bundle are arranged in an array (e.g., a hexagonal, linear, annular, or square array).
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Patent Agency Ranking
公开(公告)号：US20200224144A1
公开(公告)日：2020-07-16
申请号：US16499780
申请日：2018-03-30
Inventor： J. Christopher Love , Kerry R. Love , Laura Crowell , Alan Stockdale , Richard Dean Braatz , Amos Enshen Lu , Steven Cramer , Steven Timmick , Nicholas Vecchiarello , Chaz Goodwine , Craig A. Mascarenhas
Abstract: Aspects of the present disclosure relate to systems and methods for manufacturing biologically-produced pharmaceutical products. Some of the systems described herein comprise an upstream component comprising a bioreactor and at least one filter (e.g., a filter probe) integrated with a downstream component comprising a purification module comprising at least a first partitioning unit and a second partitioning unit. In some embodiments, these integrated biomanufacturing systems may be operated under continuous or conditions and may be capable of efficiently producing pure, high-quality pharmaceutical products.
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公开(公告)号：US20190113577A1
公开(公告)日：2019-04-18
申请号：US16161852
申请日：2018-10-16
Applicant: The Board of Trustees of the Leland Stanford Junior University , Massachusetts Institute of Technology
Inventor： Kristen Ann Severson , Richard Dean Braatz , William C. Chueh , Peter M. Attia , Norman Jin , Stephen J. Harris , Nicholas Perkins
IPC: G01R31/36 , H01M10/0525 , H01M10/48 , H01M10/44
Abstract: A method of using data-driven predictive modeling to predict and classify battery cells by lifetime is provided that includes collecting a training dataset by cycling battery cells between a voltage V1 and a voltage V2, continuously measuring battery cell voltage, current, can temperature, and internal resistance during cycling, generating a discharge voltage curve for each cell that is dependent on a discharge capacity for a given cycle, calculating, using data from the discharge voltage curve, a cycle-to-cycle evolution of cell charge to output a cell voltage versus charge curve Q(V), generating transformations of ΔQ(V), generating transformations of data streams that include capacity, temperature and internal resistance, applying a machine learning model to determine a combination of a subset of the transformations to predict cell operation characteristics, and applying the machine learning model to output the predicted battery operation characteristics.
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公开(公告)号：US11768249B2
公开(公告)日：2023-09-26
申请号：US17218829
申请日：2021-03-31
Applicant: Toyota Research Institute, Inc. , The Board of Trustees of the Leland Stanford Junior University , Massachusetts Institute of Technology
Inventor： William C. Chueh , Bruis van Vlijmen , William E. Gent , Vivek Lam , Patrick K. Herring , Chirranjeevi Balaji Gopal , Patrick A. Asinger , Benben Jiang , Richard Dean Braatz , Xiao Cui , Gabriel B. Crane
IPC: G01R31/3842 , G01R31/392 , G06N20/00 , G01R31/367 , B60L58/16 , G01R31/36
CPC classification number: G01R31/3842 , B60L58/16 , G01R31/367 , G01R31/3648 , G01R31/392 , G06N20/00
Abstract: System, methods, and other embodiments described herein relate to improving the estimation of battery life. In one embodiment, a method includes measuring electrochemical data of a battery cell associated with an electrochemical reaction triggered by a test during a diagnostic cycle. The method also includes determining a feature associated with the degradation of the battery cell from the electrochemical data. The method also includes predicting an end-of-life (EOL) of the battery cell by using the feature in a machine learning (ML) model.
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9.发明申请公开(公告)号：US20200251186A1
公开(公告)日：2020-08-06
申请号：US16499776
申请日：2018-03-30
Inventor： J. Christopher Love , Kerry R. Love , Steven Cramer , Steven Timmick , Nicholas Vecchiarello , Chaz Goodwine , Laura Crowell , Alan Stockdale , Richard Dean Braatz , Amos Enshen Lu
Abstract: Systems and methods for generating and evaluating candidate sequences of partitioning steps to partition at least one biologically produced product from at least one impurity. In some embodiments, a plurality of candidate sequences of partitioning steps may be generated, wherein at least one candidate sequence of the plurality of candidate sequences comprises a plurality of partitioning steps in a specified order. The plurality of candidate sequences may be evaluated. For instance, a data set associated with the at least one partitioning step may be accessed, the data set comprising: first data indicative of a behavior of the at least one biologically produced product with respect to the at least one partitioning step; and second data indicative of a behavior of the at least one impurity with respect to the at least one partitioning step. The at least one candidate sequence may be scored based at least in part on the data set.
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公开(公告)号：US20170354609A1
公开(公告)日：2017-12-14
申请号：US15620568
申请日：2017-06-12
Applicant: Massachusetts Institute of Technology
Inventor： Vibha Puri , Parind Mahendrakumar Desai , Keith D. Jensen , David Brancazio , Eranda Harinath , Alexander Racine Martinez , Jung Hoon Chun , Richard Dean Braatz , Allan S. Myerson , Bernhardt Levy Trout
CPC classification number: A61K9/2893 , A61K9/2013 , A61K9/2018 , A61K9/205 , A61K9/284 , A61K9/2853 , A61K31/343 , B29C45/14819 , B29C45/1615 , B29C45/1671 , B29K2029/04 , B29K2067/04 , B29K2071/02
Abstract: The disclosure describes an injection molding process for coating a tablet core to produce a coated pharmaceutical tablet, wherein the injection-molded coating is substantially continuous (e.g., completely covers the tablet core with no openings), and describes the resulting coated pharmaceutical tablet. The disclosure describes compositions for coatings and tablet cores and equipment suitable for performing the process.
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