Patents Assigned to Janssen Research & Development, LLC
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Patent number: 12198025Abstract: Disclosed herein are methods for training and deploying a predictive model for generating a prediction, e.g., patient eligibility for a CAR-T therapy. Datasets, such as open healthcare claims datasets, may be missing data. Missing data may hamper the ability to generate sufficient information needed for training a predictive model. Methods include leveraging comprehensive datasets, such as closed claims datasets, to create training examples for input into a machine learning algorithm. In various embodiments, the comprehensive dataset is modified to simulate the data missingness in the target dataset; then, the modified dataset is paired with the ground truth label derived from the comprehensive dataset to create training examples. In various embodiments, a comprehensive dataset is paired with a target dataset to create training examples. After training a predictive model on such examples, the model can be deployed to make predictions in the target dataset even in light of missing data.Type: GrantFiled: July 29, 2022Date of Patent: January 14, 2025Assignee: JANSSEN RESEARCH & DEVELOPMENT, LLCInventors: Jennifer Seto Harper, Rajarshi Roychowdhury, Smita Mitra, Jeffrey John Headd
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Publication number: 20240390285Abstract: The present disclosure relates to a process for manufacturing an oral pharmaceutical dosage form including: mixing an active pharmaceutical ingredient (API) and surfactant into a blend; feeding the blend into a processor that applies heat and shear forces at a temperature within a range of approximately equal to the melting point of the surfactant to 3° C. below the melting point of the surfactant so as to form API granulates; and formulating the API granulates into a dosage form. The disclosed technology provides a surprisingly effective and economical means for producing high dose solid dosage forms containing poorly soluble APIs with minimal excipient burden.Type: ApplicationFiled: September 23, 2022Publication date: November 28, 2024Applicants: Rutgers, The State University of New Jersey, Janssen Research & Development, LLCInventors: Fernando J. Muzzio, Ivana M. Cotabarren, Shashwat Gupta, Qiushi Zhou, Thamer A. Omar, James Scicolone, Eric J. Sánchez-Rolon, Vipul Dave, George Oze
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Publication number: 20240120037Abstract: Methods of designing a hybrid clinical trial including an external control arm (ECA) study located in at least one site, to support a randomized clinical trial (RCT) study for a treatment of a condition are disclosed. A Mahalanobis distance value is calculated based on a point comprising a set of values corresponding to a first plurality of feature variables corresponding to at least one ECA candidate; and a distribution of points comprising a set of values corresponding to the first plurality of feature variables of each of a plurality of RCT participants that have received the treatment. ECA candidates may be excluded as ECA participants if they are deemed outliers based on the Mahalanobis distance value. Recruitment is dynamically adjusted into at least one ECA participant site database by comparing sets of feature variables in at least one ECA participant site database to corresponding sets of feature variables in the RCT participant database.Type: ApplicationFiled: October 4, 2023Publication date: April 11, 2024Applicant: Janssen Research & Development, LLC.Inventor: Levon Demirdjian
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Publication number: 20240055081Abstract: A deep learning pipeline can be configured to use medical image data to generate predictions of therapeutic responses to a new treatment in members of a cohort of interest of treatment candidates. A plurality of respective deep learning networks may be trained using respective medical image datasets having respective degrees of relevance to the cohort of interest. Learned parameters of one deep learning network may be transferred in succession to another deep learning network after training the one deep learning network with a one of the respective medical image datasets and before training the other deep learning network with another medical image dataset of the respective medical image datasets.Type: ApplicationFiled: August 15, 2023Publication date: February 15, 2024Applicant: Janssen Research & Development, LLCInventors: FNU Darshana Govind, Stephen Yip
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Publication number: 20230044574Abstract: Disclosed herein are methods for training and deploying a predictive model for generating a prediction, e.g., patient eligibility for a CAR-T therapy. Datasets, such as open healthcare claims datasets, may be missing data. Missing data may hamper the ability to generate sufficient information needed for training a predictive model. Methods include leveraging comprehensive datasets, such as closed claims datasets, to create training examples for input into a machine learning algorithm. In various embodiments, the comprehensive dataset is modified to simulate the data missingness in the target dataset; then, the modified dataset is paired with the ground truth label derived from the comprehensive dataset to create training examples. In various embodiments, a comprehensive dataset is paired with a target dataset to create training examples. After training a predictive model on such examples, the model can be deployed to make predictions in the target dataset even in light of missing data.Type: ApplicationFiled: July 29, 2022Publication date: February 9, 2023Applicant: Janssen Research & Development, LLCInventors: Jennifer Seto Harper, Rajarshi Roychowdhury, Smita Mitra, Jeffrey John Headd
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Patent number: 9012159Abstract: A method for identifying a compound which modulates the activity of acyl-coA: diacylglycerol acyltransferase comprises the steps of contacting a stable isotope labeled fatty acid with cells in either presence or absence of the compound, extracting the cells with isopropyl alcohol, and determining the level of a stable isotope labeled triglyceride in the presence or absence of the compound; wherein a change in the level of the stable isotope labeled triglyceride indicates that the compound modulates the DGAT activity.Type: GrantFiled: January 7, 2010Date of Patent: April 21, 2015Assignee: Janssen Research & Development, LLCInventors: Jian-Shen Qi, Wensheng Lang, Margery A. Connelly
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Patent number: 8852556Abstract: A method for evaluating the effect of a compound on vasomotor response in vivo comprises the steps of administering said compound to a rabbit and measuring the diameter of the vessel lumen of a central ear artery of said rabbit in comparison with the baseline diameter of the vessel lumen of said central ear artery of said rabbit, said baseline diameter being measured prior to the administration of said compound.Type: GrantFiled: October 21, 2009Date of Patent: October 7, 2014Assignee: Janssen Research & Development LLCInventors: Tom Jay Parry, Bruce P. Damiano, Edward C. Giardino, Margery A. Connelly
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Patent number: 8313920Abstract: A method of screening a compound which modulates dipeptidyl peptidase I (DPPI) activities comprises the steps of adding a peptide substrate of DPPI to a reaction mixture which comprises DPPI and a compound, wherein the peptide substrate of DPPI has at least 3 amino acids and binds to a binding site of DPPI in addition to the S1-S2 site; and measuring the molecular weight of the substrate, wherein a change in the molecular weight of the substrate is indicative of the presence of DPPI activity.Type: GrantFiled: October 21, 2009Date of Patent: November 20, 2012Assignee: Janssen Research & Development, LLCInventors: Matthew Olson, Matthew Todd