Northwestern University Patent Portfolio Statistics

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Northwestern University

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This article summarizes the perfomance of the assignee in the recent years. The overall statistics for this portfolio help to analyze the areas where the assignee is performing well. The filing trend, perfomance across the tech centers and the perfomance of the recent applications has been mentioned below. All the stats are calculated based on the perfomance in USPTO.

How does the overall patent portfolio of Northwestern University look like?

Assignee Art Units
Total Applications: 2,566 2,024,593
Granted Patents: 1,493 1,118,612
Grant Index 73.87% ↑ 69.09%
Abandoned/Rejected Applications: 528 (26.13%) 500,338 (30.91%)
In-Process Applications: 502 405,643
Average Grant Time: 2.93 Years ↑ 2.76 Years
Average Office Actions: 1.76 ↑ 1.68

Which Technology Area Northwestern University is filing most patents in? (Last 10 years)

Art Unit Definition Total Applications
Opap Parked GAU 160
1637 Molecular Biology, Bioinformatics, Nucleic Acids, Recombinant DNA and RNA, Gene Regulation, Nucleic Acid Amplification, Animals and Plants, Combinatorial/ Computational Chemistry 56
1634 Molecular Biology, Bioinformatics, Nucleic Acids, Recombinant DNA and RNA, Gene Regulation, Nucleic Acid Amplification, Animals and Plants, Combinatorial/ Computational Chemistry 54
1625 Organic Chemistry 48
1654 Fermentation, Microbiology, Isolated and Recombinant Proteins/Enzymes 44

How many patents are Northwestern University filing every year?

Year Total Applications Predicted
2022 0* 524
2021 120* 483
2020 207 367
2019 150 150
2018 127 –
2017 185 –
2016 154 –
2015 170 –
2014 121 –
2013 121 –

*The drop in the number of applications filed in last two years compared to previous years is because applications can take up to 18 months to get published

Recently filed patent applications of Northwestern University in USPTO?

Publication number: None
Application number: 17/637,410

Abstract:
–

Publication date: –
Applicant: Northwestern University
Inventors: Abecassis M Michael

Publication number: None
Application number: 17/635,444

Abstract:
–

Publication date: –
Applicant: Northwestern University
Inventors: D Jennifer Wu

Publication number: US20220194093A1
Application number: 16/970,873

Abstract:
The present invention provides an artificial intelligence-assisted printed electronics self-guided optimization method, which integrates machine learning technology with printed electronics. According to variables that impact printing quality of a microelectronic printer, a user sets up experimental groups, prints samples with the microelectronic printer according to parameters in the experiment groups, characterizes printing effects, and evaluates the printing quality. The characterization result is analyzed by machine learning, and printing parameters that correspond to a best printing effect are obtained; then, the parameters are fed back to the user, and the user configures the printer according to the fed-back parameters, thereby improving printing quality. By using the present invention, optimal printing parameters can be obtained by simply setting up a few simple experiments according to a number of factors that impact printing effects, which reduces the time for a printer user to test out printing effects in an early stage, and provides a good practicability.

Publication date: –
Applicant: Northwestern University
Inventors: Li Yue

How are Northwestern University’s applications performing in USPTO?

Application Number Title Status Art Unit Examiner
17/637,410 Blood Gene Biomarkers To Diagnose And Predict Acute Rejection In Liver Transplant Recipients Application Undergoing Preexam Processing – –
17/635,444 Materials And Methods For Activating Antigen-Specific T Cell Responses Application Undergoing Preexam Processing – –
16/970,873 Artificial Intelligence-Assisted Printed Electronics Self-Guided Optimization Method Docketed New Case – Ready for Examination OPAP Central, Docket
17/626,791 Ligand-Directed Reticular Synthesis Of Metal-Organic Frameworks Having Edge-Transitive Alb Network Topologies Sent to Classification contractor – –
17/617,367 Borophene-Based Two-Dimensional Heterostructures, Fabricating Methods And Applications Of Same Docketed New Case – Ready for Examination OPAP Central, Docket