Deargen has a total of 37 patents globally, out of which 11 have been granted. Of these 37 patents, more than 91% patents are active. Korea (South) is where Deargen has filed the maximum number of patents. Parallelly, Korea (South) seems to be the main focused R&D centre and also is the origin country of Deargen.
Deargen was founded in the year 2016. The Company operates as an artificial intelligence-based drug development platform company. The company conducts research on and owns core AI technologies in-silico, such as ‘prediction of bio-markers’, ‘selection of disease targets’, and ‘extraction of candidate substances for new drugs’, utilizing techniques of meta-analysis of genome big data and its unique AI technologies.
Do read about some of the most popular patents of Deargen which have been covered by us in this article and also you can find Deargen patents information, the worldwide patent filing activity and its patent filing trend over the years, and many other stats over Deargen patent portfolio.
How many patents does the CEO of Deargen have?
The CEO Gilsu Kang has 0 patent.
How many patents does Deargen have?
Deargen has a total of 37 patents globally. These patents belong to 23 unique patent families. Out of 37 patents, 34 patents are active.
How Many Patents did Deargen File Every Year?
Are you wondering why there is a drop in patent filing for the last two years? It is because a patent application can take up to 18 months to get published. Certainly, it doesn’t suggest a decrease in the patent filing.
| Year of Patents Filing or Grant | Deargen Applications Filed | Deargen Patents Granted |
| 2023 | 2 | 6 |
| 2022 | 18 | 1 |
| 2021 | 8 | 3 |
| 2020 | 2 | 1 |
| 2019 | 4 | – |
| 2018 | 1 | – |
| 2017 | 2 | – |
How many Deargen patents are Alive/Dead?
How Many Patents did Deargen File in Different Countries?
All the Patents were filed by Deargen in the Korea (South).
Where are Research Centres of Deargen Patents Located?
List of Deargen Patents
| Deargen Patents | Title |
| WO2023176998A1 | Method For Identifying Binding Area Having Selectivity For Target Protein |
| WO2023033280A1 | Data Sampling Method For Active Learning |
| WO2023033281A1 | Method For Predicting Affinity Between Drug And Target Substance |
| WO2023033282A1 | Method For Training Multi-Task Model |
| WO2023033283A1 | Method For Predicting Medicine For Controlling Entrance Of Virus Into Host |
| WO2023027278A1 | Curriculum-Based Active Learning Method |
| WO2023027281A1 | Genetic Information Analysis Method |
| WO2023027277A1 | Training Method For Neural Network Model Diversity |
| WO2023027282A1 | Method For Searching For Hit-Compound Candidates By Using Pharmacophore Characteristics |
| WO2023027279A1 | Method For Predicting Whether Or Not Atom Inside Chemical Structure Binds To Kinase |
| WO2023027280A1 | Method For Deriving Epitope Candidate |
| WO2022203097A1 | Composition, For Preventing And Treating Central Nervous System Disorders, Inhibiting Overproduction Of Tdp-43 Proteins By Controlling Atxn2 Which Is Stress Granule Controller |
| KR102576241B1 | Method For Predicting Complex Structure Of Protein And Ligand |
| KR102571178B1 | Method For Predict Affinity Between Drug And Target Substance |
| KR102554278B1 | Method For Predicting Structure Of Protein Using Twist-Based Structure Updates |
| KR102542574B1 | Method For Traing Protein Structure Prediction Model |
| KR102496015B1 | Method For Predicting New Medicine And Apparatus For Performing The Method |
| KR102494966B1 | Method To Predict Drug For Controlling Entry Of Virus Into The Host |
| KR102376212B1 | Gene Expression Marker Screening Method Using Neural Network Based On Gene Selection Algorithm |
| KR102341336B1 | Biomarker Composition For Predicting Prognosis Of Chronic Liver Diseases |
| KR102288299B1 | Biomarker Composition For Identifying Disease Progression Of Chronic Liver Diseases |
| KR102240928B1 | Pharmaceutical Composition For Prevention Or Treatment Of Central Nervous System Diseases By Tdp-43 Mediated Stress Granule Aggregation In Cells Via Inhibiting Atxn2 |
| KR102073020B1 | System And Method For Selecting Optimized Medical Features Using Neural Network |
| KR1020230134252A | Method For Identifying A Binding Site Having Selectivity Of A Target Protein |
| KR1020230122238A | Method Of Generating Prediction Model For Diabetic Sensorimotor Polyneuropathy Based On Machine Learning Technique |
| KR1020230088045A | Biomarker For Identifying Subtypes Of Cancer-Associated Fibroblasts And Use Thereof |
| KR1020230033562A | Classification Method For Predicting Kinase Binding Ability Of Atoms In Chemical Structures |
| KR1020230031420A | Method For Active Learning Based On Curriculum |
| KR1020230031419A | Method To Train Model For Diversity Of Neural Network Model |
| KR1020230032459A | Method Of Data Sampling For Active Learning |
| KR1020230032690A | Method For Training Multi-Task Model |
| KR1020230031761A | Method Of Analyze Genetic Information |
| KR1020230031760A | Method Of Identify Epitope Candidate |
| KR1020230031762A | Method Of Discover Hit-Compound Candidate Using Pharmacophore Feature |
| WO2022085855A1 | New Drug Prediction Method, And Apparatus For Performing Method |
| WO2019088759A1 | Method And System For Determining Feature Influence |
| KR1020190050230A | System And Method For Selecting Optimized Medical Features Using Neural Network |
What are Deargen’ key innovation segments?
What Technologies are Covered by Deargen?
The chart below distributes patents filed by Deargen