| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_37b416a8c0d2b0f1c3d6026d932027af |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30024
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B40-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Q2600-158
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Q2600-106
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10064
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30056
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Q2600-142 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-68
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0012
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Q1-6883
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H30-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-533
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-5008 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-533
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H30-40 |
| filingDate |
2017-04-11-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2022-05-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c6dc8ecd43fe4a88a7bb689a735a955c
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bb524f84f8cafec01bdd67f2cc05bdc1
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_dc752e11d423029242ae538b47afc53d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_21ca75a9ce085f485244fe4a6c9aee15 |
| publicationDate |
2022-05-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-11321826-B2 |
| titleOfInvention |
High throughput method for accurate prediction of compound-induced liver injury |
| abstract |
A method and system for predicting liver injury in vivo due to hepatocyte damage by a test compound are provided. The method includes acquiring images of fluorescently stained cells obtained from a cell culture in which the cells have been treated with a dose-range of at least the test compound and its vehicle. The cells may be hepatic cells including primary or immortalized hepatocytes, hepatoma cells or induced pluripotent stem cell-derived hepatocyte-like cells. The acquired images are segmented. The method further includes extracting and analyzing one or more phenotypic features from the segmented images, wherein the one or more phenotypic features are selected from the group of intensity, textural, morphological, or ratiometric features consisting of (a) features of DNA, (b) features of RELA (NF-KB p65), and (c) features of actin filaments at different subcellular regions and d) features of cellular organelles and their substructures in the segmented images. Finally, the method includes normalizing results from the treated samples to vehicle controls and predicting the probability of liver injury by the test compound based on test compound-induced normalized changes of the extracted and selected phenotypic features using machine learning methods. |
| priorityDate |
2016-04-11-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |