| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_e757fd4fedc4fe825bb81b1b466a0947 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F19-326
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F19-3456
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H70-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H20-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-20 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H70-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H10-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H20-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-48 |
| filingDate |
2014-05-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2020-10-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f9e827c333c709e7c09c4b601faa3d8d
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f141d24b29c11996c8bdb8de75f7c7a4
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_16bb2604c7c1ff5521ad2d5383b1376e
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_53552e67a73246bde0ffa5404e8324f0 |
| publicationDate |
2020-10-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-10803144-B2 |
| titleOfInvention |
Predicting drug-drug interactions based on clinical side effects |
| abstract |
A processor-implemented method, computer program product and system are provided for predicting drug-drug interactions based on clinical side effects. The method includes constructing a drug-drug interactions training dataset that includes pharmaceutical, pharmacokinetic or pharmacodynamics drug-drug interactions from multiple data sources for each of a plurality of drugs. The method also includes constructing side effect features for each of the drugs from side effects associated with the drugs. The method further includes building, using the drug-drug interactions training dataset, a drug-drug interactions classifier that predicts adverse drug-drug interactions for drug pairs derivable from the drugs. The method additionally includes for each of the side effects, building a two-by-two table using the side effect features, and performing a Fisher's exact test using the two-by-two table to determine whether a given one of side effects is differentially shown between positive predicted drug-drug interactions and negative predicted drug-drug interactions. |
| priorityDate |
2014-05-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |