Finding precise causal multi-drug-drug interactions for adverse drug reaction analysis
US11211169B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 31, 2018 |
| Grant date | Dec 28, 2021 |
| Priority date | — |
| Expiry date | Jun 28, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/70
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Mechanisms are provided for implementing a framework to learn multiple drug-adverse drug reaction associations. The mechanisms receive and analyze patient electronic medical record data and adverse drug reaction data to identify co-occurrences of references to drugs with references to adverse drug reactions (ADRs) to thereby generate candidate rules specifying multiple drug-ADR relationships. The mechanisms filter the candidate rules to remove a subset of one or more rules having confounder drugs specified in the subset of one or more candidate rules, and thereby generate a filtered set of candidate rules. The mechanisms further generate a causal model based on the filtered set of candidate rules. The causal model comprises, for each ADR in a set of ADRs, a corresponding set of one or more rules, each rule specifying a combination of drugs having a causal relationship with the ADR.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.