Data-driven prediction of drug combinations that mitigate adverse drug reactions
US11037656B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 16, 2019 |
| Grant date | Jun 15, 2021 |
| Priority date | — |
| Expiry date | Oct 16, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/022
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Predicting beneficial drug combinations mitigating adverse drug reactions identifies drug combinations and associated target adverse drug reaction from a spontaneous reporting system containing case reports of drugs and associated adverse drug reactions. Each drug combination comprises a first drug and a second drug, and a propensity score is computed for each drug in each group. This propensity score expresses a probability of being exposed to a given drug based on other co-prescribed drugs and reported indications, which reflect patient characteristics. Associations are computed for each drug as well as drug interaction. Among the associations, the sum of the associations of the second drug and the interaction effect represents the predicted beneficial score expressing whether the second drug alters the chance of developing the target adverse drug reaction for patients on the first drug. The interaction effect is referred to as predicted interaction score, and represents antagonistic or synergistic drug interactions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.