Invention Grant
- Patent Title: Data-driven prediction of drug combinations that mitigate adverse drug reactions
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Application No.: US16654539Application Date: 2019-10-16
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Publication No.: US11037656B2Publication Date: 2021-06-15
- Inventor: Jianying Hu , Ying Li , Zhaonan Sun , Ping Zhang
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agent Kristofer L. Haggerty
- Main IPC: G06N5/02
- IPC: G06N5/02 ; G16C20/30 ; G06N5/00

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.
Public/Granted literature
- US20200051670A1 DATA-DRIVEN PREDICTION OF DRUG COMBINATIONS THAT MITIGATE ADVERSE DRUG REACTIONS Public/Granted day:2020-02-13
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