Document Type
Article
Publication Date
July 2024
Patent Number
12051512
Abstract
A method for predicting side effects of a combination of drugs administered concurrently includes training a multi-modal cell complex neural network (MCXN) on a dataset. The MCXN includes nodes representing the drugs and proteins, pair-wise relationships between nodes representing interactions between pairs of drugs and/or proteins, and k-wise relationships between the nodes representing interactions between k drugs and/or proteins, where k¿2. The training dataset includes a list of drugs, a list of proteins, and pharmacological information about the drugs in the list of drugs and proteins in the list of proteins. A specification of the combination of at least three drugs to be administered concurrently is input to the MCXN which predicts probabilities that administering the combination of drugs concurrently results in potential side effects. It also predicts both frequencies of the potential side effects and severities of the potential side effects.
Application Number
17/950906
Recommended Citation
Hajij, Mustafa; Alzamzmi, Ghada; and Miolane, Nina, "Multimodal cell complex neural networks for prediction of multiple drug side effects severity and frequency" (2024). USF Patents. 1432.
https://digitalcommons.usf.edu/usf_patents/1432
Assignees
Santa Clara University
Filing Date
09/22/2022
