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Updated: Jul 1, 2025
07:51
High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
Published on: May 21, 2018
11.8K
Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction
Jia'an Qin1, Yuhe Yang2, Chao Ai3
1Beijing Institute of Clinical Pharmacy, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
International Journal of Antimicrobial Agents
|March 2, 2024
Summary
This study developed a machine learning model to predict feasible antibiotic combinations, aiming to reduce drug interaction risks. The Antibiotic Combination Recommendation Model (ACRM) supports safer antibiotic prescribing practices.
Area of Science:
- Pharmacology
- Infectious Diseases
- Computational Biology
Background:
- Rising antibiotic resistance necessitates effective combination therapies.
- Current antibiotic combination prescribing lacks rapid feasibility assessment and clear understanding of drug interaction risks.
Purpose of the Study:
- To develop a machine learning model for predicting feasible antibiotic combinations.
- To assess the correlation between antibiotic combinations and drug interactions.
- To support safer antibiotic usage and improve medication safety.
Main Methods:
- Statistical analysis of 16,101 antibiotic coprescriptions (2015-2023).
- Development of an Antibiotic Combination Recommendation Model (ACRM) using a feedforward neural network (FNN).
- Integration of sequential methods and DrugBank for drug interaction analysis.
Main Results:
- The ACRM was built using 55 antibiotics and 657 combinations, achieving prediction accuracies of 61.54-73.33% in a retrospective cohort.
- AUROCs ranged from 0.589-0.895 for various recommendation classes.
- A positive correlation was found between recommended combinations and drug interaction risk (29.2% for strongly recommended vs. 43.5% for not recommended).
Conclusions:
- Machine learning effectively models retrospective antibiotic prescription data for combination recommendations.
- The ACRM aids in reducing drug interactions, enhancing antibiotic management.
- Adoption of such systems can improve clinical decision-making and medication safety.
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