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A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases
- Source :
- Computer methods and programs in biomedicine. 163
- Publication Year :
- 2018
-
Abstract
- Background and objective Drug-drug interaction (DDI) is one of the main causes of toxicity and treatment inefficacy. This work focuses on non-communicable diseases (NCDs), the non-transmissible and long-lasting diseases since they are the leading cause of death globally. Drugs that are used in NCDs increase the probability of DDIs as a result of long time usage. This work proposes an Integrated Action Crossing (IAC) method that is effective in predicting the NCDs DDIs based on pharmacokinetic (PK) mechanism. Methods Drug-Enzyme (CYP450) and Drug-Transporter actions including substrate, inhibitor and inducer affect the PK mechanism of other drugs. Hence, this paper proposes an enzyme and transporter protein integrated action crossing method for DDIs prediction in NCDs. The NCDs Drugs information was retrieved from the DrugBank database and the actions of enzymes and transporter proteins that were crossed and integrated. The datasets were generated for machine training. Results Three machine learning approaches: Support Vector Machine, k-Nearest Neighbors, and Neural Networks were used for the assessment of the method. Performance evaluation was performed through five-fold cross validation and the different datasets and learning methods were compared. Two layers NNs achieved the best performance at the accuracy of 83.15% (F-Measure 85.23% and AUC 0.901). Conclusions The IAC method delivers better performance compared to the conventional method for the identification of NCDs DDIs.
- Subjects :
- 0301 basic medicine
Quantitative structure–activity relationship
Simvastatin
Support Vector Machine
Databases, Factual
Computer science
Drug-drug interaction
Quantitative Structure-Activity Relationship
Health Informatics
Machine learning
computer.software_genre
Machine Learning
03 medical and health sciences
0302 clinical medicine
Pharmacokinetics
Cytochrome P-450 Enzyme System
medicine
Cluster Analysis
Humans
Computer Simulation
Drug Interactions
False Positive Reactions
030212 general & internal medicine
Noncommunicable Diseases
Probability
chemistry.chemical_classification
business.industry
Mechanism (biology)
Substrate (chemistry)
Reproducibility of Results
Non-communicable disease
medicine.disease
Computer Science Applications
030104 developmental biology
Enzyme
chemistry
Area Under Curve
Toxicity
Artificial intelligence
Neural Networks, Computer
business
DrugBank
computer
Software
Algorithms
Subjects
Details
- ISSN :
- 18727565
- Volume :
- 163
- Database :
- OpenAIRE
- Journal :
- Computer methods and programs in biomedicine
- Accession number :
- edsair.doi.dedup.....94d47c30182c95fbda52d0f0fd00f540