title: Prediction of milk/plasma drug concentration (M/P) ratio using support vector machine (SVM) method.
abstract: OBJECTIVE
  Development of reliable computational models to predict/classify milk-to-plasma (M/P) drug concentration ratio remains a challenging object. Support vector machine (SVM) method, as a new algorithm, was constructed to distinguish the potential risk of drugs to nursing infants.
  
  
  METHODS
  Each drug was represented by a large pool of descriptors, of which five were found to be most important for constructing the predictive models. Next, two classification models, linear discriminant analysis (LDA) and SVM, were developed with bootstrapping validation based on the selected molecular descriptors.
  
  
  CONCLUSIONS
  The classification accuracy of training set and test set for SVM was 90.63 and 90.00%, respectively. The total accuracy for SVM was 90.48%, which was higher than that of LDA (77.78%). Comparison of the two methods shows that the performance of SVM was better than that of LDA, which implies that the SVM method is an effective tool in evaluating the risk of drugs when experimental M/P ratios have not been investigated.
authors.affiliation: Department of Chemistry, Lanzhou University, Lanzhou, 730000, China.
authors.forename: Chunyan
authors.initials: C
authors.lastname: Zhao
authors.forename: Haixia
authors.initials: H
authors.lastname: Zhang
authors.forename: Xiaoyun
authors.initials: X
authors.lastname: Zhang
authors.forename: Ruisheng
authors.initials: R
authors.lastname: Zhang
authors.forename: Feng
authors.initials: F
authors.lastname: Luan
authors.forename: Mancang
authors.initials: M
authors.lastname: Liu
authors.forename: Zhide
authors.initials: Z
authors.lastname: Hu
authors.forename: Botao
authors.initials: B
authors.lastname: Fan
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D016014:Linear Models; D008895:Milk, Human / Q000737:chemistry*; D015233:Models, Statistical; D004364:Pharmaceutical Preparations / Q000032:analysis* / Q000378:metabolism; D010599:Pharmacokinetics; D010949:Plasma / Q000737:chemistry*; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D013329:Structure-Activity Relationship; D009626:Terminology as Topic
chemical_list: D004364:Pharmaceutical Preparations