Drug-Drug Interactions Prediction Based on Similarity Calculation and Pharmacokinetics Mechanism

  • Quan Lu
  • Liangtao Zhang
  • Jing ChenEmail author
  • Zeyuan Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10983)


Drug-drug interactions (DDIs) are one of the major causes of adverse drug events (ADEs), therefore, the prediction of DDIs for avoiding the ADEs is an important issue, which can help medical researchers economize research related resources in clinical trials. This study aims to predict DDIs based on drug similarity and ontology reasoning, and accordingly gives some possible explanations to why these drugs have DDIs. we develop a DDIs ontology integrated with similar drugs and pharmacokinetics(PK) mechanism, and formulate rules for inferring DDIs. Our method extends the existing research ideas, not only adds extrapolation of unknown data, but also reduces reliance on known data, and innovatively combines similar drugs with PK mechanism, which proved to be useful for inferring DDIs and can give some possible explanations for these DDIs. Besides our study is less demanding for data type, and the rules are more concise.


Drug-drug interactions Pharmacokinetic mechanism Ontology Inference Similarity 



The authors gratefully acknowledge the financial support for this work provided by National Natural Science Foundation of China (No: 61772375 and 71420107026) and the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities (No: 17JJD870002).

Conflicts of Interest

The authors declare they have no conflicts of interest in this research.

Protection of Human and Animal Subjects

Neither human nor animal subjects were included in this project.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Center for Studies of Information ResourcesWuhan UniversityWuhanPeople’s Republic of China
  2. 2.School of Information ManagementWuhan UniversityWuhanPeople’s Republic of China
  3. 3.School of Information ManagementCentral China Normal UniversityWuhanPeople’s Republic of China
  4. 4.Henry Samueli School of Engineering and Applied ScienceUniversity of CaliforniaLos AngelesUSA

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