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A computational approach to predict multi-pathway drug-drug interactions: A case study of irinotecan, a colon cancer

Abdullah Assiri1, Adeeb Noor2

  • 1Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha 62529, Saudi Arabia.

Saudi Pharmaceutical Journal : SPJ : the Official Publication of the Saudi Pharmaceutical Society
|January 11, 2021
PubMed

Insights

Predicting complex drug-drug interactions (DDIs) is crucial for patient safety. This study introduces a novel Semantic Web-based method to forecast metabolic and transporter DDIs, using irinotecan as a case study.

Area of Science:

  • Pharmacology
  • Bioinformatics
  • Computational Chemistry

Background:

  • Drug-drug interactions (DDIs) pose significant health risks, ranging from discomfort to mortality.
  • Current research often overlooks multi-pathway DDIs, which can lead to severe complications.
  • Predicting and preventing complex DDIs requires advanced methodologies.

Purpose of the Study:

  • To introduce a novel method for predicting drug-drug interactions (DDIs) at both metabolic and transporter levels.
  • To demonstrate the method's validity using the chemotherapy agent irinotecan as a case study.
  • To highlight the need for evidence-based resources for DDI identification in clinical practice.

Main Methods:

  • Development of a rule-based model utilizing Semantic Web technologies.
  • Prediction of DDIs at two pharmacological levels: metabolic and transporter interactions.
  • Mining mechanistic and interaction data from available sources for case study analysis.

Main Results:

  • Successfully predicted potential interactors of irinotecan, including DDIs via previously unidentified mechanisms.
  • Demonstrated the capability of the novel method to identify complex, multi-pathway DDIs.
  • Highlighted significant variations among existing DDI resources.

Conclusions:

  • The proposed Semantic Web-based approach offers a promising method for predicting complex DDIs.
  • Accurate DDI prediction can enhance patient safety and inform clinical decision-making.
  • There is a critical need for a consolidated, evidence-based resource to support clinical DDI identification.
Keywords:
Colon cancerDrug-drug interactionIrinotecanMulti-pathwayPredictionSemantic web technologies

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