Tool: NEO-DEER_Drug_Interaction: A Web-Tool for Machine Learning-Based Drug-Drug Interaction Prediction in NICU

Version: 1.0

Published: 2022-01-15

Contributors: Nadir Yalcin, PhD
                      Merve Kasikci, MSc
                      Hasan Tolga Celik, Assoc Prof, MD
                      Karel Allegaert, Prof, MD
                      Kutay Demirkan, Prof, PharmD
                      Sule Yigit, Prof, MD
                      Murat Yurdakok, Prof, MD

Logo Designer: Nuri Beydemir

Description: Prospectively 11,908 medication orders from 412 NICU patients over 17 months were comprehensively analyzed by a pediatric clinical pharmacist. A machine learning-based potential drug-drug interaction (PDDI) prediction tool was developed for these patients, with a total of 328 PDDI (75 of these clinically relevant) determined objectively by a risk analysis (matrix). The positive predictive value and AUC value are 0.917 and 0.929, respectively. It is estimated that PDDIs can be prevented before they occur, with the use of this free, user-friendly, online, non-registered, and high-performance web-tool, which predicts PDDIs in each patient admitted to the NICUs.