Hokkaido University · Medicine
Professor Shungo Imai's research lab specializes in clinical pharmacology and pharmaceutical care, focusing on optimizing antibiotic therapy through advanced data-driven approaches. The lab primarily investigates vancomycin-induced nephrotoxicity and develops predictive models using machine learning techniques such as decision trees and artificial neural networks. Their work emphasizes improving patient safety by creating clinically applicable risk prediction models for adverse drug reactions at the time of initial drug administration. The lab also explores the impact of pharmacy services on therapeutic drug monitoring practices in real-world hospital settings.
Figures are computed from collected data and may differ slightly.
Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine. However, no studies have used artificial neural networks for the prediction of adverse drug reactions. We aimed to validate the usefulness of artificial neural networks for the prediction of adverse drug reactions and focused on vancomycin -induced nephrotoxicity. For constructing an artificial neural network, a multilayer
This study suggests the usefulness of DT models for the evaluation of adverse drug reactions.
This study aimed to construct an optimal algorithm for initial dose settings of vancomycin (VCM) using machine learning (ML) with decision tree (DT) analysis. Patients who were administered intravenous VCM and underwent therapeutic drug monitoring (TDM) at the Hokkaido University Hospital were enrolled. The study period was November 2011 to March 2019. In total, 654 patients were included in the study. Patients were divided into two groups, training (patients who received VCM from November 2011
Abstract Objectives In our previous study, we built a risk prediction model of vancomycin (VCM)‐associated nephrotoxicity using decision tree (DT) analysis. However, this has several limitations in clinical applications. Our objective here was to construct a clinically applicable risk prediction model to be used at the time of initial therapeutic drug monitoring (TDM), in patients with uncomplicated infections. Method A retrospective study was conducted at Hokkaido University Hospital. Subjects
We previously constructed a risk prediction model of vancomycin (VCM)-associated nephrotoxicity for use when performing initial therapeutic drug monitoring (TDM), using decision tree analysis. However, we could not build a model to be used at the time of initial administration due to insufficient sample size. Therefore, we performed a multicenter study at four hospitals in Japan. We investigated patients who received VCM intravenously at a standard dose from the first day until the initial TDM f
We found that the ward pharmacy service is associated with the active implementation of TDM for anti-MRSA agents, such as VCM and TEIC.
The anti-inflammatory agent colchicine may cause toxic effects such as rhabdomyolysis, pancytopenia, and acute respiratory distress syndrome in cases of overdose and when patients have renal or liver impairment. As colchicine is a substrate for CYP3A4 and P-glycoprotein (P-gp), drug-drug interactions are important factors that cause fatal colchicine-related side effects. Thus, we conducted a nation-wide survey to determine the status of inappropriate colchicine prescriptions in Japan. Patients p
We successfully built a risk prediction model of GCV-induced neutropaenia including severity grade. This model is expected to assist decision-making in the clinical setting.
Based on the predictive performance in our previous study, we switched the therapeutic drug monitoring (TDM) analysis software for dose setting of vancomycin (VCM) from "Vancomycin MEEK TDM analysis software Ver2.0" (MEEK) to "SHIONOGI-VCM-TDM ver.2009" (VCM-TDM) in January 2015. In the present study, our aim was to validate the effectiveness of the changing VCM TDM analysis software in initial dose setting of VCM. The enrolled patients were divided into two groups, each having 162 patients in t
A major adverse effect of benzbromarone is hepatotoxicity. Therefore, periodic liver function tests are required at least for the first 6 months of benzbromarone administration. However, it is not clear whether the relevant blood tests are implemented appropriately. Here, we performed a cross-sectional survey of the implementation status of liver function tests in patients who were newly prescribed benzbromarone, using the Japanese large claims database. Male patients who were newly prescribed b
The usefulness of disproportionality analysis for the pharmacovigilance of vaccines in the Japanese Adverse Drug Event Report (JADER) database is yet to be proven. This study aimed to verify whether significant disproportionality could be detected before adding new vaccine adverse event information to package inserts. Information on package insert revisions related to vaccine adverse drug events from January 2013 to March 2023 was extracted from the Pharmaceuticals and Medical Devices Agency web
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