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Pharmaceutics
Special Issues
Drug Interaction Mechanisms in Clinical Practice
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Drug Interaction Mechanisms in Clinical Practice

A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmacokinetics and Pharmacodynamics".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 3517

Special Issue Editors

Dr. Yoshihiro Noguchi

E-Mail Website
Guest Editor
Department of Pharmacy Practice and Science, Laboratory of Clinical Pharmacy, Gifu Pharmaceutical University, Gifu 500-0000, Japan
Interests: clinical pharmacology; pharmacovigilance; pharmacoepidemiology; drug interaction; real-world data
Dr. Shuji Yamashita

E-Mail Website
Guest Editor
Laboratory of Community Pharmaceutical Practice and Science, Gifu Pharmaceutical University, Gifu 500-0000, Japan
Interests: health care; clinical pharmacy; pharmacotherapy; clinical pharmacology; drug storage

Special Issue Information

Dear Colleagues,

The economic and health burden of adverse drug events has increased dramatically over the past few years. In particular, the proportion of unexpected adverse events due to drug interactions is estimated to be about 30% of all reported adverse events. Considering the recent polypharmacy in prescribing, early detection of adverse events due to drug interactions is one of the most critical issues in clinical practice.

Therefore, this special issue aims to highlight the mechanisms of drug-drug interactions from the perspective of clinical pharmacology, pharmacokinetics, and pharmacogenomics, as well as the search for signals of unknown interactions from the epidemiology perspective, for early detection and understanding of drug-drug interactions.

Dr. Yoshihiro Noguchi
Dr. Shuji Yamashita
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceutics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • drug interaction mechanisms
  • clinical pharmacology
  • pharmacovigilance
  • pharmacogenomics
  • pharmacokinetics

Published Papers (2 papers)

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20 pages, 1689 KiB  
Article
Improving Drug–Drug Interaction Extraction with Gaussian Noise
by Marco Molina, Cristina Jiménez and Carlos Montenegro
Pharmaceutics 2023, 15(7), 1823; https://doi.org/10.3390/pharmaceutics15071823 - 26 Jun 2023
Cited by 1 | Viewed by 1263
Abstract
Drug–Drug Interactions (DDIs) produce essential and valuable insights for healthcare professionals, since they provide data on the impact of concurrent administration of medications to patients during therapy. In that sense, some relevant works, related to the DDIExtraction2013 Challenge, are available in the current [...] Read more.
Drug–Drug Interactions (DDIs) produce essential and valuable insights for healthcare professionals, since they provide data on the impact of concurrent administration of medications to patients during therapy. In that sense, some relevant works, related to the DDIExtraction2013 Challenge, are available in the current technical literature. This study aims to improve previous results, using two models, where a Gaussian noise layer is added to achieve better DDI relationship extraction. (1) A Piecewise Convolutional Neural Network (PW-CNN) model is used to capture relationships among pharmacological entities described in biomedical databases. Additionally, the model incorporates multichannel words to enrich a person’s vocabulary and reduce unfamiliar words. (2) The model uses the pre-trained BERT language model to classify relationships, while also integrating data from the target entities. After identifying the target entities, the model transfers the relevant information through the pre-trained architecture and integrates the encoded data for both entities. The results of the experiment show an improved performance, with respect to previous models. Full article
(This article belongs to the Special Issue Drug Interaction Mechanisms in Clinical Practice)
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16 pages, 3585 KiB  
Systematic Review
Systematic Review and Meta-Analysis of the Effect of Loop Diuretics on Antibiotic Pharmacokinetics
by David A. Kerling, Sarah C. Clarke, Jesse P. DeLuca, Martin O. Evans, Adrian T. Kress, Robert J. Nadeau and Daniel J. Selig
Pharmaceutics 2023, 15(5), 1411; https://doi.org/10.3390/pharmaceutics15051411 - 05 May 2023
Cited by 1 | Viewed by 1837
Abstract
Loop diuretics and antibiotics are commonly co-prescribed across many clinical care settings. Loop diuretics may alter antibiotic pharmacokinetics (PK) via several potential drug interactions. A systematic review of the literature was performed to investigate the impact of loop diuretics on antibiotic PK. The [...] Read more.
Loop diuretics and antibiotics are commonly co-prescribed across many clinical care settings. Loop diuretics may alter antibiotic pharmacokinetics (PK) via several potential drug interactions. A systematic review of the literature was performed to investigate the impact of loop diuretics on antibiotic PK. The primary outcome metric was the ratio of means (ROM) of antibiotic PK parameters such as area under the curve (AUC) and volume of distribution (Vd) on and off loop diuretics. Twelve crossover studies were amenable for metanalysis. Coadministration of diuretics was associated with a mean 17% increase in plasma antibiotic AUC (ROM 1.17, 95% CI 1.09–1.25, I2 = 0%) and a mean decrease in antibiotic Vd by 11% (ROM 0.89, 95% CI 0.81–0.97, I2 = 0%). However, the half-life was not significantly different (ROM 1.06, 95% CI 0.99–1.13, I2 = 26%). The remaining 13 observational and population PK studies were heterogeneous in design and population, as well as prone to bias. No large trends were collectively observed in these studies. There is currently not enough evidence to support antibiotic dosing changes based on the presence or absence of loop diuretics alone. Further studies designed and powered to detect the effect of loop diuretics on antibiotic PK are warranted in applicable patient populations. Full article
(This article belongs to the Special Issue Drug Interaction Mechanisms in Clinical Practice)
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