Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
4.9
Journals
Pharmaceutics
Special Issues
Drug–Drug Interactions—New Approaches and Perspectives
share announcement

Drug–Drug Interactions—New Approaches and Perspectives

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

Deadline for manuscript submissions: closed (10 August 2024) | Viewed by 7429

Special Issue Editor

Dr. Lucreția Udrescu

E-Mail Website
Guest Editor
Department I—Drug Analysis, “Victor Babeş” University of Medicine and Pharmacy Timişoara, 300041 Timişoara, Romania
Interests: drug repositioning; network pharmacology; drug–drug interactions; drug–drug similarity networks; drug solubility; drug bioavailability; biopharmacy; drug–cyclodextrin inclusion complexes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Drug–drug interactions represent a crucial factor affecting pharmacotherapeutic success. Good knowledge of the mechanisms of drug–drug interactions is vital for avoiding them. Accordingly, pharmacists and prescribing doctors must consider the clinical context when assessing drug interactions; the clinical relevance of the same drug combination can differ in distinct pathophysiological states (e.g., extreme ages, pregnancy, diabetes, immune-system-related disorders, and so on). Multiple morbidities in the elderly or specific clinical circumstances that require more than two drugs are conditions for drug–drug interactions that could affect the therapeutic outcome. To evaluate drug–drug interaction in a clinical context, healthcare specialists can use multiple online tools to check drug interactions. However, in practice, they may obtain contradicting results for the same drug combination (An even more unwanted case is when an online drug–drug interaction checker does not include a required drug).

Extensive wet-lab experiments to screen all potential drug–drug interactions will address the information uncertainty in many online check tools (based on existing drug–drug interaction databases). Unfortunately, such an approach would be unfeasible, as covering the entailed search space requires enormous resources. This situation calls for computational methods to predict drug–drug interactions; such tools would substantially narrow the wet-lab experiments search space.

This Special Issue calls for papers presenting multiple aspects of drug interactions relevant to their assessment: mechanisms, evaluation of the clinical relevance, prediction algorithms, electronic alert systems, and the Internet of Medical Things (IoMT) applied in the clinical evaluation of drug–drug and drug–disease interactions.

Dr. Lucreția Udrescu
Guest Editor

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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review, Other

14 pages, 472 KiB  
Article
Pharmacological Prescription at the End of Life: Quality Assessment in the Transition of Care to a Community Palliative Care Support Team
by Inês Rodrigues, Hugo Ribeiro, Carolina Costa, João Rocha-Neves and Marília Dourado
Pharmaceutics 2024, 16(9), 1152; https://doi.org/10.3390/pharmaceutics16091152 - 30 Aug 2024
Viewed by 490
Abstract
Appropriate pharmacological management is a cornerstone of quality in palliative care (PC), focusing on comfort and quality of life. Therapeutic review is crucial in PC, aiming to optimize symptom relief, reduce adverse effects, and manage drug interactions. This study aims to delve into [...] Read more.
Appropriate pharmacological management is a cornerstone of quality in palliative care (PC), focusing on comfort and quality of life. Therapeutic review is crucial in PC, aiming to optimize symptom relief, reduce adverse effects, and manage drug interactions. This study aims to delve into the real-world pharmacological prescription practices within a Community Palliative Care Support Team (CPCST) in the northern region of Portugal, comparing practices at admission and at the last consultation before death. It is an observational, cross-sectional, retrospective study without intervention involving patients admitted to a CPCST in 2021. Data were obtained from clinical records, and the statistical analysis included descriptive and inferential measures. Sixty-four patients were included, with an average age of 77.34 years, referred mainly by a specialized Hospital Palliative Care Support Team (65.63%). Polypharmacy was present, with a significant increase in opioids, antipsychotics, prokinetics, antiemetics, antispasmodics, and local corticosteroids, and a reduction in drugs for peptic ulcer and gastroesophageal reflux treatment, antithrombotics, hypolipidemics, antihypertensives, and antidiabetics, among others. The oral route was preferred, decreasing between the two analyzed moments (85.5% versus 49.1%). Pro re nata (PRN) medications increased significantly (p ≤ 0.001). The prescription profile reflects a focus on symptom relief. The deprescription of drugs for chronic comorbidities suggests adaptation to care goals. At the end of life, PRN medications increase significantly (1.34 versus 3.26, p ≤ 0.001), administered as needed to soothe fluctuating symptoms. The pharmacological classes that have significantly increased are relevant in alleviating common symptoms in PC. The use of alternative routes for medication administration increases as instability of the oral route occurs, leading to a reduction in orally administered medications. Among these alternatives, the subcutaneous route shows the largest increase. The findings underscore the importance of flexible and responsive medication strategies in end-of-life care. Full article
(This article belongs to the Special Issue Drug–Drug Interactions—New Approaches and Perspectives)
►▼ Show Figures

Figure 1

16 pages, 1021 KiB  
Article
Categorical Analysis of Database Consistency in Reporting Drug–Drug Interactions for Cardiovascular Diseases
by Liana Suciu, Sebastian Mihai Ardelean, Mihai Udrescu, Florina-Diana Goldiş, Daiana Hânda, Maria-Medana Tuică, Sabina-Oana Vasii and Lucreţia Udrescu
Pharmaceutics 2024, 16(3), 339; https://doi.org/10.3390/pharmaceutics16030339 - 28 Feb 2024
Viewed by 1051
Abstract
Drug–drug interactions (DDIs) can either enhance or diminish the positive or negative effects of the associated drugs. Multiple drug combinations create difficulties in identifying clinically relevant drug interactions; this is why electronic drug interaction checkers frequently report DDI results inconsistently. Our paper aims [...] Read more.
Drug–drug interactions (DDIs) can either enhance or diminish the positive or negative effects of the associated drugs. Multiple drug combinations create difficulties in identifying clinically relevant drug interactions; this is why electronic drug interaction checkers frequently report DDI results inconsistently. Our paper aims to analyze drug interactions in cardiovascular diseases by selecting drugs from pharmacotherapeutic subcategories of interest according to Level 2 of the Anatomical Therapeutic Chemical (ATC) classification system. We checked DDIs between 9316 pairs of cardiovascular drugs and 25,893 pairs of cardiovascular and other drugs. We then evaluated the overall agreement on DDI severity results between two electronic drug interaction checkers. Thus, we obtained a fair agreement for the DDIs between drugs in the cardiovascular category, as well as for the DDIs between drugs in the cardiovascular and other (i.e., non-cardiovascular) categories, as reflected by the Fleiss’ kappa coefficients of κ=0.3363 and κ=0.3572, respectively. The categorical analysis of agreement between ATC-defined subcategories reveals Fleiss’ kappa coefficients that indicate levels of agreement varying from poor agreement (κ<0) to perfect agreement (κ=1). The main drawback of the overall agreement assessment is that it includes DDIs between drugs in the same subcategory, a situation of therapeutic duplication seldom encountered in clinical practice. Our main conclusion is that the categorical analysis of the agreement on DDI is more insightful than the overall approach, as it allows a more thorough investigation of the disparities between DDI databases and better exposes the factors that influence the different responses of electronic drug interaction checkers. Using categorical analysis avoids potential inaccuracies caused by particularizing the results of an overall statistical analysis in a heterogeneous dataset. Full article
(This article belongs to the Special Issue Drug–Drug Interactions—New Approaches and Perspectives)
►▼ Show Figures

Figure 1

23 pages, 6277 KiB  
Article
Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis
by Michael Hecker, Niklas Frahm and Uwe Klaus Zettl
Pharmaceutics 2024, 16(1), 3; https://doi.org/10.3390/pharmaceutics16010003 - 19 Dec 2023
Cited by 2 | Viewed by 1701
Abstract
Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and [...] Read more.
Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and side effects. This is because a drug may alter the pharmacokinetic and/or pharmacodynamic properties of another drug, which is referred to as drug-drug interaction (DDI). We aimed to predict interactions of drugs that are used by patients with MS based on a deep neural network (DNN) using structural information as input. We further aimed to identify potential drug-food interactions (DFIs), which can affect drug efficacy and patient safety as well. We used DeepDDI, a multi-label classification model of specific DDI types, to predict changes in pharmacological effects and/or the risk of adverse drug events when two or more drugs are taken together. The original model with ~34 million trainable parameters was updated using >1 million DDIs recorded in the DrugBank database. Structure data of food components were obtained from the FooDB database. The medication plans of patients with MS (n = 627) were then searched for pairwise interactions between drug and food compounds. The updated DeepDDI model achieved accuracies of 92.2% and 92.1% on the validation and testing sets, respectively. The patients with MS used 312 different small molecule drugs as prescription or over-the-counter medications. In the medication plans, we identified 3748 DDIs in DrugBank and 13,365 DDIs using DeepDDI. At least one DDI was found for most patients (n = 509 or 81.2% based on the DNN model). The predictions revealed that many patients would be at increased risk of bleeding and bradycardic complications due to a potential DDI if they were to start a disease-modifying therapy with cladribine (n = 242 or 38.6%) and fingolimod (n = 279 or 44.5%), respectively. We also obtained numerous potential interactions for Bruton’s tyrosine kinase inhibitors that are in clinical development for MS, such as evobrutinib (n = 434 DDIs). Food sources most often related to DFIs were corn (n = 5456 DFIs) and cow’s milk (n = 4243 DFIs). We demonstrate that deep learning techniques can exploit chemical structure similarity to accurately predict DDIs and DFIs in patients with MS. Our study specifies drug pairs that potentially interact, suggests mechanisms causing adverse drug effects, informs about whether interacting drugs can be replaced with alternative drugs to avoid critical DDIs and provides dietary recommendations for MS patients who are taking certain drugs. Full article
(This article belongs to the Special Issue Drug–Drug Interactions—New Approaches and Perspectives)
►▼ Show Figures

Figure 1

Review

Jump to: Research, Other

34 pages, 8030 KiB  
Review
Drug–Drug Interactions in Nosocomial Infections: An Updated Review for Clinicians
by Sorina Hîncu, Miruna-Maria Apetroaei, Gabriela Ștefan, Anca Ionela Fâcă, Andreea Letiția Arsene, Beatrice Mahler, Doina Drăgănescu, Adriana-Elena Tăerel, Emilia Stancu, Lucian Hîncu, Andreea Zamfirescu and Denisa Ioana Udeanu
Pharmaceutics 2024, 16(9), 1137; https://doi.org/10.3390/pharmaceutics16091137 - 28 Aug 2024
Viewed by 456
Abstract
Prevention, assessment, and identification of drug–drug interactions (DDIs) represent a challenge for healthcare professionals, especially in nosocomial settings. This narrative review aims to provide a thorough assessment of the most clinically significant DDIs for antibiotics used in healthcare-associated infections. Complex poly-pharmaceutical regimens, targeting [...] Read more.
Prevention, assessment, and identification of drug–drug interactions (DDIs) represent a challenge for healthcare professionals, especially in nosocomial settings. This narrative review aims to provide a thorough assessment of the most clinically significant DDIs for antibiotics used in healthcare-associated infections. Complex poly-pharmaceutical regimens, targeting multiple pathogens or targeting one pathogen in the presence of another comorbidity, have an increased predisposition to result in life-threatening DDIs. Recognising, assessing, and limiting DDIs in nosocomial infections offers promising opportunities for improving health outcomes. The objective of this review is to provide clinicians with practical advice to prevent or mitigate DDIs, with the aim of increasing the safety and effectiveness of therapy. DDI management is of significant importance for individualising therapy according to the patient, disease status, and associated comorbidities. Full article
(This article belongs to the Special Issue Drug–Drug Interactions—New Approaches and Perspectives)
►▼ Show Figures

Figure 1

Other

Jump to: Research, Review

40 pages, 1270 KiB  
Systematic Review
Clinical Relevance of Drug Interactions in People Living with Human Immunodeficiency Virus on Antiretroviral Therapy—Update 2022: Systematic Review
by Pedro Amariles, Mónica Rivera-Cadavid and Mauricio Ceballos
Pharmaceutics 2023, 15(10), 2488; https://doi.org/10.3390/pharmaceutics15102488 - 18 Oct 2023
Cited by 1 | Viewed by 2677
Abstract
Background: The clinical outcomes of antiretroviral drugs may be modified through drug interactions; thus, it is important to update the drug interactions in people living with HIV (PLHIV). Aim: To update clinically relevant drug interactions in PLHIV on antiretroviral therapy with novel drug [...] Read more.
Background: The clinical outcomes of antiretroviral drugs may be modified through drug interactions; thus, it is important to update the drug interactions in people living with HIV (PLHIV). Aim: To update clinically relevant drug interactions in PLHIV on antiretroviral therapy with novel drug interactions published from 2017 to 2022. Methods: A systematic review in Medline/PubMed database from July 2017 to December 2022 using the Mesh terms antiretroviral agents and drug interactions or herb–drug interactions or food–drug interactions. Publications with drug interactions in humans, in English or Spanish, and with full-text access were retrieved. The clinical relevance of drug interactions was grouped into five levels according to the gravity and probability of occurrence. Results: A total of 366 articles were identified, with 219 (including 87 citation lists) were included, which allowed for the identification of 471 drug interaction pairs; among them, 291 were systematically reported for the first time. In total 42 (14.4%) and 137 (47.1%) were level one and two, respectively, and 233 (80.1%) pairs were explained with the pharmacokinetic mechanism. Among these 291 pairs, protease inhibitors (PIs) and ritonavir/cobicistat-boosted PIs, as well as integrase strand transfer inhibitors (InSTIs), with 70 (24.1%) and 65 (22.3%) drug interaction pairs of levels one and two, respectively, were more frequent. Conclusions: In PLHIV on antiretroviral therapy, we identify 291 drug interaction pairs systematically reported for the first time, with 179 (61.5%) being assessed as clinically relevant (levels one and two). The pharmacokinetic mechanism was the most frequently identified. PIs, ritonavir/cobicistat-boosted PIs, and InSTIs were the antiretroviral groups with the highest number of clinically relevant drug interaction pairs (levels one and two). Full article
(This article belongs to the Special Issue Drug–Drug Interactions—New Approaches and Perspectives)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop