Introduction: Complete delineation of the HIV-1 life cycle has resulted in the development of several antiretroviral drugs. Twenty-five therapeutic agents belonging to five different classes are currently available for the treatment of HIV-1 infections. Advent of triple combination antiretroviral therapy has significantly lowered the mortality rate in HIV patients. However, fungal infections still represent major opportunistic diseases in immunocompromised patients worldwide.
Areas Covered: Antiretroviral drugs that target enzymes and/or proteins indispensable for viral replication are discussed in this article. Fungal infections, causative organisms, epidemiology and preferred treatment modalities are also outlined. Finally, observed/predicted drug-drug interactions between antiretrovirals and antifungals are summarized along with clinical recommendations.
Expert Opinion: Concomitant use of amphotericin B and tenofovir must be closely monitored for renal functioning. Due to relatively weak interactive potential with the CYP450 system, fluconazole is the preferred antifungal drug. High itraconazole doses (> 200 mg/day) are not advised in patients receiving booster protease inhibitor (PI) regimen. Posaconazole is contraindicated in combination with either efavirenz or fosamprenavir. Moreover, voriconazole is contraindicated with high-dose ritonavir-boosted PI. Echinocandins may aid in overcoming the limitations of existing antifungal therapy. An increasing number of documented or predicted drug-drug interactions and therapeutic drug monitoring may aid in the management of HIV-associated opportunistic fungal infections.
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http://dx.doi.org/10.1517/17425255.2014.883379 | DOI Listing |
J Chem Inf Model
January 2025
Industrial and Molecular Pharmaceutics, Purdue University, West Lafayette, Indiana 47907, United States.
Drug-drug interaction can lead to diminished therapeutic effects or increased toxicity, posing significant risks, especially in polypharmacy, and cytochrome P450 plays an indispensable role in this interaction. Cytochrome P450, responsible for the metabolism and detoxification of most drugs, metabolizes about 90% of Food and Drug Administration-approved drugs, making early detection of potential drug-drug interactions. Over the years, in-silico modeling has become a valuable tool for predicting drug-drug interactions.
View Article and Find Full Text PDFJ Am Geriatr Soc
January 2025
School of Pharmacy, University of Washington, Seattle, Washington, USA.
Improving the quality of medication use and medication safety are important priorities for healthcare providers who care for older adults. The objective of this article was to identify four exemplary articles with this focus in 2023. We selected high-quality studies that advanced this field of research.
View Article and Find Full Text PDFComput Biol Med
January 2025
College of Electronic Information, Xijing University, Xi'an, China. Electronic address:
Accurate and efficient drug-drug interaction extraction (DDIE) from the medical corpus is essential for pharmacovigilance, drug therapy and drug development. To solve the problems of unbalance dataset and lack of accurate manual annotations in DDIE, a cross-attention guided Siamese quantum BiGRU (CA-SQBG) is constructed to improve feature representation learning ability for DDIE. It mainly consists of two quantum BiGRUs (QBiGRUs) and a cross-attention, where two QBiGRUs are Siamese implemented in a variational quantum environment to learn the contextual semantic feature representation of drug pairs, cross-attention is employed to learn mutual information from the Siamese QBiGRUs, which in turn allows the two modules to extract DDI more collaboratively.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
School of Computer Science and Technology, University of Science and Technology of China, 443 Huangshan Road, Hefei, 230027, China.
Background: Drug-drug interactions (DDIs) especially antagonistic ones present significant risks to patient safety, underscoring the urgent need for reliable prediction methods. Recently, substructure-based DDI prediction has garnered much attention due to the dominant influence of functional groups and substructures on drug properties. However, existing approaches face challenges regarding the insufficient interpretability of identified substructures and the isolation of chemical substructures.
View Article and Find Full Text PDFNaunyn Schmiedebergs Arch Pharmacol
January 2025
Department of Organ Transplantation, The Second Affiliated Hospital of Nanchang University, Minde Road No. 1, Nanchang, 330006, Jiangxi, China.
Multimorbidity, therapeutic complexity, and polypharmacy, which greatly increases the risk of drug-drug interactions (DDIs) and adverse medical outcomes, have become important and growing challenges in clinical practice. Statins are frequently prescribed to manage post-transplant dyslipidemia and reduce overall cardiovascular risk in solid organ transplant recipients. This study aimed to determine whether rosuvastatin has significant DDIs with tacrolimus (the first-line immunosuppressant) and to evaluate the risk of hepatotoxicity associated with concomitant therapy.
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