{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T04:24:16Z","timestamp":1774585456406,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:00:00Z","timestamp":1743033600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2014NextGenerationEU\u2014through the National Recovery and Resilience Plan of the Republic of Bulgaria","award":["BG-RRP-2.004-0009-C02"],"award-info":[{"award-number":["BG-RRP-2.004-0009-C02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmaceuticals"],"abstract":"<jats:p>Background: Pharmacotherapy of chronic heart failure (CHF) with a reduced ejection fraction includes a combination of drugs. Often, different groups of drugs are added together for the treatment of concomitant conditions, such as statins, anticoagulants, antiplatelet agents, and cardiac glycosides, which have a narrow therapeutic window. Increased medication intake is a prerequisite for the increased risk of potential adverse drug\u2013drug interactions (DDI), especially those occurring at the pharmacokinetic level. The main objectives of this study are to identify the most common potential pharmacokinetic drug\u2013drug interactions (pPKDDIs), to explore more complex cases, and to simulate and analyze them with appropriate software. Methods: The data selected for the simulations were collected over a two-year period from January 2014 to December 2015. Identification of the pPKDDIs was carried out using Lexicomp Drug interaction, while simulations were performed with Simcyp software (V20, R1). Results: The most common pharmacokinetic mechanisms responsible for the occurrence of drug\u2013drug interactions in the selected drugs with narrow therapeutic windows are those featuring the cytochrome isoforms CYP3A4 and 2C9 and the efflux pump\u2014P-glycoprotein (P-gp). Simulations with the available data in Simcyp software showed possibilities to analyze and evaluate pPKDDIs, which would be difficult to assess without appropriate software, as well as ways to manage them. Conclusions: The frequency and complexity of pPKDDIs in patients with cardiovascular disease are high. Therefore, such patients require a specific approach to reduce these risks as well as to optimize the therapy. An appropriate PBPK software with the necessary database would be suitable in these cases.<\/jats:p>","DOI":"10.3390\/ph18040477","type":"journal-article","created":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:06:35Z","timestamp":1743141995000},"page":"477","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Using Physiologically Based Pharmacokinetic Models for Assessing Pharmacokinetic Drug\u2013Drug Interactions in Patients with Chronic Heart Failure Taking Narrow Therapeutic Window Drugs"],"prefix":"10.3390","volume":"18","author":[{"given":"Nadezhda","family":"Hvarchanova","sequence":"first","affiliation":[{"name":"Department of Pharmacology, Toxicology and Pharmacotherapy, Faculty of Pharmacy, Medical University\u2014Varna, 9000 Varna, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5778-4043","authenticated-orcid":false,"given":"Maya","family":"Radeva-Ilieva","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, Toxicology and Pharmacotherapy, Faculty of Pharmacy, Medical University\u2014Varna, 9000 Varna, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1839-1452","authenticated-orcid":false,"given":"Kaloyan D.","family":"Georgiev","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, Toxicology and Pharmacotherapy, Faculty of Pharmacy, Medical University\u2014Varna, 9000 Varna, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,27]]},"reference":[{"key":"ref_1","unstructured":"GBD 2017 Disease and Injury Incidence and Prevalence Collaborators (2018). 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