Understanding Multidrug Resistance Mechanism in Cardiovascular Therapeutics: A Review Article
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Mohana G
Likhith N
Monalisa G
T. Selvan Kumar
Suresh Babu SV
Abstract
Multidrug resistance (MDR) is a main challenge in the management of cardiovascular diseases (CVDs), which restricts the efficacy of therapeutic actions and generates insufficient clinical results. Comprising efflux transporters like P-glycoprotein, genetic changes leading in changing drug targets, overexpression of drug-metabolizing enzymes, and dysregulated cellular pathways like PI3K/AKT and NF-κB, MDR processes are sophisticated and multifactional. Commonly used drugs including statins, antiplatelets, and antihypertensives have decreased therapeutic value when these systems affect drug absorption, distribution, or action. Patients-specific characteristics that worsen resistance even more and underline the requirement of customised treatments are medication non-adherence and genetic polymorphisms. Recent advances have focused on pharmacological control using efflux pump inhibitors, innovative drug delivery technologies including nanoparticles and liposomes, and genetic treatments including CRISpen and RNA therapies to overcome resistance pathways. Furthermore showing great potential in optimising therapy results is the mix of biomarker-guided treatment with pharmacogenomics. Still, significant challenges remain including regulatory barriers for innovative medicines, inadequate clinical translation of preclinical data, and low awareness of MDR routes in CVDs. Future research should pay high importance to identifying new resistance paths, applying artificial intelligence and machine learning for predictive modelling, and helping multidisciplinary teams to produce practical responses. Emphasising a diverse strategy integrating sophisticated research, personalised medicine, and creative technology to raise treatment efficacy and improve patient outcomes, this study underscores the vital need of concentrated efforts to combat MDR in cardiovascular therapy.
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This work is licensed under a Creative Commons Attribution 4.0 International License.