Publication | Open Access
Simulation-based approaches for drug delivery systems: Navigating advancements, opportunities, and challenges
92
Citations
327
References
2023
Year
EngineeringSimulationBiomedical EngineeringMolecular DynamicsNanomedicinePharmaceutical TechnologyModeling And SimulationDrug Delivery SystemSystem SimulationNavigating AdvancementsDrug FormulationsBiophysicsSimulation-based ApproachesMolecular EngineeringPharmacologyDelivery SystemDrug Delivery SystemsNano-drug DeliveryMedicine
Efficient drug delivery systems (DDSs) play a pivotal role in ensuring pharmaceuticals' targeted and effective administration. However, the intricate interplay between drug formulations and delivery systems poses challenges in their design and optimization. Simulations have emerged as indispensable tools for comprehending these interactions and enhancing DDS performance to address this complexity. This comprehensive review explores the latest advancements in simulation techniques for drug delivery systems and provides a detailed analysis. The review encompasses various simulation methodologies, including molecular dynamics (MD), Monte Carlo (MC), finite element analysis (FEA), computational fluid dynamics (CFD), density functional theory (DFT), machine learning (ML), and dissipative particle dynamics (DPD). These techniques are critically examined in the context of drug delivery research. The article presents illustrative case studies involving liposomal, polymer-based, nano-particulate, and implantable DDSs, demonstrating the influential role of simulations in optimizing these systems. Furthermore, the review addresses the advantages and limitations of simulations in drug delivery research. It also identifies future directions for research and development, such as integrating multiple simulation techniques, refining and validating models for greater accuracy, overcoming computational limitations, and exploring applications of simulations in personalized medicine and innovative DDSs. Simulations employing various techniques like MD, MC, FEA, CFD, DFT, ML, and DPD offer crucial insights into drug behaviour, aiding in DDS design and optimization. Despite their advantages, including rapid and cost-effective screening, simulations require validation and addressing computational limitations. Future research should focus on integrating techniques, refining models, and exploring personalized medicine applications to enhance drug delivery outcomes. This paper underscores the indispensable contribution of simulations to drug research and development, emphasizing their role in providing valuable insights into drug behaviour, facilitating the development and optimization of DDSs, and ultimately enhancing patient outcomes. As we continue to explore and enhance simulation techniques, their impact on advancing drug discovery and improving DDSs is expected to be profound.
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