Materials Today Proceedings, Год журнала: 2023, Номер unknown
Опубликована: Авг. 1, 2023
Язык: Английский
Advanced Drug Delivery Reviews, Год журнала: 2022, Номер 184, С. 114194 - 114194
Опубликована: Март 10, 2022
Язык: Английский
Процитировано
98
Engineering, Год журнала: 2023, Номер 27, С. 37 - 69
Опубликована: Апрель 28, 2023
Drug discovery and development affects various aspects of human health dramatically impacts the pharmaceutical market. However, investments in a new drug often go unrewarded due to long complex process research (R&D). With advancement experimental technology computer hardware, artificial intelligence (AI) has recently emerged as leading tool analyzing abundant high-dimensional data. Explosive growth size biomedical data provides advantages applying AI all stages R&D. Driven by big biomedicine, led revolution R&D, its ability discover drugs more efficiently at lower cost. This review begins with brief overview common models field discovery; then, it summarizes discusses depth their specific applications such target discovery, design, preclinical research, automated synthesis, influences Finally, major limitations R&D are fully discussed possible solutions proposed.
Язык: Английский
Процитировано
67
Journal of Molecular Liquids, Год журнала: 2023, Номер 395, С. 123888 - 123888
Опубликована: Дек. 27, 2023
Efficient drug delivery systems (DDSs) play a pivotal role in ensuring pharmaceuticals' targeted and effective administration. However, the intricate interplay between formulations poses challenges their design optimization. Simulations have emerged as indispensable tools for comprehending these interactions enhancing DDS performance to address this complexity. This comprehensive review explores latest advancements simulation techniques provides detailed analysis. The encompasses various methodologies, including molecular dynamics (MD), Monte Carlo (MC), finite element analysis (FEA), computational fluid (CFD), density functional theory (DFT), machine learning (ML), dissipative particle (DPD). These are critically examined context of research. article presents illustrative case studies involving liposomal, polymer-based, nano-particulate, implantable DDSs, demonstrating influential simulations optimizing systems. Furthermore, addresses advantages limitations It also identifies future directions research development, such integrating multiple techniques, refining validating models greater accuracy, overcoming limitations, exploring applications personalized medicine innovative DDSs. employing like MD, MC, FEA, CFD, DFT, ML, DPD offer crucial insights into behaviour, aiding Despite advantages, rapid cost-effective screening, require validation addressing limitations. Future should focus on models, enhance outcomes. paper underscores contribution emphasizing providing valuable facilitating development optimization ultimately patient As we continue explore impact advancing discovery improving DDSs is expected be profound.
Язык: Английский
Процитировано
61
Advanced Drug Delivery Reviews, Год журнала: 2023, Номер 202, С. 115108 - 115108
Опубликована: Сен. 27, 2023
Язык: Английский
Процитировано
56
Advanced Drug Delivery Reviews, Год журнала: 2023, Номер 199, С. 114974 - 114974
Опубликована: Июнь 24, 2023
Язык: Английский
Процитировано
51
Advanced Materials, Год журнала: 2025, Номер unknown
Опубликована: Фев. 9, 2025
Machine learning is increasingly being applied in polymer chemistry to link chemical structures macroscopic properties of polymers and identify patterns the that help improve specific properties. To facilitate this, a dataset needs be translated into machine readable descriptors. However, limited inadequately curated datasets, broad molecular weight distributions, irregular configurations pose significant challenges. Most off shelf mathematical models often need refinement for applications. Addressing these challenges demand close collaboration between chemists mathematicians as must formulate research questions terms while are required refine This review unites both disciplines address curation hurdles highlight advances synthesis modeling enhance data availability. It then surveys ML approaches used predict solid-state properties, solution behavior, composite performance, emerging applications such drug delivery polymer-biology interface. A perspective field concluded importance FAIR (findability, accessibility, interoperability, reusability) integration theory discussed, thoughts on machine-human interface shared.
Язык: Английский
Процитировано
6
Trends in Food Science & Technology, Год журнала: 2023, Номер 143, С. 104297 - 104297
Опубликована: Дек. 15, 2023
Язык: Английский
Процитировано
42
Nano Convergence, Год журнала: 2023, Номер 10(1)
Опубликована: Авг. 7, 2023
Abstract Cancer immunotherapy, which harnesses the power of immune system, has shown immense promise in fight against malignancies. Messenger RNA (mRNA) stands as a versatile instrument this context, with its capacity to encode tumor-associated antigens (TAAs), cell receptors, cytokines, and antibodies. Nevertheless, inherent structural instability mRNA requires development effective delivery systems. Lipid nanoparticles (LNPs) have emerged significant candidates for cancer providing both protection enhanced intracellular efficiency. In review, we offer comprehensive summary recent advancements LNP-based systems, focus on strategies optimizing design mRNA-encoded therapeutics treatment. Furthermore, delve into challenges encountered field contemplate future perspectives, aiming improve safety efficacy immunotherapies. Graphical
Язык: Английский
Процитировано
40
Materials Today Bio, Год журнала: 2023, Номер 20, С. 100672 - 100672
Опубликована: Май 18, 2023
Over the past three decades, nanoscience has offered a unique solution for reducing systemic toxicity of chemotherapy drugs and increasing drug therapeutic efficiency. However, poor accumulation pharmacokinetics nanoparticles are some key reasons their slow translation into clinic. The is intimately linked to non-biological nature aberrant features solid cancer, which together significantly compromise nanoparticle delivery. New findings on properties tumors interactions with human body suggest that, contrary what was long-believed, tumor may be more mirage than miracle, as enhanced permeability retention based efficacy estimated low 1%. In this review, we highlight current barriers available solutions pave way approved nanoformulations. Furthermore, aim discuss main solve inefficient delivery use nanobioengineering nanocarriers environment. Finally, will suggested strategies overcome two or biological one nanocarrier. variety design formats, applications implications each these methods also evaluated.
Язык: Английский
Процитировано
34
Global Challenges, Год журнала: 2023, Номер 8(1)
Опубликована: Ноя. 20, 2023
The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm knowledge discovery translational applications within precision medicine. Efficient management, analysis, interpretation big data can pave way for groundbreaking advancements However, unprecedented strides automated collection large-scale molecular clinical have also introduced formidable terms analysis interpretation, necessitating development novel computational approaches. Some potential include curse dimensionality, heterogeneity, missing data, class imbalance, scalability issues. This overview article focuses on recent progress breakthroughs application Key aspects are summarized, including content, sources, technologies, tools, challenges, existing gaps. Nine fields-Datawarehouse electronic medical record, imaging informatics, Artificial intelligence-aided surgical design surgery optimization, omics health monitoring graph, public security privacy-are discussed.
Язык: Английский
Процитировано
32