Revolutionizing Prostate Cancer Therapy: Artificial intelligence – based Nanocarriers for Precision Diagnosis and Treatment

Critical Reviews in Oncology/Hematology, Год журнала: 2025, Номер unknown, С. 104653 - 104653

Опубликована: Фев. 1, 2025

Язык: Английский

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Intelligence analysis of drug nanoparticles delivery efficiency to cancer tumor sites using machine learning models

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 6, 2025

This study focuses on the use of machine learning (ML) models to predict biodistribution nanoparticles in various organs, using a dataset derived from research nanoparticle behavior for cancer treatment. The includes both categorical and numerical variables related properties, with focus their distribution across organs such as tumor, heart, liver, spleen, lung, kidney tissues. In order address complex non-linear nature data, three were utilized: Bayesian Ridge Regression (BRR), Kernel (KRR), K-Nearest Neighbors (KNN). selection these was based wide range capabilities dealing relationships data complexity. To further model performance strength, also applied cutting-edge methods including Firefly Algorithm hyperparameter tuning Recursive Feature Elimination (RFE) feature selection. Based higher R² lower RMSE values most output parameters, concluded that (KRR) did better compared other predicting outcomes. revealed models, particularly KRR, exhibit high level efficiency accurately representing characteristics biodistribution. results obtained provide valuable insights into optimization predictive nanoparticles. These can be enhanced by advanced techniques.

Язык: Английский

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AI-Driven Innovations in Smart Multifunctional Nanocarriers for Drug and Gene Delivery: A Mini-Review

Critical Reviews in Oncology/Hematology, Год журнала: 2025, Номер unknown, С. 104701 - 104701

Опубликована: Март 1, 2025

Язык: Английский

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Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration

Biomolecules, Год журнала: 2025, Номер 15(3), С. 444 - 444

Опубликована: Март 20, 2025

Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targeting capabilities, and multifunctional modalities. Recent advancements material engineering have enabled the development of nanoparticles tailored for various techniques, including magnetic resonance (MRI), computed tomography (CT), positron emission (PET), ultrasound (US). These nanoscale agents improve sensitivity specificity, enabling early detection precise tumor characterization. Monte Carlo (MC) simulations play a pivotal role optimizing nanomaterial-based modeling their interactions with biological tissues, predicting contrast enhancement, refining dosimetry radiation-based techniques. computational methods provide valuable insights into nanoparticle behavior, aiding design more effective agents. Moreover, artificial intelligence (AI) machine learning (ML) approaches are transforming enhancing image reconstruction, automating segmentation, improving diagnostic accuracy. AI-driven models can also optimize MC-based accelerating data analysis through predictive modeling. This review explores latest imaging, highlighting synergy between nanotechnology, MC simulations, innovations. By integrating these interdisciplinary approaches, future technologies achieve unprecedented precision, paving way diagnostics personalized treatment strategies.

Язык: Английский

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Revisiting nanomedicine design strategies for follow-on products: A model-informed approach to optimize performance

Journal of Controlled Release, Год журнала: 2024, Номер 376, С. 1251 - 1270

Опубликована: Ноя. 12, 2024

Язык: Английский

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Artificial intelligence in tumor drug resistance: Mechanisms and treatment prospects

Опубликована: Фев. 1, 2025

Язык: Английский

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Hyaluronic acid-functionalized nanomedicines for CD44-receptors-mediated targeted cancer therapy: A review of selective targetability and biodistribution to tumor microenvironment

International Journal of Biological Macromolecules, Год журнала: 2025, Номер unknown, С. 142486 - 142486

Опубликована: Март 1, 2025

Язык: Английский

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Design Considerations for Organ-Selective Nanoparticles

ACS Nano, Год журнала: 2025, Номер unknown

Опубликована: Апрель 7, 2025

Nanoparticles (NPs) have been extensively researched for targeted diagnostic imaging and drug delivery, yet their clinical translation remains limited, with only a few achieving Food Drug Administration approval. This limited success is primarily due to challenges in precise organ- or tissue-specific targeting, which arise from off-target tissue accumulation suboptimal clearance profiles. Herein we examine the critical role of physicochemical properties, including size, surface charge, shape, elasticity, hardness, density, governing biodistribution, targetability, NPs. We highlight recent advancements engineering NPs showcasing both significant progress remaining field nanomedicine. Additionally, discuss emerging tools technologies that are being developed address these challenges. Based on insights materials science, biomedical engineering, computational biology, research, propose key design considerations next-generation nanomedicines enhanced organ selectivity.

Язык: Английский

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Orchestrating cancer therapy: Recent advances in nanoplatforms harmonize immunotherapy with multifaceted treatments

Materials Today Bio, Год журнала: 2024, Номер 30, С. 101386 - 101386

Опубликована: Дек. 9, 2024

Язык: Английский

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Utilization of artificial intelligence for evaluation of targeted cancer therapy via drug nanoparticles to estimate delivery efficiency to various sites

Chemometrics and Intelligent Laboratory Systems, Год журнала: 2024, Номер unknown, С. 105309 - 105309

Опубликована: Дек. 1, 2024

Язык: Английский

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