Nanoparticles in cancer diagnosis and treatment: Progress, challenges, and opportunities

Journal of Drug Delivery Science and Technology, Год журнала: 2024, Номер 95, С. 105599 - 105599

Опубликована: Март 26, 2024

Despite considerable progress in patient care, the global incidence of various cancer types continues to rise. Developing safer and more efficient anti-cancer treatment approaches are great interest. In recent decades, nanotechnology has emerged as a promising innovative medical approach for diagnosis treatment. However, nanomedicine advances, it is important understand address challenges. Herein, we identify gaps current understanding effectiveness on clinical outcomes provide an outlook improved application medicine. We discuss use different nanoparticles therapy impact efficiency existing treatments, such chemotherapeutic, anti-angiogenic, immunotherapeutic drugs, radiotherapy. Additionally, update status trials nanoparticle-based treatments provided.

Язык: Английский

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Nanosuspension Innovations: Expanding Horizons in Drug Delivery Techniques

Pharmaceutics, Год журнала: 2025, Номер 17(1), С. 136 - 136

Опубликована: Янв. 19, 2025

Nanosuspensions (NS), with their submicron particle sizes and unique physicochemical properties, provide a versatile solution for enhancing the administration of medications that are not highly soluble in water or lipids. This review highlights recent advancements, future prospects, challenges NS-based drug delivery, particularly oral, ocular, transdermal, pulmonary, parenteral routes. The conversion oral NS into powders, pellets, granules, tablets, capsules, incorporation film dosage forms to address stability concerns is thoroughly reviewed. article summarizes key stabilizers, polymers, surfactants, excipients used formulations, along ongoing clinical trials patents. Furthermore, comprehensive analysis various methods preparation provided. also explores vitro vivo characterization techniques, as well scale-down technologies bottom-up preparation. Selected examples commercial products discussed. Rapid advances field could resolve issues related permeability-limited absorption hepatic first-pass metabolism, offering promise based on proteins peptides. evolution novel stabilizers essential overcome current limitations stability, bioavailability, targeting ability, safety profile, which ultimately accelerates application commercialization.

Язык: Английский

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Machine Learning in Polymer Research

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

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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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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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Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling

Toxicological Sciences, Год журнала: 2022, Номер 191(1), С. 1 - 14

Опубликована: Сен. 22, 2022

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model requires the collection species-specific physiological, chemical-specific absorption, distribution, metabolism, excretion (ADME) parameters, which can be a time-consuming expensive process. This raises need to create computational capable predicting input parameter values for models, especially new compounds. In this review, we summarize an emerging paradigm integrating modeling with machine learning (ML) or artificial intelligence (AI)-based methods. includes 3 steps (1) obtain time-concentration PK data and/or ADME parameters from publicly available databases, (2) develop ML/AI-based approaches predict (3) incorporate ML/AI into summary statistics (eg, area under curve maximum plasma concentration). We also discuss neural network architecture "neural ordinary differential equation (Neural-ODE)" that is providing better predictive capabilities than other ML methods when used directly time-series profiles. order support applications development, several challenges should addressed as more become available, it important expand training set by including structural diversity compounds improve prediction accuracy models; due black box nature many lack sufficient interpretability limitation; Neural-ODE has great potential generate profiles limited information, but its application remains explored. Despite existing challenges, will continue facilitate efficient robust large number

Язык: Английский

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“Targeting Design” of Nanoparticles in Tumor Therapy

Pharmaceutics, Год журнала: 2022, Номер 14(9), С. 1919 - 1919

Опубликована: Сен. 11, 2022

Tumor-targeted therapy based on nanoparticles is a popular research direction in the biomedical field. After decades of and development, both passive targeting ability inherent properties NPs active ligand receptor interaction have gained deeper understanding. Unfortunately, most targeted delivery strategies are still preclinical trial stage, so it necessary to further study biological fate particles vivo mechanism with tumors. This article reviews different NPs, focuses physical chemical (size, morphology, surface intrinsic properties), ligands (binding number/force, activity species) receptors (endocytosis, distribution recycling) other factors that affect particle targeting. The limitations solutions these discussed, variety new schemes introduced, hoping provide guidance for future design achieve purpose rapid transformation into clinical application.

Язык: Английский

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Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer metastases

Pharmacological Research, Год журнала: 2023, Номер 189, С. 106706 - 106706

Опубликована: Фев. 20, 2023

Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In past decade, breakthroughs in field artificial intelligence (AI) have inspired development algorithms cancer setting. A growing body recent studies evaluated machine learning (ML) and deep (DL) for pre-screening, diagnosis management liver patients through diagnostic image analysis, biomarker discovery predicting personalized clinical outcomes. Despite promise these early AI tools, there is a significant need to explain 'black box' work towards deployment enable ultimate translatability. Certain emerging fields such as RNA nanomedicine targeted therapy may also benefit from application AI, specifically nano-formulation research given that they still largely reliant on lengthy trial-and-error experiments. this paper, we put forward current landscape along with challenges management. Finally, discussed future perspectives how multidisciplinary approach using could accelerate transition medicine bench side clinic.

Язык: Английский

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Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation

Chemical Reviews, Год журнала: 2023, Номер 123(13), С. 8575 - 8637

Опубликована: Июнь 1, 2023

Decades of nanotoxicology research have generated extensive and diverse data sets. However, is not equal to information. The question how extract critical information buried in vast streams. Here we show that artificial intelligence (AI) molecular simulation play key roles transforming nanotoxicity into information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, elucidating toxicity-related mechanisms. For AI realize their full impacts this mission, several obstacles must be overcome. These include paucity high-quality nanomaterials (NMs) standardized data, lack model-friendly databases, scarcity specific universal nanodescriptors, inability simulate NMs at realistic spatial temporal scales. This review provides a comprehensive representative, but exhaustive, summary current capability gaps tools required fill these formidable gaps. Specifically, discuss applications simulation, which can address large-scale challenge for research. need powerful new modeling approaches, mechanism analysis, design next-generation are also critically discussed. Finally, provide perspective on future trends challenges.

Язык: Английский

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Recent progress of 4D printing in cancer therapeutics studies

SLAS TECHNOLOGY, Год журнала: 2023, Номер 28(3), С. 127 - 141

Опубликована: Фев. 17, 2023

Cancer is a critical cause of global human death. Not only are complex approaches to cancer prognosis, accurate diagnosis, and efficient therapeutics concerned, but post-treatments like postsurgical or chemotherapeutical effects also followed up. The four-dimensional (4D) printing technique has gained attention for its potential applications in therapeutics. It the next generation three-dimensional (3D) technique, which facilitates advanced fabrication dynamic constructs programmable shapes, controllable locomotion, on-demand functions. As well-known, it still initial stage requires insight study 4D printing. Herein, we present first effort report on technology This review will illustrate mechanisms used induce management. recent be further detailed, future perspectives conclusions finally proposed.

Язык: Английский

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