Shape Transformable Strategies for Drug Delivery

Advanced Functional Materials, Journal Year: 2021, Volume and Issue: 31(18)

Published: Feb. 19, 2021

Abstract In tumor therapy, nanodrug delivery systems have gained momentum in the last decade. However, its efficacy remains insufficient for clinical applications. The physical properties of nanoparticles, including size, shape, and surface characteristics, can strongly affect efficacy. Ironically, research on shape function is relatively scarce, although nanoparticle greatly impacts their performance; example, nanorods with a high aspect ratio (AR) achieve greater accumulation, but penetration weak. Hence, rather than selecting suitable AR to balance them, strategy transformable (i.e., transformation) ideal this case. Nanoparticle transformation be achieved by either internal stimuli (such as pH enzymes) or external light) spatially temporally precision, thereby dramatically enhancing efficiency drug delivery. Thus, becoming promising prospect improving cancer treatment. review, first, effect summarized, then, recently are reviewed, finally, future direction shape‐transformable nanoparticles therapy discussed.

Language: Английский

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Design of Polymeric Carriers for Intracellular Peptide Delivery in Oncology Applications

Chemical Reviews, Journal Year: 2021, Volume and Issue: 121(18), P. 11653 - 11698

Published: Feb. 10, 2021

In recent decades, peptides, which can possess high potency, excellent selectivity, and low toxicity, have emerged as promising therapeutics for cancer applications. Combined with an improved understanding of tumor biology immuno-oncology, peptides demonstrated robust antitumor efficacy in preclinical models. However, the translation intracellular targets into clinical therapies has been severely hindered by limitations their intrinsic structure, such systemic stability, rapid clearance, poor membrane permeability, that impede delivery. this Review, we summarize advances polymer-mediated delivery therapy, including both therapeutic peptide antigens. We highlight strategies to engineer polymeric materials increase efficiency, especially cytosolic delivery, plays a crucial role potentiating peptide-based therapies. Finally, discuss future opportunities treatment, emphasis on design polymer nanocarriers optimized

Language: Английский

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Metal-phenolic networks for cancer theranostics

Biomaterials Science, Journal Year: 2021, Volume and Issue: 9(8), P. 2825 - 2849

Published: Jan. 1, 2021

Metal-phenolic networks (MPNs) have shown promising potential in biomedical applications since they provide a rapid, simple and robust way to construct multifunctional nanoplatforms. As novel nanomaterial self-assembled from metal ions polyphenols, MPNs can be prepared assist the theranostics of cancer owing their bio-adhesiveness, good biocompatibility, versatile drug loading, stimuli-responsive profile. This Critical Review aims summarize recent progress MPN-based nanoplatforms for multimodal tumor therapy imaging. First, advantages as carriers are summarized. Then, various therapeutic modalities based on introduced. Next, theranostic systems reviewed. In terms vivo applications, specific attention is paid biosafety, biodistribution, well excretion. Finally, some problems limitations discussed, along with future perspective field.

Language: Английский

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Nanotherapies for sepsis by regulating inflammatory signals and reactive oxygen and nitrogen species: New insight for treating COVID-19

Redox Biology, Journal Year: 2021, Volume and Issue: 45, P. 102046 - 102046

Published: June 15, 2021

SARS-CoV-2 has caused up to 127 million cases of COVID-19. Approximately 5% COVID-19 patients develop severe illness, and approximately 40% those with illness eventually die, corresponding more than 2.78 people. The pathological characteristics resemble typical sepsis, been identified as viral sepsis. Progress in sepsis research is important for improving the clinical care these patients. Recent advances understanding pathogenesis have led view that an uncontrolled inflammatory response oxidative stress are core factors. However, traditional treatment it difficult achieve a balance between inflammation, pathogens (viruses, bacteria, fungi), patient tolerance, resulting high mortality In recent years, nanomaterials mediating reactive oxygen nitrogen species (RONS) shown previously unattainable therapeutic effects on Despite advantages, RONS response-based yet be extensively adopted therapy. To best our knowledge, no review discussed application nanomaterials. help bridge this gap, we discuss related inflammation overproduction RONS, which activate pathogen-associated molecular pattern (PAMP)-pattern recognition receptor (PRR) damage-associated (DAMP)-PRR signaling pathways. We also summarize As highlighted here, strategy could synergistically improve efficacy against both may prolong survival. Current challenges future developments summarized.

Language: Английский

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Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

International Journal of Nanomedicine, Journal Year: 2022, Volume and Issue: Volume 17, P. 1365 - 1379

Published: March 1, 2022

Background: Low delivery efficiency of nanoparticles (NPs) to the tumor is a critical barrier in field cancer nanomedicine. Strategies on how improve NP remain be determined. Methods: This study analyzed roles physicochemical properties, models, and types using multiple machine learning artificial intelligence methods, data from recently published Nano-Tumor Database that contains 376 datasets generated physiologically based pharmacokinetic (PBPK) model. Results: The deep neural network model adequately predicted different NPs tumors it outperformed all other methods; including random forest, support vector machine, linear regression, bagged methods. adjusted determination coefficients (R 2 ) full training dataset were 0.92, 0.77, 0.77 0.76 for maximum (DE max ), at 24 h 168 last sampling time Tlast ). corresponding R values test 0.70, 0.46, 0.33 0.63, respectively. Also, this showed type was an important determinant predicting across endpoints (19– 29%). Among Zeta potential core material played greater role than such as type, shape, targeting strategy. Conclusion: provides quantitative design nanomedicine with efficiency. These results help our understanding causes low demonstrates feasibility integrating PBPK modeling approaches Graphical Abstract: Keywords: intelligence, learning, modeling, nanomedicine, drug delivery, nanotechnology

Language: Английский

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