2023
DOI: 10.1039/d2nr06215a
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Microfluidic fabrication of photo-responsive Ansamitocin P-3 loaded liposomes for the treatment of breast cancer

Abstract: Ansamitocin P-3 (AP-3) is a promising anticancer agent. However, its low solubility has limited its biomedical applications. On the other hand, the preparation of liposomal formulations for drug delivery using...

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Cited by 11 publications
(7 citation statements)
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“…The total flow rates of the two phases were set at 10.5 and 40 mL/min. The two phases were injected into the inlets of the microfluidic device ,,, for the preparation of gelatin NPs. The particle size and PDI of the gelatin NPs were recorded to optimize the experimental conditions.…”
Section: Experimental Sectionmentioning
confidence: 99%
See 2 more Smart Citations
“…The total flow rates of the two phases were set at 10.5 and 40 mL/min. The two phases were injected into the inlets of the microfluidic device ,,, for the preparation of gelatin NPs. The particle size and PDI of the gelatin NPs were recorded to optimize the experimental conditions.…”
Section: Experimental Sectionmentioning
confidence: 99%
“…On the other hand, the controlled release of anticancer drugs can be achieved through the fine-tuning of the chemical properties of constituent materials used in NP fabrication. At present, commonly used biomaterials for nanodrug formulations include lipids (e.g., liposomes, lipid nanoparticles), polymers (e.g., PLGA, PLA, chitosan, alginate), and proteins (e.g., collagen, gelatin, silk, albumin). , Gelatin is a natural protein that can be obtained by partial acid or alkali hydrolysis, thermal degradation, or enzymatic degradation of structural animal collagen . Compared with collagen, gelatin does not express antigenicity in vivo and is easy to dissolve in an aqueous solution .…”
Section: Introductionmentioning
confidence: 99%
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“…Automation and AI methods are driving experimental science, particularly the discovery of new chemicals [13], genes [31], and materials [17], by enabling high throughput experiments. Beyond just executing the experiment, an AI algorithm can guide the experimental process sequentially by learning from the experiments it is performing.…”
Section: Introductionmentioning
confidence: 99%
“…This would enable humans to understand these hazardous odors and dramatically reduce the number of accidents based on hazardous odors such as natural gas leaked from pipelines 5 and volcanic gases. 6 To establish an automated odor-blending system, we need to develop three elements: an olfactory sensor [7][8][9][10][11][12][13] to replace the human sense of odors, blackbox optimization [14][15][16] to determine the amount of blending, and a robotic system [17][18][19][20][21][22][23][24][25] to perform actual blending of samples.…”
Section: Introductionmentioning
confidence: 99%