| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Mulet, Xavier
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2022Biomimetic Metal-Organic Frameworks as Protective Scaffolds for Live-virus Encapsulation and Vaccine Stabilisation – TEM Staining Considerations.
- 2022Biomimetic Metal-Organic Frameworks as Protective Scaffolds for Live-virus Encapsulation and Vaccine Stabilisation – TEM Staining Considerations.
- 2022Underlying Polar and Nonpolar Modification MOF-Based Factors that Influence Permanent Porosity in Porous Liquidscitations
- 2021Underlying solvent-based factors that influence permanent porosity in porous liquidscitations
- 2019Encapsulation, Visualization and Expression of Genes with Biomimetically Mineralized Zeolitic Imidazolate Framework-8 (ZIF-8)citations
- 2017Limitations with solvent exchange methods for synthesis of colloidalfullerenescitations
- 2013Predicting properties of nanoparticles for drug delivery and tissue targeting
- 2012Predicting phase behaviour of nanostructured lipid-based self-assembled materials
- 2012Predicting complex phase behaviour of self-assembling drug delivery nanoparticles
- 2011Robust and predictive modelling of amphiphilic nanostructured nanoparticle drug delivery vehicle phase behaviour
Places of action
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document
Predicting properties of nanoparticles for drug delivery and tissue targeting
Abstract
Nanoparticles are playing an increasingly important role in medicine, spawning the new field of nanomedicine. Amphiphilic lyotropic liquid crystalline self-assembled nanomaterials have great potential as delivery vehicles for drugs and imaging agents as they are biodegradable, adaptable to multiple drug sizes and types, have enhanced physical and chemical stability, and enhanced tissue and cellular uptake, properties valuable for new therapeutic or diagnostic applications. However, little is known about the effect of the incorporated drug on the structure of nanoparticles. Predicting these properties is widely considered intractable. We present computational models for three drug delivery carriers, loaded with 10 drugs at six concentrations and two temperatures. These models predicted nanophase behavior for 11 new drugs.1 Subsequent synchrotron small-angle X-ray scattering experiments validated the predictions. Hard nanoparticles, i.e. metallic, metal oxide nanoparticles and quantum dots, also play an important and complementary role to soft nanoparticles in medicine, particularly in tissue targeting and diagnostics. Computational models allow rapid prediction of tissue specificities, cellular uptake, and potential toxicities of new and modified nanomaterials, and leverage sparse and expensive experimental data. We generated quantitative, predictive models of cellular uptake and apoptosis induced by nanoparticles for several cell types.2 Of the cell lines tested, only the p PaCa2 and HUVEC lines showed significant variation in uptake of surface modified nanoparticles and generated robust predictive computational models for uptake.1. Le, TC; Mulet, X; Burden, FR; Winkler, DA Mol. Pharmaceut. 2013 10, 1368 2. Epa, VC; Burden, FR; Tassa, C; Weissleder, R; Shaw, S; Winkler, DA. Nano Lett., 2012, 12, 5808.