The Nanomaterial Registry: facilitating the sharing and analysis of data in the diverse nanomaterial community

Ostraat, Michele L.; Mills, Karmann; Guzan, Kimberly; Murry, Damaris

doi:10.2147/ijn.s40722

Cited by 13 publications

(5 citation statements)

References 7 publications

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“…Another repository that compiles the available literature related to various categories of nanocarriers, including metallic nanocarriers, polymers or dendrimers, is called the Nanomaterial Registry. eNanoMapper is a complete database that specifically focuses on the safety information of nanomaterials [203].…”

Section: Applications Of Ai In the Development And Optimization Of Na...mentioning

confidence: 99%

Nanocarrier Drug Delivery Systems: Characterization, Limitations, Future Perspectives and Implementation of Artificial Intelligence

et al. 2022

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There has been an increasing demand for the development of nanocarriers targeting multiple diseases with a broad range of properties. Due to their tiny size, giant surface area and feasible targetability, nanocarriers have optimized efficacy, decreased side effects and improved stability over conventional drug dosage forms. There are diverse types of nanocarriers that have been synthesized for drug delivery, including dendrimers, liposomes, solid lipid nanoparticles, polymersomes, polymer–drug conjugates, polymeric nanoparticles, peptide nanoparticles, micelles, nanoemulsions, nanospheres, nanocapsules, nanoshells, carbon nanotubes and gold nanoparticles, etc. Several characterization techniques have been proposed and used over the past few decades to control and predict the behavior of nanocarriers both in vitro and in vivo. In this review, we describe some fundamental in vitro, ex vivo, in situ and in vivo characterization methods for most nanocarriers, emphasizing their advantages and limitations, as well as the safety, regulatory and manufacturing aspects that hinder the transfer of nanocarriers from the laboratory to the clinic. Moreover, integration of artificial intelligence with nanotechnology, as well as the advantages and problems of artificial intelligence in the development and optimization of nanocarriers, are also discussed, along with future perspectives.

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Section: Applications Of Ai In the Development And Optimization Of Na...mentioning

confidence: 99%

Nanocarrier Drug Delivery Systems: Characterization, Limitations, Future Perspectives and Implementation of Artificial Intelligence

et al. 2022

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“…The commonality among these approaches, however, is that they often only consider datasets containing properties relating to the pristine state of nanoparticles, thereby neglecting the impact of biotransformation. Furthermore, the technical barriers for nanomaterial grouping progress relate to data quality and assay selection [ 15 , 16 ]. Specifically, in the case of monitoring silver nanomaterials after ingestion, the lack of standardisation to recreate realistic exposure conditions (in terms of acute and chronic dosing, realistic composition for simulant gastro-intestinal juices, and dynamic digestion protocols) has prevented the identification of suitable descriptors [ 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Biotransformation of Silver Nanoparticles into Oro-Gastrointestinal Tract by Integrated In Vitro Testing Assay: Generation of Exposure-Dependent Physical Descriptors for Nanomaterial Grouping

et al. 2021

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Grouping approaches of nanomaterials have the potential to facilitate high throughput and cost effective nanomaterial screening. However, an effective grouping of nanomaterials hinges on the application of suitable physicochemical descriptors to identify similarities. To address the problem, we developed an integrated testing approach coupling acellular and cellular phases, to study the full life cycle of ingested silver nanoparticles (NPs) and silver salts in the oro-gastrointestinal (OGI) tract including their impact on cellular uptake and integrity. This approach enables the derivation of exposure-dependent physical descriptors (EDPDs) upon biotransformation of undigested nanoparticles, digested nanoparticles and digested silver salts. These descriptors are identified in: size, crystallinity, chemistry of the core material, dissolution, high and low molecular weight Ag-biomolecule soluble complexes, and are compared in terms of similarities in a grouping hypothesis. Experimental results indicate that digested silver nanoparticles are neither similar to pristine nanoparticles nor completely similar to digested silver salts, due to the presence of different chemical nanoforms (silver and silver chloride nanocrystals), which were characterized in terms of their interactions with the digestive matrices. Interestingly, the cellular responses observed in the cellular phase of the integrated assay (uptake and inflammation) are also similar for the digested samples, clearly indicating a possible role of the soluble fraction of silver complexes. This study highlights the importance of quantifying exposure-related physical descriptors to advance grouping of NPs based on structural similarities.

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“…An extensive list can be found in a review by Panneerselvam and Choi. 249 On the other hand, while there are experimental databases (e.g., caNanoLab, 250 NR, 251 and eNanoMapper 252 ) specifically for biological/medical applications, including physicochemical properties such as size, shape, composition, purity, surface area, toxicity, and environmental effects (reviews can be found in refs 253 and 254), a similar resource is not available for the purpose of materials science.…”

Section: Data-driven Nanomaterials Synthesismentioning

confidence: 99%

Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and Synthesis

et al. 2022

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The recent rise of computational, data-driven research has significant potential to accelerate materials discovery. Automated workflows and materials databases are being rapidly developed, contributing to high-throughput data of bulk materials that are growing in quantity and complexity, allowing for correlation between structural−chemical features and functional properties. In contrast, computational datadriven approaches are still relatively rare for nanomaterials discovery due to the rapid scaling of computational cost for finite systems. However, the distinct behaviors at the nanoscale as compared to the parent bulk materials and the vast tunability space with respect to dimensionality and morphology motivate the development of data sets for nanometric materials. In this review, we discuss the recent progress in data-driven research in two aspects: functional materials design and guided synthesis, including commonly used metrics and approaches for designing materials properties and predicting synthesis routes. More importantly, we discuss the distinct behaviors of materials as a result of nanosizing and the implications for data-driven research. Finally, we share our perspectives on future directions for extending the current data-driven research into the nano realm.

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The Nanomaterial Registry: facilitating the sharing and analysis of data in the diverse nanomaterial community

Cited by 13 publications

References 7 publications

Nanocarrier Drug Delivery Systems: Characterization, Limitations, Future Perspectives and Implementation of Artificial Intelligence

Nanocarrier Drug Delivery Systems: Characterization, Limitations, Future Perspectives and Implementation of Artificial Intelligence

Biotransformation of Silver Nanoparticles into Oro-Gastrointestinal Tract by Integrated In Vitro Testing Assay: Generation of Exposure-Dependent Physical Descriptors for Nanomaterial Grouping

Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and Synthesis

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