An annotated corpus with nanomedicine and pharmacokinetic parameters

A vast amount of data on nanomedicines is being generated and published, and natural language processing (NLP) approaches can automate the extraction of unstructured text-based data. Annotated corpora are a key resource for NLP and information extraction methods which employ machine learning. Although corpora are available for pharmaceuticals, resources for nanomedicines and nanotechnology are still limited. To foster nanotechnology text mining (NanoNLP) efforts, we have constructed a corpus of annotated drug product inserts taken from the US Food and Drug Administration’s Drugs@FDA online database. In this work, we present the development of the Engineered Nanomedicine Database corpus to support the evaluation of nanomedicine entity extraction. The data were manually annotated for 21 entity mentions consisting of nanomedicine physicochemical characterization, exposure, and biologic response information of 41 Food and Drug Administration-approved nanomedicines. We evaluate the reliability of the manual annotations and demonstrate the use of the corpus by evaluating two state-of-the-art named entity extraction systems, OpenNLP and Stanford NER. The annotated corpus is available open source and, based on these results, guidelines and suggestions for future development of additional nanomedicine corpora are provided

Mapping Nanomedicine Terminology in the Regulatory Landscape

A common terminology is essential in any field of science and technology for a mutual understanding among different communities of experts and regulators, harmonisation of policy actions, standardisation of quality procedures and experimental testing, and the communication to the general public. It also allows effective revision of information for policy making and optimises research fund allocation. In particular, in emerging scientific fields with a high innovation potential, new terms, descriptions and definitions are quickly generated, which are then ambiguously used by stakeholders having diverse interests, coming from different scientific disciplines and/or from various regions. The application of nanotechnology in health -often called nanomedicine- is considered as such emerging and multidisciplinary field with a growing interest of various communities. In order to support a better understanding of terms used in the regulatory domain, the Nanomedicines Working Group of the International Pharmaceutical Regulators Forum (IPRF) has prioritised the need to map, compile and discuss the currently used terminology of regulatory scientists coming from different geographic areas. The JRC has taken the lead to identify and compile frequently used terms in the field by using web crawling and text mining tools as well as the manual extraction of terms. Websites of 13 regulatory authorities and clinical trial registries globally involved in regulating nanomedicines have been crawled. The compilation and analysis of extracted terms demonstrated sectorial and geographical differences in the frequency and type of nanomedicine related terms used in a regulatory context. Finally 31 relevant and most frequently used terms deriving from various agencies have been compiled, discussed and analysed for their similarities and differences. These descriptions will support the development of harmonised use of terminology in the future. The report provides necessary background information to advance the discussion among stakeholders. It will strengthen activities aiming to develop harmonised standards in the field of nanomedicine, which is an essential factor to stimulate innovation and industrial competitiveness.JRC.F.2-Consumer Products Safet

Nanoporous silica-based protocells at multiple scales for designs of life and nanomedicine.

Various protocell models have been constructed de novo with the bottom-up approach. Here we describe a silica-based protocell composed of a nanoporous amorphous silica core encapsulated within a lipid bilayer built by self-assembly that provides for independent definition of cell interior and the surface membrane. In this review, we will first describe the essential features of this architecture and then summarize the current development of silica-based protocells at both micro- and nanoscale with diverse functionalities. As the structure of the silica is relatively static, silica-core protocells do not have the ability to change shape, but their interior structure provides a highly crowded and, in some cases, authentic scaffold upon which biomolecular components and systems could be reconstituted. In basic research, the larger protocells based on precise silica replicas of cells could be developed into geometrically realistic bioreactor platforms to enable cellular functions like coupled biochemical reactions, while in translational research smaller protocells based on mesoporous silica nanoparticles are being developed for targeted nanomedicine. Ultimately we see two different motivations for protocell research and development: (1) to emulate life in order to understand it; and (2) to use biomimicry to engineer desired cellular interactions

PEGylated graphene oxide for tumor-targeted delivery of paclitaxel.

AIM: The graphene oxide (GO) sheet has been considered one of the most promising carbon derivatives in the field of material science for the past few years and has shown excellent tumor-targeting ability, biocompatibility and low toxicity. We have endeavored to conjugate paclitaxel (PTX) to GO molecule and investigate its anticancer efficacy. MATERIALS & METHODS: We conjugated the anticancer drug PTX to aminated PEG chains on GO sheets through covalent bonds to get GO-PEG-PTX complexes. The tissue distribution and anticancer efficacy of GO-PEG-PTX were then investigated using a B16 melanoma cancer-bearing C57 mice model. RESULTS: The GO-PEG-PTX complexes exhibited excellent water solubility and biocompatibility. Compared with the traditional formulation of PTX (Taxol®), GO-PEG-PTX has shown prolonged blood circulation time as well as high tumor-targeting and -suppressing efficacy. CONCLUSION: PEGylated graphene oxide is an excellent nanocarrier for paclitaxel for cancer targeting

Using natural language processing techniques to inform research on nanotechnology

Literature in the field of nanotechnology is exponentially increasing with more and more engineered nanomaterials being created, characterized, and tested for performance and safety. With the deluge of published data, there is a need for natural language processing approaches to semi-automate the cataloguing of engineered nanomaterials and their associated physico-chemical properties, performance, exposure scenarios, and biological effects. In this paper, we review the different informatics methods that have been applied to patent mining, nanomaterial/device characterization, nanomedicine, and environmental risk assessment. Nine natural language processing (NLP)-based tools were identified: NanoPort, NanoMapper, TechPerceptor, a Text Mining Framework, a Nanodevice Analyzer, a Clinical Trial Document Classifier, Nanotoxicity Searcher, NanoSifter, and NEIMiner. We conclude with recommendations for sharing NLP-related tools through online repositories to broaden participation in nanoinformatics

Creation of an Annotated Library on FDA Approved Nanomedicines

Nanomedicine is a type of nanotechnology used in the medical field to limit the dosage amount and target drug delivery to specific cells. Nanomedicines that are approved and used tend to be extremely successful; however despite over a decade of research, only a limited number of nanomedicines have advanced for clinical use. A possible reason for the numerous nanomedicine failures is lack of easily accessible information and research on previous nanomedicines. In this project, we have compiled nanomedicine labeling information from the Drugs@FDA website. We have extracted phrases/sentences from labels relating to keywords on nanomaterial properties and drug profile characteristics. In the future, we plan to incorporate discontinued nanomedicines, nanomedicines on the market, and nanomedicines in different clinical trial phases. By compiling the descriptions and contents of a set of specific nanomedicines, a machine learning program could be developed to comb through literature and automatically identify similar nanomedicine related entities. Our research works to provide an easier and quicker method to obtain specific information on approved nanomedicines.https://scholarscompass.vcu.edu/uresposters/1175/thumbnail.jp

Doctor of Philosophy

dissertationNanoinformatics is a relatively young field of study that is important due to its implications in the field of nanomedicine, specifically toward the development of nanoparticle drug delivery systems. As more structural, biochemical, and physiochemical data become available regarding nanoparticles, the greater the knowledge-gain from using nanoinformatics methods will become. While there are challenges that exist with nanoparticle data, including heterogeneity of data and complexity of the particles, nanoinformatics will be at the forefront of processing these data and aid in the design of nanoparticles for biomedical applications. In this dissertation, a review of data mining and machine learning studies performed in the field of nanomedicine is presented. Next, the use of natural language processing methods to extract numeric values of biomedical property terms of poly(amido amine) (PAMAM) dendrimers from nanomedicine literature is demonstrated, along with successful extraction results. Following this is an implementation and its results of data mining techniques used for the development of predictive models of cytotoxicity of PAMAM dendrimers using their chemical and structural properties. Finally, a method and its results for using molecular dynamics simulations to test the ability of EDTA, as a gold standard, and generation 3.5 (G3.5) PAMAM dendrimers to chelate calcium

Heparin: New life for an old drug

© 2017 Future Medicine Ltd. Heparin is one of the oldest drugs, which nevertheless remains in widespread clinical use as an inhibitor of blood coagulation. The history of its identification a century ago unfolded amid one of the most fascinating scientific controversies turning around the distribution of credit for its discovery. The composition, purification and structure-function relationship of this naturally occurring glycosaminoglycan regarding its classical role as anticoagulant will be dealt with before proceeding to discuss its therapeutic potential in, among other, inflammatory and infectious disease, cancer treatment, cystic fibrosis and Alzheimer's disease. The first bibliographic reference hit using the words 'nanomedicine' and 'heparin' is as recent as 2008. Since then, nanomedical applications of heparin have experienced an exponential growth that will be discussed in detail, with particular emphasis on its antimalarial activity. Some of the most intriguing potential applications of heparin nanomedicines will be exposed, such as those contemplating the delivery of drugs to the mosquito stages of malaria parasites

Poly(propylene imine) dendrimers with histidine-maltose shell as novel type of nanoparticles for synapse and memory protection

Poly(propylene imine) dendrimers have been shown to be promising 3-dimensional polymers for the use in the pharmaceutical and biomedical applications. Our aims of this study were first, to synthesize a novel type of dendrimer with poly(propylene imine) core and maltose-histidine shell (G4HisMal) assessing if maltose-histidine shell can improve the biocompatibility and the ability to cross the blood-brain barrier, and second, to investigate the potential of G4HisMal to protect Alzheimer disease transgenic mice from memory impairment. Our data demonstrate that G4HisMal has significantly improved biocompatibility and ability to cross the blood-brain barrier in vivo. Therefore, we suggest that a maltose-histidine shell can be used to improve biocompatibility and ability to cross the blood-brain barrier of dendrimers. Moreover, G4HisMal demonstrated properties for synapse and memory protection when administered to Alzheimer disease transgenic mice. Therefore, G4HisMal can be considered as a promising drug candidate to prevent Alzheimer disease via synapse protection. © 2019 The Author

Poly(propylene imine) dendrimers with histidine-maltose shell as novel type of nanoparticles for synapse and memory protection

Poly(propylene imine) dendrimers have been shown to be promising 3-dimensional polymers for the use in the pharmaceutical andbiomedical applications. Our aims of this study were first, to synthesize a novel type of dendrimer with poly(propylene imine) core andmaltose-histidine shell (G4HisMal) assessing if maltose-histidine shell can improve the biocompatibility and the ability to cross the blood-brain barrier, and second, to investigate the potential of G4HisMal to protect Alzheimer disease transgenic mice from memory impairment.Our data demonstrate that G4HisMal has significantly improved biocompatibility and ability to cross the blood-brain barrier in vivo.Therefore, we suggest that a maltose-histidine shell can be used to improve biocompatibility and ability to cross the blood-brain barrier ofdendrimers. Moreover, G4HisMal demonstrated properties for synapse and memory protection when administered to Alzheimer diseasetransgenic mice. Therefore, G4HisMal can be considered as a promising drug candidate to prevent Alzheimer disease via synapse protection