Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets

The density, porosity, breaking force, viscoelastic properties, and the presence or absence of any structural defects or irregularities are important physical-mechanical quality attributes of popular solid dosage forms like tablets. The irregularities associated with these attributes may influence the drug product functionality. Thus, an accurate and efficient characterization of these properties is critical for successful development and manufacturing of a robust tablets. These properties are mainly analyzed and monitored with traditional pharmacopeial and non-pharmacopeial methods. Such methods are associated with several challenges such as lack of spatial resolution, efficiency, or sample-sparing attributes. Recent advances in technology, design, instrumentation, and software have led to the emergence of newer techniques for non-invasive characterization of physical-mechanical properties of tablets. These techniques include near infrared spectroscopy, Raman spectroscopy, X-ray microtomography, nuclear magnetic resonance (NMR) imaging, terahertz pulsed imaging, laser-induced breakdown spectroscopy, and various acoustic- and thermal-based techniques. Such state-of-the-art techniques are currently applied at various stages of development and manufacturing of tablets at industrial scale. Each technique has specific advantages or challenges with respect to operational efficiency and cost, compared to traditional analytical methods. Currently, most of these techniques are used as secondary analytical tools to support the traditional methods in characterizing or monitoring tablet quality attributes. Therefore, further development in the instrumentation and software, and studies on the applications are necessary for their adoption in routine analysis and monitoring of tablet physical-mechanical properties

Design of highly stabilized nanocomposite inks based on biodegradable polymer-matrix and gold nanoparticles for Inkjet Printing

Nowadays there is a worldwide growing interest in the Inkjet Printing technology owing to its potentially high levels of geometrical complexity, personalization and resolution. There is also social concern about usage, disposal and accumulation of plastic materials. In this work, it is shown that sugar-based biodegradable polyurethane polymers exhibit outstanding properties as polymer-matrix for gold nanoparticles composites. These materials could reach exceptional stabilization levels, and demonstrated potential as novel robust inks for Inkjet based Printing. Furthermore, a physical comparison among different polymers is discussed based on stability and printability experiments to search for the best ink candidate. The University of Seville logo was printed by employing those inks, and the presence of gold was confirmed by ToF-SIMS. This approach has the potential to open new routes and applications for fabrication of enhanced biomedical nanometallic-sensors using stabilized AuNP.Spanish Ministerio de Economía y Competitividad MINECO, (Grants Nos. CTQ2016- 78703-P and MAT2016-78703-P)Junta de Andalucía (Consolidation Grant for Research Group FQM135 and 2017/FQM-386, P-2018/809)University of Seville (V y VI Plan Propio PP2016-5937

An examination of the sequence of intersecting lines using attenuated total reflectance-Fourier transform infrared spectral imaging

In this study, the potential of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectral imaging as a technique to determine the sequence of line crossings was examined. The technique was successful in determining the sequence of heterogeneous line intersections produced using ballpoint pens and laser printers. By imaging at characteristic frequencies, it was possible to form spectral images showing the spatial distribution of the materials. By examining the spectral images from the inks, it was possible to determine whether the ink was above or below the toner. In blind testing, ATR-FTIR spectral imaging results were directly compared to those obtained by eight experienced forensic document examiners using methods regularly employed in casework. ATR-FTIR spectral imaging was shown to achieve a 100% success rate in the blind tests, whereas some incorrect sequence determinations were made by the forensic document examiners when using traditional techniques. The technique was unable to image ink-jet printing, gel pens, roller ball pens, and felt-tip pens, and was also unable to determine the sequence of intersecting ballpoint pen lines. © 2008 American Academy of Forensic Sciences

North Tyneside Printing Sector Training Needs Analysis

The printing sector in this region has a proportionately low level of employment compared to the UK as a whole. North Tyneside provides the location for some 36 print-based firms, which account for only 11% of Tyne & Wear’s total print employment. However, this survey indicates that the official data significantly under-estimates the employment size of the sector in North Tyneside

DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks

This paper proposes DeepMarks, a novel end-to-end framework for systematic fingerprinting in the context of Deep Learning (DL). Remarkable progress has been made in the area of deep learning. Sharing the trained DL models has become a trend that is ubiquitous in various fields ranging from biomedical diagnosis to stock prediction. As the availability and popularity of pre-trained models are increasing, it is critical to protect the Intellectual Property (IP) of the model owner. DeepMarks introduces the first fingerprinting methodology that enables the model owner to embed unique fingerprints within the parameters (weights) of her model and later identify undesired usages of her distributed models. The proposed framework embeds the fingerprints in the Probability Density Function (pdf) of trainable weights by leveraging the extra capacity available in contemporary DL models. DeepMarks is robust against fingerprints collusion as well as network transformation attacks, including model compression and model fine-tuning. Extensive proof-of-concept evaluations on MNIST and CIFAR10 datasets, as well as a wide variety of deep neural networks architectures such as Wide Residual Networks (WRNs) and Convolutional Neural Networks (CNNs), corroborate the effectiveness and robustness of DeepMarks framework

Flow-Based Single Cell Deposition for High-Throughput Screening of Protein Libraries

The identification and engineering of proteins having refined or novel characteristics is an important area of research in many scientific fields. Protein modelling has enabled the rational design of unique proteins, but high-throughput screening of large libraries is still required to identify proteins with potentially valuable properties. Here we report on the development and evaluation of a novel fluorescent activated cell sorting based screening platform. Single bacterial cells, expressing a protein library to be screened, are electronically sorted and deposited onto plates containing solid nutrient growth media in a dense matrix format of between 44 and 195 colonies/cm2. We show that this matrix format is readily applicable to machine interrogation (<30 seconds per plate) and subsequent bioinformatic analysis (~60 seconds per plate) thus enabling the high-throughput screening of the protein library. We evaluate this platform and show that bacteria containing a bioluminescent protein can be spectrally analysed using an optical imager, and a rare clone (0.5% population) can successfully be identified, picked and further characterised. To further enhance this screening platform, we have developed a prototype electronic sort stream multiplexer, that when integrated into a commercial flow cytometric sorter, increases the rate of colony deposition by 89.2% to 24 colonies per second. We believe that the screening platform described here is potentially the foundation of a new generation of high-throughput screening technologies for proteins