Search

Novel ways to track and verify items of a high value or security is an ever-present need. Taggants made from deoxyribonucleic acid (DNA) have several advantageous properties, such as high information density and robust synthesis; however, existing methods require laboratory techniques to verify, limiting applications. Here, we leverage DNA nanotechnology to create DNA taggants that can be validated in the field in seconds to minutes with a simple equipment. The system is driven by toehold-mediated strand-displacement reactions where matching oligonucleotide sequences drive the generation of a fluorescent signal through the potential energy of base pairing. By pooling different "input" oligonucleotide sequences in a taggant and spatially separating "reporter" oligonucleotide sequences on a paper ticket, unique, sequence-driven patterns emerge for different taggant formulations. Algorithmically generated oligonucleotide sequences show no crosstalk and ink-embedded taggants maintain activity for at least 99 days at 60 °C (equivalent to nearly 2 years at room temperature). The resulting fluorescent signals can be analyzed by the eye or a smartphone when paired with a UV flashlight and filtered glasses.

The authentication of the packaging represents an important step in the investigation of suspected counterfeits of pharmaceutical products. The visual comparison with a retained sample is the first step to detect a counterfeited packaging. Due to the improvement of technologies like printing, the emergence of counterfeits with a better appearance can be observed. Moreover counterfeits are nowadays often a combination of fake and genuine parts that have been manipulated. Authenticating each part of the product is important in the frame of the investigation to understand how the counterfeiters proceed, and which prevention measures should be taken. Lab instruments like spectrometers can help confirm counterfeits of packaging for packaging components on which visually, no difference with a reference would be observed. In this study several analytical tools were evaluated to help support the authentication of the primary and secondary packaging of one medicinal product as an example using seven reference materials and five counterfeits. In some cases, visual examination of the packaging already enabled to detect counterfeits of the studied features. Also the boxes, leaflets and vials have been analysed with Infrared (IR) spectroscopy, Raman microspectroscopy, X-ray fluorescence (XRF) spectroscopy, Scanning Electron Microscopy (SEM) and microcomputed tomography (microCT). According to the obtained results, IR and XRF could support the visual examination of the different packaging components. Despite the small amount of counterfeits, relevant links could also be detected between the studied cases based on the packaging characteristics.

The work presented in this paper details the design and performance characteristics of a new hyperspectral visible imaging technique. Rather than using optical filters or a dispersing element, this design implements Fourier transform spectroscopy to achieve spectral discrimination. One potentially powerful application of this new technology is the nondestructive analysis and authentication of written and printed documents. Document samples were prepared using red, blue, and black inks. The samples were later altered using a different ink of the same color. While the alterations are undetectable to the naked eye, the alterations involving the blue and black inks were easily detected when the spectrally resolved images were viewed. Analysis of the sample using the red inks was unsuccessful. A 2004 series $20 bill was imaged to demonstrate the application to document authentication. The results argue that counterfeit detection and quality control during printing are plausible applications of Fourier transform hyperspectral visible imaging. All of the images were subjected to fuzzy c-means cluster analysis in an effort to objectively analyze and automate image analysis. Our results show that cluster analysis can distinguish image features that have remarkably similar visible transmission spectra.