“Our work seeks to adapt and apply additive technologies to create thin and flexible polymer films containing the drug and capable of its release. The main advantage of this approach is that it allows making films of complex geometry layer by layer. Just as a tailor taking measurements from a model and cutting out flat pieces of complex shape from a cloth flap, which then turn into clothes and perfectly fit, we create polymer coatings of a certain shape using additive technologies, which are ideally suited for certain areas of a prosthesis or other medical device and may contain various medicinal substances. As almost any drugs or their combinations can be included in the film, this technology can be used in personalized medicine for the treatment and prevention of postoperative complications, and the locality of drug release significantly reduces the risk of systemic side effects,” the scientists explained.
The team shared that they were very excited to learn about the results: “When discussing new ideas, we received an email. Since submitting the application, we have been aware that the award is prestigious and very competitive, so we express our gratitude to its founders and the board of experts for choosing our research.”
Dmitry submitted a paper, which combined a large cycle of research — about 20 articles — carried out in the Photonics Center’s Laboratory of Nanomaterials at Skoltech: “A family of carbon nanomaterials covers a wide range of different properties, and for each application we need to optimize them for a specific case. For more than 20 years, scientists around the world have been trying to solve this task, and we have made our own contribution. Our strategy was to divide all these complex processes into simpler ones and work with them separately. For example, we were able to identify the stages of catalyst activation and deactivation during production of nanotubes. Similarly, we made a reactor conveyor: instead of one system, we presented a chain of two or three reactors. At each stage, additional modification takes place in order to enrich carbon nanotubes with a semiconductor fraction or, conversely, to make nanotubes with a more metallic conductivity. We used all the accumulated experience to create a smart reactor based on our experience and machine learning. Thus, the separation of tandem systems (or the conveyor approach) and machine learning allowed us to create materials with high performance characteristics. The findings establish a strong foundation for the creation of various devices that are based on carbon nanomaterials.”