| Summary: |
The main goal of the project MyTag, is to validate a new approach for the real time detection of micro contaminants in complex scenarios, from water quality control, industrial
process optimization, to fast medical diagnostic. A new universal molecular detection platform is envisage using a combination of scattering analysis, assisted with real time modeling
and artificial intelligence (AI) coupled with Molecular Imprinted Tags (MIP Tags), that can be implemented with relatively simple and robust optoelectronic instrumentation. Our
motivation lays in the fact that the ubiquity and wide diversity of damaging substances that threaten our health and the environment, is in contrast with the poor coverage of the
available monitoring tools, which most of the times rely on sample collection, chemical extraction, and laboratory analysis. Although remarkable progresses are underway towards
the development of new sensing technologies, such as photonics and electrochemistry, very few solutions provide the market with the needed technologies [1-5]. The solution
proposed by MyTag builds on very recent results of INESC TEC team which demonstrated the application of AI methods, supported by physical modeling, to the analysis of the
backscattering patterns, enabled the identification of different kinds of cells, extracellular vesicles and other micro and NPs at very low concentrations and with high accuracy. |
| Results: |
The main goal of the project MyTag, is to validate a new approach for the real time detection of micro contaminants in complex scenarios, from water quality control, industrial
process optimization, to fast medical diagnostic. A new universal molecular detection platform is envisage using a combination of scattering analysis, assisted with real time modeling
and artificial intelligence (AI) coupled with Molecular Imprinted Tags (MIP Tags), that can be implemented with relatively simple and robust optoelectronic instrumentation. Our
motivation lays in the fact that the ubiquity and wide diversity of damaging substances that threaten our health and the environment, is in contrast with the poor coverage of the
available monitoring tools, which most of the times rely on sample collection, chemical extraction, and laboratory analysis. Although remarkable progresses are underway towards
the development of new sensing technologies, such as photonics and electrochemistry, very few solutions provide the market with the needed technologies [1-5]. The solution
proposed by MyTag builds on very recent results of INESC TEC team which demonstrated the application of AI methods, supported by physical modeling, to the analysis of the
backscattering patterns, enabled the identification of different kinds of cells, extracellular vesicles and other micro and NPs at very low concentrations and with high accuracy. |