Next-Gen NMR Prediction and Analysis: A Cutting-Edge Tool for High-Precision Structure Identification

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The proposal aims to advance diagnostic technology by enhancing Nuclear Magnetic Resonance (NMR) as a tool for personalized medicine. Current NMR techniques face limitations in sensitivity, resolution, and uncertainty quantification, particularly in analyzing complex biological mixtures. These challenges hinder its potential to deliver the precise, non-invasive diagnostics required in personalized healthcare. Our solution is an advanced NMR software that integrates quantum-chemical calculations with empirical data to significantly improve NMR's accuracy and reliability. Current methods fall short in accuracy when dealing with complex or novel molecular structures. Our tool addresses these limitations by providing accurate conformer sampling and error propagation techniques to quantify uncertainties in peak assignments and chemical shift variations, which are crucial for high-precision analysis. Additionally, it aims to enable low-field NMR devices as a viable option for advanced diagnostics, particularly in cost-sensitive sectors such as pharmaceuticals, biotechnology, and environmental science. The software automates many aspects of NMR analysis, reducing time and effort for researchers while improving accuracy, enabling wider adoption and faster results. This innovation is particularly relevant to the EIC Transition program’s focus on bringing deep-tech innovations from lab to market. The software has the potential to revolutionize fields like drug discovery, personalized medicine, and environmental monitoring, opening new markets for point-of-care diagnostics and expanding the use of low-field NMR in industries previously restricted by high costs. Early interest from key players, including Merck and the University Medical Center Freiburg, supports the commercialization potential.