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The medical art of recognizing disease by its odor is known at least since Hippocrates wrote in 400 BC in his Book of Prognostics[1] that “ smells which are somewhat putrid and fetid, are bad...”. Mimicking this approach by nanoscience methods, we report the design and clinical validation of a nanomechanical cantilever array based olfactory system coupled with an artificial neural network for fast detection of disease-specific breath patterns. Arrays of silicon cantilevers produced by microfabrication were differentially surface functionalized with polymers that exhibit different swelling properties upon exposure to various vapor mixtures. The resulting complex, nonlinear bending pattern of the cantilever array was analyzed by pattern recognition techniques and allowed in cross-validation experiments the noninvasive, fast, label-free, sensitive and specific detection of disease states in clinical samples from normal individual and patients with kidney failure and with respiratory failure in an intensive care unit setting. This demonstrates the applicability of nanomechanics-based systems for noninvasive medical diagnosis. Hunziker P. Eur J Nanomed 2008 1:44-47 understood. We chose to apply a similar approach for disease detection by utilizing an array of cantilevers of which each is functionalized in a different way, although this functionalization is not specific for certain ligand/receptor pairs. Thus, disease classification is not based on the response of a single sensor that is highly specific for a particular marker of a specific disease as done in conventional biochemical testing. Classification is done instead through pattern recognition/classification techniques that take the overall response pattern of the cantilevers induced by the interaction of the complex mixture of volatile gas into account. Both, linear discriminant analysis, and a nonlinear approach based on an artificial neural network were applied, because nonlinear behaviour of the system was expected in advance and is evident from the sensor data, with nonlinear analysis proving to be advantageous. methods The measurement chamber consisted of arrays of 8 cantilevers with a length of 500μm, a width of 100μm and a thickness of 1μm produced from silicon Clinical studies

Clinical studies: Diagnosing disease by nanomechanical olfactory sensors – system design and clinical validation