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Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and associated with poor prognosis. Unfortunately, most of the patients that achieve clinical complete remission after the treatment will ultimately relapse due to the persistence of minimal residual disease (MRD), that is not measurable using conventional technologies in the clinic. Microfluidics is a potential tool to improve the diagnosis by providing early detection of MRD. Herein, different designs of microfluidic devices were developed to promote lateral and vertical mixing of cells in microchannels to increase the contact area of the cells of interest with the inner surface of the device. Possible interactions between the cells and the surface were studied using fluid simulations. For the isolation of leukemic blasts, a positive selection strategy was used, targeting the cells of interest using a panel of specific biomarkers expressed in immature and aberrant blasts. Finally, once the optimisation was complete, the best conditions were used to process patient samples for downstream analysis and benchmarking, including phenotypic and genetic characterisation. The potential of these microfluidic devices to isolate and detect AML blasts may be exploited for the monitoring of AML patients at different stages of the disease. [ABSTRACT FROM AUTHOR]

Droplet-based microfluidic technology is a powerful tool for generating large numbers of monodispersed nanoliter-sized droplets for ultra-high throughput screening of molecules or single cells. Yet further progress in the development of methods for the real-time detection and measurement of passing droplets is needed for achieving fully automated systems and ultimately scalability. Existing droplet monitoring technologies are either difficult to implement by non-experts or require complex experimentation setups. Moreover, commercially available monitoring equipment is expensive and therefore limited to a few laboratories worldwide. In this work, we validated for the first time an easy-to-use, open-source Bonsai visual programming language to accurately measure in real-time droplets generated in a microfluidic device. With this method, droplets are found and characterized from bright-field images with high processing speed. We used off-the-shelf components to achieve an optical system that allows sensitive image-based, label-free, and cost-effective monitoring. As a test of its use we present the results, in terms of droplet radius, circulation speed and production frequency, of our method and compared its performance with that of the widely-used ImageJ software. Moreover, we show that similar results are obtained regardless of the degree of expertise. Finally, our goal is to provide a robust, simple to integrate, and user-friendly tool for monitoring droplets, capable of helping researchers to get started in the laboratory immediately, even without programming experience, enabling analysis and reporting of droplet data in real-time and closed-loop experiments. [ABSTRACT FROM AUTHOR]