Magnetic Microfluidics with AI-Based Cell Level Quantification of Nanoparticle Delivery

Abstract Targeted therapeutic delivery to sites of nerve injury remains a major challenge in regenerative medicine, where efficient treatment requires maximizing local drug concentration while minimizing off-target effects. Recently, microfluidic platforms have proven to be powerful tools for modeling physiological flow and drug delivery. Here, we used iron oxide nanoparticles conjugated to nerve growth factor (NGF-MNPs) and applied an external magnetic field to defined target regions within a microfluidic device. Using live imaging, we first visualize the flow of fluorescent MNPs within the device to track particle displacement under magnetic stimulation. The resulting shift in particle trajectories, designed to mimic physiological flow conditions, was quantified to assess the influence of the magnetic field on nanoparticle behavior. We next quantified the accumulation of MNP-associated fluorescent puncta at a single-cell resolution utilizing state-of-the-art artificial intelligence and image processing approaches for segmentation, enabling optimization of nanoparticle internalization per cell as a function of external magnetic field application and nanoparticle size. We also demonstrated that PC12 cells exposed to NGF-MNPs within the microfluidic device exhibited efficient growth and differentiation. Finally, our results showed that a strong magnetic field increased MNP internalization by 116% relative to conditions without external magnetic stimulation, highlighting the efficiency of magnetically guided drug delivery. In all, these findings establish a magnetic microfluidic delivery platform approach for guiding therapeutic nanoparticles under physiologically relevant flow conditions. This integrated platform approach provides a quantitative foundation for future neurorepair systems and supports the development of magnetically guided regenerative drug delivery technologies.