UCLA

Decentralized diagnostics, pivotal in shifting healthcare paradigms, play a crucial role in enabling accessible and frequent health monitoring outside traditional central laboratory confines. This approach, by facilitating early detection of health issues, enhances treatment outcomes and significantly reduces healthcare costs. Key requirements for effective decentralized diagnostics include a small footprint, automated liquid handling, high multiplexity, and minimal reagent and sample usage.We present an innovative ferrobotic platform to address the challenges. This system comprises a network of individually addressable robots, each performing designated micro-/nano-fluidic manipulation tasks in collaboration toward a unified objective. The platform leverages addressable electromagnetic actuation of mobile magnets for fluidic operations, manipulating aqueous droplets containing biocompatible magnetic nanoparticles. The robustness and individual addressability of the ferrobots underpin their capability for efficient cross-collaborative logistics. This, coupled with the system's reconfigurability, allows the integration of passive/active functional components for versatile lab-equivalent operations. The ferrobotic platform we developed marks a substantial advancement in medical diagnostics. It is adept at streamlining and automating a wide array of assays. This platform significantly extends beyond our previous viral diagnostics, transitioning from simple nucleic acid amplification tests with binary readouts to comprehensive, multi-reagent and multi-step assay workflows. It incorporates advanced multiplexing strategies, enhancing diagnostic spectrum and adaptability. This innovation represents a pivotal step in evolving point-of-care diagnostic capabilities. In biomedical applications, the ferrobotic platform excels, particularly in quantifying active matrix metallopeptidases in human plasma, a key biomarker for cancer and inflammation. This cross-collaborative robotic function facilitates fully automated assays. Its efficacy extends to detecting SARS-CoV-2 in clinical samples, with results matching traditional methods. Notably, the platform employs a square matrix pooled testing algorithm for efficient viral testing, potentially reducing reagent costs by up to 300-fold, depending on viral prevalence. Additionally, in neonatal intensive care unit settings, it significantly reduces blood draw volumes and sample costs, demonstrating its utility in sensitive medical environments. This versatility underscores the platform's significant impact in advancing biomedical diagnostics. The concluding section also lists the challenges to enhance the platform for practical application and anticipates the potential fields beyond diagnostics where the ferrobotic platform could be impactful.