Wash optimization for cross-contamination removal in flow-based microfluidic biochips

Recent advances in flow-based microfluidics have enabled the emergence of biochemistry-on-a-chip as a new paradigm in drug discovery and point-of-care disease diagnosis. However, these applications in biochemistry require high precision to avoid erroneous assay outcomes, and therefore are vulnerable to contamination between two fluidic flows with different biochemistries. Moreover, to wash contaminated sites, the buffer solution in flow-based biochips has to be guided along pre-etched channel networks. This constraint makes washing in flow-based microfluidics even harder. In this paper, we propose the first approach for automated wash optimization for contamination removal in flow-based microfluidic biochips. The proposed approach targets the generation of washing pathways to clean all contaminated microchannels with minimum execution time. A path dictionary is first established by pre-searching physically implementable paths in a given chip layout. When wash targets and occupied microchannels are defined, the proposed methods determine an optimized path set with the least washing time by calculating the priorities of wash targets. Two fabricated biochips are used to evaluate the proposed washing method. Compared to an ad hoc baseline method, the proposed approach leads to more efficient washing in all cases.