Design Automation for Error-Tolerant Sample Preparation with Digital Microfluidic Biochips / Dr. Sudip Poddar
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Microfluidic chips are now being increasingly used for fast and cost-effective implementation of biochemical protocols. Sample preparation involves dilution and mixing of fluids in certain ratios, which are needed for most of the protocols. On a digital microfluidic biochip (DMFB), these tasks are usually automated as a sequence of droplet mix-split steps. In the most widely used (1:1) mix-split operation for DMFBs, two equal-volume droplets are mixed followed by a split operation, which, ideally, should produce two daughter-droplets of equal volume (balanced splitting). However, because of uncertain variabilities in fluidic operations, the outcome of droplet-split operations often becomes erroneous, i.e., they may cause unbalanced splitting. As a result, the concentration factor (CF) of each constituent fluid in the mixture may become erroneous during sample preparation. All traditional approaches on error recoverability used checkpointing-based rollback approach, that is, re-execution of certain portions of the protocol starting from the previous checkpoint. Most of them suffer from significant overhead in terms of assay-completion time, reactant-cost, and uncertainties in termination due to randomly occurring split-errors. In this work, we propose alternative and low-cost solution strategies for reliable sample preparation on a DMFB, which are fast as well as deterministic in nature. More precisely, we consider imprecise droplet mix-split operations and present novel roll-forward techniques where the erroneous droplets, thus produced, are used in the error-recovery process, instead of being discarded or remixed. All erroneous droplets participate in the dilution process
and they mutually cancel or reduce the concentration-error when the target droplet is reached. Simulation experiments on various test-cases demonstrate the effectiveness of the proposed method.