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Microfluidics-based biochips offer a promising platform for massively parallel DNA analysis, automated drug discovery, and real-time biomolecular recognition. Current techniques for full-custom design of droplet-based "digital" biochips do not scale well for concurrent assays and for next-generation system-on-chip (SOC) designs that are expected to include fluidic components. We propose a system design methodology that attempts to apply classical architectural-level synthesis techniques to the design of digital microfluidics-based biochips. We first develop an optimal scheduling strategy based on integer linear programming. Since the scheduling problem is NP-complete, we also develop two heuristic techniques that scale well for large problem instances. A clinical diagnostic procedure, namely multiplexed in-vitro diagnostics on human physiological fluids, is used to evaluate the proposed method.