Microfluidic 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 microfluidic components. We propose a system design methodology that attempts to apply classical high-level synthesis techniques to the design of digital microfluidic biochips. We focus here on the problem of scheduling bioassay functions under resource constraints. We first develop an optimal scheduling strategy based on integer linear programming. However, because 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 first used to illustrate and evaluate the proposed method. Next, the synthesis approach is applied to a protein assay, which serves as a more complex bioassay application. The proposed synthesis approach is expected to reduce human effort and design cycle time, and it will facilitate the integration of microfluidic components with microelectronic components in next-generation SOCs.

Microfluidic biochips promise to revolutionize biosensing and clinical diagnostics. As more bioassays are executed concurrently on a biochip, system integration and design complexity are expected to increase dramatically. This problem is also identified by the 2003 ITRS document as a major system-level design challenge beyond 2009. We focus here on the automated design of droplet-based microfluidic biochips. We present a synthesis methodology that unifies operation scheduling, resource binding, and module placement for such "digital" biochips. The proposed technique, which is based on parallel recombinative simulated annealing, can also be used after fabrication to bypass defective cells in the microfluidic array. A real-life protein assay is used to evaluate the synthesis methodology.

Abstract-Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, deoxyribonucleic acid (DNA) sequencing, and other laboratory procedures involving molecular biology. In contrast to continuous-flow systems that rely on permanently etched microchannels, micropumps, and microvalves, digital microfluidics offers a scalable system architecture and dynamic reconfigurability; groups of unit cells in a microfluidics array can be reconfigured to change their functionality during the concurrent execution of a set of bioassays. As more bioassays are executed concurrently on a biochip, system integration and design complexity are expected to increase dramatically. This paper presents an overview of an integrated system-level design methodology that attempts to address key issues in the synthesis, testing and reconfiguration of digital microfluidics-based biochips. Different actuation mechanisms for microfluidics-based biochips, and associated design-automation trends and challenges are also discussed. The proposed top-down design-automation approach is expected to relieve biochip users from the burden of manual optimization of bioassays, time-consuming hardware design, and costly testing and maintenance procedures, and it will facilitate the integration of fluidic components with a microelectronic component in next-generation systems-on-chips (SOCs).

Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, DNA sequencing, and other laboratory procedures involving molecular biology. Most microfluidic biochips today are based on the principle of continuous fluid flow and they rely on permanently etched microchannels, micropumps, and microvalves. We focus here on the automated design of “digital” droplet-based microfluidic biochips. In contrast to conventional continuous-flow systems, digital microfluidics offers dynamic reconfigurability; groups of cells in a microfluidics array can be reconfigured to change their functionality during the concurrent execution of a set of bioassays. We present a simulated annealing-based technique for module placement in such biochips. The placement procedure not only addresses chip area, but also considers fault tolerance, which allows a microfluidic module to be relocated elsewhere in the system when a single cell is detected to be faulty. Simulation results are presented for case studies involving the polymerase chain reaction and multiplexed in vitro clinical diagnostics.

We present a concurrent testing methodology for detecting catastrophic faults in droplet-based microfluidic systems and investigate the related problems of test planning and resource optimization. We apply this methodology to a droplet-based microfluidic array that was fabricated and used to perform multiplexed glucose and lactate assays. The test approach interleaves test application with the biomedical assays and prevents resource conflicts. We show that an integer linear programming model can be used to minimize testing time for a given hardware overhead due to droplet dispensing sources and capacitive sensing circuitry. The proposed approach is therefore directed at ensuring high reliability and availability of bio-MEMS and lab-on-a-chip systems, as they are increasingly deployed for safety-critical applications.