Design Optimization at the Fluid-Level Synthesis for Safe and Low-Cost Droplet-Based Microfluidic Biochips

Abstract: Production of correct bioassay outcome is the foremost objective in digital microfluidic biochips (or DMFBs). In high-frequency DMFBs, continuous actuation of electrodes leads to malfunctioning or even breakdown of the system. The improper functioning of a biochip tends to produce erroneous results. On the other hand, while transporting droplets, the residues may get stuck to electrode walls and cause contamination to other droplets. To ensure proper assay outcome, washing becomes mandatory, whose incorporation may delay the bioassay completion time significantly. Furthermore, each wash droplet possesses a capacity constraint within which the residues can be washed off successfully. Evidently, the design objectives possess a large degree of trade-offs among themselves and must be attacked to prepare an efficient platform. Here, the authors propose a complete fluid-level synthesis considering all the essential goals together instead of dealing with them in isolation. The presented approach effectively handles the trade-off scenarios and provides flexibility to the designer to decide the threshold of the individual optimisation objective leading to the construction of a good-quality solution as a whole. The performance is evaluated over several benchmark bioassays.

Abstract: Digital microfluidic biochips (DMFBs) are attractive instruments for obtaining modern molecular biology and chemical measurements. Due to the increasingly complex measurements carried out on a DMFB, such chips are more prone to failure. To compensate for the shortcomings of the module-based DMFB, this paper proposes a routing-based fault repair method. The routing-based synthesis methodology ensures a much higher chip utilization factor by removing the virtual modules on the chip, as well as removing the extra electrodes needed as guard cells. In this paper, the routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed. By introducing a cost function into the Dijkstra algorithm, the path-planning problem under dynamic obstacles is solved, and the problem of mixed path design is solved by redefining the position and velocity vectors of the particle swarm optimization. The ID-IPSO routing-based fault repair method is applied to a multibody fluid detection experiment. The proposed design method has a stronger optimization ability than the greedy algorithm. The algorithm is applied to , , and fault-free chips. The proposed ID-IPSO routing-based chip design method saves 13.9%, 14.3%, and 14.5% of the experiment completion time compared with the greedy algorithm. Compared with a modular fault repair method based on the genetic algorithm, the ID-IPSO routing-based fault repair method has greater advantages and can save 39.3% of the completion time on average in the completion of complex experiments. When the ratio of faulty electrodes is less than 12% and 23%, the modular and ID-IPSO routing-based fault repair methods, respectively, can guarantee a 100% failure repair rate. The utilization rate of the electrodes is 18% higher than that of the modular method, and the average electrode usage time is 17%. Therefore, the ID-IPSO routing-based fault repair method can accommodate more faulty electrodes for the same fault repair rate; the experiment completion time is shorter, the average number of electrodes is lower, and the security performance is better.

Abstract: Digital microfluidic biochips (DMFBs) are increasingly important and are used for point-of-care, drug discovery, clinical diagnosis, immunoassays, etc. Pin-constrained DMFBs are an important part of digital microfluidic biochips, and they have gained increasing attention from researchers. However, many previous works have focused on the problem of electrode addressing and aimed to minimize the number of control pins in pin-constrained DMFBs. Although the number of control pins can be effectively redistributed through broadcast addressing technology, the chip reliability will be reduced if the signals are shared arbitrarily. Arbitrary signal sharing can lead to a large number of actuations for many idle electrodes, and as a result, a trapping charge or decreasing contact angle problem could occur for some electrodes, reducing the reliability of the chip. To address this problem, the appropriate electrode matching object should be carefully selected, and the influence of these factors on chip reliability should be fully considered. For this purpose, we aimed to fully consider electrode addressing and the reliability of the chip in improving the reliability of DMFBs. This paper proposed a pin addressing method based on a support vector machine (SVM) with the reliability constraint algorithm, which can fully consider the electrode addressing method and the reliability of the chip together. The proposed method achieved an average maximum number of electrode actuations that was 53.8% and 18.2% smaller than those of the baseline algorithm and the graph-based algorithm, respectively. The simulation experiment results showed that the proposed method can efficiently solve reliability problems during the DMFB design process.

Abstract: Digital micro-fluidic biochips (DMFBs) are revolutionizing laboratory procedures for point-of-care clinical diagnostics, environmental monitoring, and protein analysis. Those procedures require high precision of the output for every operation so it need to ensure the chip reliability and the chip lifetime. Because the electrodes on the chip may be reused at different experimental stages, a degraded electrode may be reused for many times. So the lifetime of the chips is closely related to the total actuating time of an electrode. Thus, the electrode total actuating time needs to be considered carefully in an efficient DMFBs design process. This paper proposed an improved whale optimization algorithm (IWOA), which can reduce excessive use of an electrode and reuse electrodes in average manner to optimal the longest lifetime of DMFBs during the design process. Firstly, the position mass of individual whales was improved to solve the problem that the data, calculated by the WOA, cannot be directly used to represent the sequence of operations. Secondly, the inertial weight was added to enhance the local search ability of WOA. The simulation experimental results showed that this algorithm was able to solve lifetime optimization problems. The maximum electrode time used was reduced by 10% to 20%. The performance of efficiency and convergence of algorithm were very good.

Abstract: Digital microfluidic biochips (DMFBs) are increasingly important used for clinical diagnostics drug discovery and point-of-care. Those procedures require high output precision, so the reliability and lifetime of the chips are extremely important. Due to the inherently reconfigurable nature of DMFBs, a degraded electrode may be reused many times. Therefore, the lifetime of the chips is closely related to the total actuation time of an electrode. Thus, the electrode total actuation time needs to be considered carefully in an efficient DMFB design process. This paper proposes an improved whale optimization algorithm (IWOA), which can reduce the excessive use of an electrode and reuse electrodes in an average manner to optimize the longest lifetime of DMFBs. First, the IWOA combined a WOA with a genetic algorithm, and inertial weights were added to enhance the local search ability of the IWOA. Second, the max-min WOA was proposed in the exploration phase. Lastly, the position mass of individual whales was improved to represent the sequence of operations. The simulation experimental results showed that this algorithm was able to solve lifetime optimization problems. The efficiency and convergence performance of the algorithm were very good. The proposed algorithm can achieve maximum improvement in the maximum electrode activation time of 74.6%, 8.2%,15.7% and 7.2% respectively, compared with T-trees algorithm, 3-DDD algorithm, PRSA algorithm and 3D-DDMS algorithm.

Abstract: 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.

Abstract: Recent advances in digital microfluidics have enabled droplet-based biochip devices for DNA sequencing, immunoassays, clinical chemistry, and protein crystallization. Since cross-contamination between droplets of different biomolecules can lead to erroneous outcomes for bioassays, the avoidance of cross-contamination during droplet routing is a key design challenge for biochips. We propose a droplet-routing method that avoids cross-contamination in the optimization of droplet flow paths. The proposed approach targets disjoint droplet routes and synchronizes wash-droplet routing with functional droplet routing, in order to reduce the duration of droplet routing while avoiding the cross-contamination between different droplet routes. In order to avoid cross-contamination between successive routing steps, an optimization technique is used to minimize the number of wash operations that must be used between successive routing steps. Two real-life biochemical applications are used to evaluate the proposed droplet-routing methods.

Abstract: Microfluidics-based biochips are revolutionizing high-throughput sequencing, parallel immunoassays, blood chemistry for clinical diagnostics, and drug discovery. These devices enable the precise control of nanoliter volumes of biochemical samples and reagents. They combine electronics with biology, and they integrate various bioassay operations, such as sample preparation, analysis, separation, and detection. Compared to conventional laboratory procedures, which are cumbersome and expensive, miniaturized biochips offer the advantages of higher sensitivity, lower cost due to smaller sample and reagent volumes, system integration, and less likelihood of human error. This tutorial paper provides an overview of droplet-based ?digital? microfluidic biochips. It describes emerging computer-aided design (CAD) tools for the automated synthesis and optimization of biochips from bioassay protocols. Recent advances in fluidic-operation scheduling, module placement, droplet routing, pin-constrained chip design, and testing are presented. These CAD techniques allow biochip users to concentrate on the development of nanoscale bioassays, leaving chip optimization and implementation details to design-automation tools.

Abstract: Given a directed graph whose arcs have an associated cost, and associated weight, the weight constrained shortest path problem (WCSPP) consists of finding a least-cost path between two specified nodes, such that the total weight along the path is less than a specified value. We will consider the case of the WCSPP defined on a graph without cycles. Even in this case, the problem is NP-hard, unless all weights are equal or all costs are equal, however pseudopolynomial time algorithms are known. The WCSPP applies to a number of real-world problems. Traditionally, dynamic programming approaches were most commonly used, but in recent times other methods have been developed, including exact approaches based on Lagrangean relaxation, and fully polynomial approximation schemes. We will review the area and present a new exact algorithm, based on scaling and rounding of weights.

Abstract: Digital microfluidic biochips have emerged as a popular alternative for laboratory experiments. Pin-count reduction and cross-contamination avoidance are key design considerations for practical applications with different droplets being transported and manipulated on highly integrated biochips. This paper presents the first design automation flow that considers the cross-contamination problems on pin-constrained biochips. The factors that make the problems harder on pin-constrained biochips are explored. To cope with these cross contaminations, this paper proposes: 1) early crossing minimization algorithms during placement, and 2) systematic wash droplet scheduling and routing that require only one extra control pin and zero assay completion time overhead for practical bioassays. Experimental results show the effectiveness and scalability of our algorithms for practical bioassays.