Micro-electrode-dot-array Biochips Research Articles

Harnessing the advances of MEDA to optimize multi-PUF for enhancing IP security of biochips

Digital microfluidic biochips (DMFBs) have a significant stride in the applications of medicine and the biochemistry in recent years. DMFBs based on micro-electrode-dot-array (MEDA) architecture, as the next-generation DMFBs, aim to overcome drawbacks of conventional DMFBs, such as droplet size restriction, low accuracy, and poor sensing ability. Since the potential market value of MEDA biochips is vast, it is of paramount importance to explore approaches to protect the intellectual property (IP) of MEDA biochips during the development process. In this paper, an IP authentication strategy based on the multi-PUF applied to MEDA biochips is presented, called bioMPUF, consisting of Delay PUF, Split PUF and Countermeasure. The bioMPUF strategy is designed to enhance the non-linearity between challenges and responses of PUFs, making the challenge–response pairs (CRPs) on the MEDA biochips are difficult to be anticipated, thus thwarting IP piracy attacks. Moreover, based on the easy degradation of MEDA biochip electrodes, a countermeasure is proposed to destroy the availability of piracy chips. Experimental results demonstrate the feasibility of the proposed bioMPUF strategy against the brute force attack and modeling attack.

Enhanced Built-In Self-Diagnosis and Self-Repair Techniques for Daisy-Chain Design in MEDA Digital Microfluidic Biochips

Digital microfluidic biochips have emerged as a promising alternative for various laboratory procedures in biochemistry such as drug discovery and DNA sequencing. A recent generation of digital biochips uses a micro-electrode-dotarray (MEDA) architecture, which provides finer controllability of droplets and seamlessly integrates microelectronics and microfluidics. To simplify the wiring design of such biochips, all microelectrodes and their control registers are daisy-chained together. Therefore, the ability to both identify faults in the chain and tolerate them is required in MEDA biochips. In this study, a new daisy-chain design approach is proposed, integrating a built-in self-repair scheme that can automatically detect faults and correct them. Moreover, an efficient test generation method that requires only a small number of test vectors is proposed to achieve 100% fault coverage without degrading the electrodes. The proposed self-repair scheme can be used in both offline and online modes. Experimental results show that detection and repair can be carried out for various types of faults that can occur in daisy chains.

Multi-Target Fluid Mixing in MEDA Biochips: Theory and an Attempt towards Waste Minimization

Sample preparation is an inherent procedure of many biochemical applications, and digital microfluidic biochips (DMBs) proved to be very effective in performing such a procedure. In a single mixing step, conventional DMBs can mix two droplets in 1:1 ratio only. Due to this limitation, DMBs suffer from heavy fluid wastage and often require a lot of mixing steps. However, the next-generation DMBs, i.e., micro-electrode-dot-array (MEDA) biochips can realize multiple mixing ratios, which in general helps in minimizing the number of mixing operations. In this paper, we present a heuristic-based sample preparation algorithm, specifically a mixing algorithm called Division by Factor Method for MEDA that exploits the mixing models of MEDA biochips. We propose another mixing algorithm for MEDA biochips called Single Target Waste Minimization ( STWM ), which minimizes the wastage of fluids and determines an efficient mixing graph. We also propose an advanced methodology for multiple target reagent mixing problems called Multi-Target Waste Minimization ( MTWM ), which determines efficient mixing graphs for different target ratios by maximizing the sharing of fluids and minimizing the fluid wastage. Simulation results suggest that the proposed STWM and MTWM methods outperform the state-of-the-art methods in terms of minimizing the amount of fluid wastage, reducing the total usage of reagent fluids, and minimizing the number of mixing operations.

Deep Reinforcement Learning-Based Approach for Efficient and Reliable Droplet Routing on MEDA Biochips

The micro-electrode-dot-array (MEDA) architecture provides precise droplet control and real-time sensing in digital microfluidic biochips. Previous work has shown that trapped charge under microelectrodes (MCs) leads to droplets being stuck and failures in fluidic operations. A recent approach utilizes real-time sensing of MC health status, and attempts to avoid degraded electrodes during droplet routing. However, the problem with this solution is that the computational complexity is unacceptable for MEDA biochips of realistic size. Consequently, in this work, we introduce a deep reinforcement learning (DRL)-based approach to bypass degraded electrodes and enhance the reliability of routing. The DRL model utilizes the information of health sensing in real time to proactively reduce the likelihood of charge trapping and avoid using degraded MCs. Simulation results show that our approach provides effective routing strategies for COVID-19 testing protocols. We also validate our DRL-based approach using fabricated prototype biochips. Experimental results show that the developed DRL model completed the routing tasks using a fewer number of clock cycles and shorter total execution time, compared with a baseline routing method. Moreover, our DRL-based approach provides reliable routing strategies even in the presence of degraded electrodes. Our experimental results show that the proposed DRL-based routing is robust to occurrences of electrode faults, as well as increases the lifetime and usability of microfluidic biochips compared to existing strategies.

Formal Synthesis of Adaptive Droplet Routing for MEDA Biochips

A digital microfluidic biochip (DMFB) enables the miniaturization of immunoassays, point-of-care clinical diagnostics, and DNA sequencing. A recent generation of DMFBs uses a microelectrode-dot-array (MEDA) architecture, which provides fine-grained control of droplets and real-time droplet sensing using CMOS technology. However, microelectrodes in a MEDA biochip can degrade due to charge trapping when they are repeatedly charged and discharged during bioassay execution; such degradation leads to the failure of microelectrodes and erroneous bioassay outcomes. To address this problem, we first introduce a new microelectrode-cell design such that we can obtain the health status of all the microelectrodes in a MEDA biochip by employing the inherent sensing mechanism. Next, we present a stochastic game-based model for droplet manipulation, and a formal synthesis method for droplet routing that can dynamically change droplet transportation routes. This adaptation is based on the real-time health information obtained from microelectrodes. Comprehensive simulation results for four real-life bioassays show that our method increases the likelihood of successful bioassay completion with negligible impact on time-to-results.

Efficient Regulation of Synthetic Biocircuits Using Droplet-Aliquot Operations on MEDA Biochips

Microfluidic platforms have recently emerged as an invaluable component for studying synthetic biology as they are capable of emulating complex molecular networks of biological pathways (biocircuits) on a chip. A special type of biochemical assays, known as biocircuit-regulatory scanning (BRS) assays, is employed to regulate gene expression, enabling comprehensive exploration of related biocircuit parameters. Prior work has provided high-level design methodologies for implementing BRS; however, most of these methods are abstract and cannot be used in practice as they overlook the dynamics of interactions between the samples and the biochip. In this article, we address this limitation by providing a comprehensive framework that implements BRS assays. The proposed framework, named BioScan, includes: 1) a statistical method that selects suitable volumetric ratios of biochemicals used to execute a BRS assay; 2) a high-level synthesis method that generates the specifications of the target BRS assay; 3) a translation technique enabling implementation of BRS on a microelectrode-dot array (MEDA) biochip; and 4) a Dirichlet-regressor that constructs the parameter space of the associated biocircuit. Simulation results show that the proposed framework can efficiently perform parameter-space exploration (PSE) while significantly reducing completion time and reagent cost.

Minimization of MEDA Biochip-Size in Droplet Routing

With the increasing demand for fast, accurate, and reliable biological sensor systems, miniaturized systems have been aimed at droplet-based sensor systems and have been promising. A micro-electrode dot array (MEDA) biochip, which is one kind of the miniaturized systems for biochemical protocols such as dispensing, dilutions, mixing, and so on, has become widespread due to enabling dynamical control of the droplets in microfluidic manipulations. In MEDA biochips, the electrowetting-on-dielectric (EWOD) technique stands out since it can actuate droplets with nano/picoliter volumes. Microelectrode cells on MEDA actuate multiple droplets simultaneously to route locations for the purpose of the biochemical operations. Taking advantage of the feature, droplets are often routed in parallel to achieve high-throughput outcomes. Regarding parallel manipulation of multiple droplets, however, the droplets are known to be initially placed at a distant position to avoid undesirable mixing. The droplets thus result in traveling a long way for a manipulation, and the required biochip size for routing is also enlarged. This paper proposes a routing method for droplets to reduce the biochip size on a MEDA biochip with the allowance of splitting during routing operations. We mathematically derive the routing problem, and the experiments demonstrate that our proposal can significantly reduce the biochip size by 70.8% on average, compared to the state-of-the-art method.

Shape-Dependent Velocity Based Droplet Routing on MEDA Biochips

Digital microfluidic biochip (DMFB) has attracted attention in the biochemical and medical industries. In particular, a microelectrode dot array (MEDA) biochip, which is composed of a two-dimensional microelectrode array, enables to realize fine-grained manipulation such as dilution, mixing, sensing, and so on in real-time. Unlike existing DMFB biochips, a MEDA architecture allows microelectrodes to control a certain volume of droplet in a fine-grained manner and can vary droplet volume and shape in such a way that it efficiently conducts synthesis and manipulation of droplets. There have been many works in order to improve the efficiency of synthesis of MEDA biochips; however, the synthesis, especially droplet routing, has never considered the shape-dependent velocity of droplets. In this paper, we propose the droplet routing techniques for MEDA biochips with shape-dependent velocity of droplets. The proposed techniques take the advantage of variant velocities of droplets dependent on the shapes and aim to reduce the overall routing time of a droplet from a source to a destination. Simulation results confirm that the proposed techniques can shorten the routing time by 80% compared to the state-of-the-art techniques.

Mixing Models as Integer Factorization: A Key to Sample Preparation With Microfluidic Biochips

Microfluidic biochips have recently emerged with significant promise and versatility in automating a variety of biochemical protocols on a tiny chip. Sample preparation, which involves the mixing of fluids with a specified target ratio in the minuscule scale, is an essential component of these protocols. Algorithms that optimize on-chip sample-preparation cost and time are closely intertwined with the underlying mixing model, mixing sequence, and fluidic architecture. Although numerous mixing models have been studied in the literature, their impact on the dynamics of mixing steps is hitherto not fully understood. In this article, we show that various mixing models can be envisaged in the light of prime factorization of integers thus establishing a connection among mixing algorithms, chip architectures, and performance. This insight has led to the development of the proposed factorization-based dilution algorithm ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FacDA</i> ) considering a generalized mixing model suitable for micro-electrode-dot-array (MEDA) biochips. It further leads to target volume oriented dilution algorithm ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TVODA</i> ) to cater to user’s demand for an output with a given volume. We formulate the optimization problem on the fabric of the satisfiability modulo theory (SMT) while determining mixing sequences. Simulation results on a large number of test-cases reveal that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FacDA</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TVODA</i> outperform the state-of-the-art dilution algorithms for MEDA biochips with respect to reactant cost, mixing time, and waste production.

Enhancing the Reliability of MEDA Biochips Using IJTAG and Wear Leveling

A digital microfluidic biochip (DMFB) enables the miniaturization of immunoassays, point-of-care clinical diagnostics, DNA sequencing, and other laboratory procedures in biochemistry. A recent generation of biochips uses a micro-electrode-dot-array (MEDA) architecture, which provides fine-grained control of droplets and seamlessly integrates microelectronics and microfluidics using CMOS technology and a TSMC fabrication process. To ensure that bioassays are carried out on MEDA biochips efficiently, high-level synthesis algorithms have recently been proposed. However, as in the case of conventional DMFBs, microelectrodes are likely to fail when they are heavily utilized, and previous methods fail to consider reliability issues. In this article, we first present a new microelectrode cell (MC) design such that the droplet-sensing operation can be enabled/disabled for individual MCs. Next, “partial update” and “partial sensing” operations are presented based on an IEEE Std. 1687 IJTAG network design. Finally, wear-leveling synthesis method is proposed to ensure uniform utilization of MCs on MEDA. A comprehensive set of simulation results demonstrate the effectiveness of the proposed hardware design and design automation methods.

Extending the Lifetime of MEDA Biochips by Selective Sensing on Microelectrodes

A digital microfluidic biochip (DMFB) enables miniaturization of immunoassays, point-of-care clinical diagnostics, and DNA sequencing. A recent generation of DMFBs uses a micro-electrode-dot-array (MEDA) architecture, which provides fine-grained control of droplets and real-time droplet sensing using the CMOS technology. However, microelectrodes in a MEDA biochip degrade when they are charged and discharged frequently during bioassay execution. In this article, we first make the key observation that the droplet-sensing operations contribute up to 94% of all microelectrode actuation in MEDA. Consequently, to reduce the number of droplet-sensing operations, we present a new microelectrode cell (MC) design as well as a selective-sensing method such that only a small fraction of microelectrodes perform droplet sensing during bioassay execution. The selection of microelectrodes that need to perform the droplet sensing is based on an analysis of experimental data. A comprehensive set of simulation results show that the total number of droplet-sensing operations is reduced to only 0.7%, which prolongs the lifespan of a MEDA biochip by 11× without any impact on bioassay time-to-response.

Programmable Daisychaining of Microelectrodes to Secure Bioassay IP in MEDA Biochips

As digital microfluidic biochips (DMFBs) make the transition to the marketplace for commercial exploitation, security and intellectual property (IP) protection are emerging as important design considerations. Recent studies have shown that DMFBs are vulnerable to reverse engineering aimed at stealing biomolecular protocols (IP theft). The IP piracy of proprietary protocols may lead to significant losses for pharmaceutical and biotech companies. The microelectrode dot array (MEDA) is a next-generation DMFB platform that supports real-time sensing of droplets and has the added advantage of important security protection. However, real-time sensing offers opportunities to an attacker to steal the biochemical IP. We show that the daisychaining of microelectrodes and the use of one-time programmability in MEDA biochips provides effective bitstream scrambling of biochemical protocols. To examine the strength of this solution, we develop a Satisfiability (SAT)-based attack that can unscramble the bitstreams through repeated observations of bioassays executed on the MEDA platform. Based on insights gained from the SAT attack, we propose an advanced defense against IP theft. Simulation results using real-life biomolecular protocols confirm that while the SAT attack is effective for simple instances, our advanced defense can thwart it for realistic MEDA biochips and real-life protocols.

IJTAG-Based Fault Recovery and Robust Microelectrode-Cell Design for MEDA Biochips

A digital microfluidic biochip (DMFB) is an attractive platform for immunoassays, point-of-care clinical diagnostics, DNA sequencing, and other laboratory procedures in biochemistry. A recent generation of biochips uses a micro-electrode-dot-array (MEDA) architecture, which provides fine-grained controllability of droplets and seamlessly integrates microelectronics and microfluidics using CMOS technology. In order to ensure robust fluidic operations and high confidence in the outcome of biochemical experiments, chip testing, fault diagnosis, and fault recovery are critical for MEDA biochips. In this article, we present an effective fault-recovery solution based on the homogeneous structure of MEDA. Since the microelectrode cells (MCs) in an MEDA biochip are identical, we add multiplexers for reconfigurability, whereby an MC with faulty components can use the hardware resources in a neighboring MC. In addition, we use the IEEE 1687 (also known as IJTAG) network to reduce the number of control signals needed for the multiplexers, and to provide flexible subscan chain access for the fault-recovery control flow. A comprehensive set of simulation results demonstrates the effectiveness of the proposed fault-recovery solution for MEDA biochips.

Secure Assay Execution on MEDA Biochips to Thwart Attacks Using Real-Time Sensing

Digital microfluidic biochips (DMFBs) have emerged as a promising platform for DNA sequencing, clinical chemistry, and point-of-care diagnostics. Recent research has shown that DMFBs are susceptible to various types of malicious attacks. Defenses proposed thus far only offer probabilistic guarantees of security due to the limitation of on-chip sensor resources. A micro-electrode-dot-array (MEDA) biochip is a next-generation DMFB that enables the real-time sensing of on-chip droplet locations, which are captured in the form of a droplet-location map. We propose a security mechanism that validates assay execution by reconstructing the sequencing graph (i.e., the assay specification) from the droplet-location maps and comparing it against the golden sequencing graph. We prove that there is a unique (one-to-one) mapping from the set of droplet-location maps (over the duration of the assay) to the set of possible sequencing graphs. Any deviation in the droplet-location maps due to an attack is detected by this countermeasure because the resulting derived sequencing graph is not isomorphic to the original sequencing graph. We highlight the strength of the security mechanism by simulating attacks on real-life bioassays. We also address the concern that the proposed mechanism may raise false alarms when some fluidic operations are executed on MEDA biochips. To avoid such false alarms, we propose an enhanced sensing technique that provides fine-grained sensing for the security mechanism.

Harnessing the Granularity of Micro-Electrode-Dot-Array Architectures for Optimizing Droplet Routing in Biochips

In this article, we consider the problem of droplet routing for Microelectrode-Dot-Array (MEDA) biochips. MEDA biochips today provide a host of useful features for droplet movement by making it possible to manoeuvre droplets at a much finer granularity and with significantly increased flexibility. More precisely, MEDA biochips support more degrees of freedom in navigation and volumetric manipulation such as diagonal movement, droplet reshaping, and fractional-level split-and-merge. This helps improve routing of droplets on microfluidic grids—in particular, when the space available on the grid is limited or blocked by obstacles. In this work, we discuss how these improved capabilities can be utilized in the realization of the desired routes on those biochips. To this end, we introduce a routing method that utilizes satisfiability solvers and guarantees the generation of optimal solutions, considering the set of MEDA operations we model. This significantly improves the state of the art, since previously proposed solutions either (1) relied on heuristics and, hence, were not able to guarantee the optimum or (2) only considered a subset of the MEDA features. The solution proposed in this work includes a formulation of all MEDA features, which, as illustrated by examples, allows for the determination of routing solutions with smaller completion times. Experimental evaluations confirm these findings.

Security Assessment of Micro-Electrode-Dot-Array Biochips

Digital microfluidic biochips (DMFBs) are versatile, reconfigurable systems for manipulating discrete fluid droplets. Building on the success of DMFBs, platforms based on “sea-of-electrodes,” the micro-electrode-dot-array (MEDA), has been proposed to further increase scalability and reconfigurability. Research has shown that DMFBs are susceptible to actuation tampering attacks which alter control signals and result in fluid manipulation; such attacks have yet to be studied in the context of MEDA biochips. In this paper, we assess the security of MEDA biochips under such attacks, and further argue that it is inherently a more secure platform than traditional DMFBs. First, we identify a new class of actuation tampering attacks specific to MEDA biochips: the micro-droplet attack. We show that this new attack is stealthy as it produces a subtler difference in results compared to traditional DMFBs. We then illustrate our findings through a case study of an MEDA biochip implementing a glucose measurement assay. Second, we enumerate the system features required to secure an MEDA biochip against actuation tampering attacks and show that these features are naturally implemented in MEDA.

Multitarget Sample Preparation Using MEDA Biochips

Sample preparation, as a key procedure in many biochemical protocols, mixes various samples, and/or reagents into solutions that contain the target concentrations. Digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation because they provide automatic procedures that require less reactant consumption and reduce human-induced errors. However, the most existing methods only consider two-reactant sample preparation, and they cannot be used for many biochemical applications that involve multiple reactants. In addition, the existing methods that can be used for multiple-reactant sample preparation were proposed on traditional DMFBs where only the (1:1) mixing model is available. In the (1:1) mixing model, only two droplets of the same volume can be mixed at a time, which results in higher completion time and the wastage of valuable reactants. To overcome this limitation, the micro-electrode-dot-array (MEDA) architecture has been introduced; it provides the flexibility of mixing multiple droplets of different volumes in a single operation. In this article, we present a generic multiple-reactant sample preparation algorithm that exploits the novel fluidic operations on MEDA biochips. We also propose an enhanced algorithm that increases the operation-sharing opportunities when multiple target concentrations are needed, and therefore the usage of reactants can be further reduced. The simulated experiments show that the proposed method outperforms existing methods in terms of saving reactant cost, minimizing the number of operations, and reducing the amount of waste.

Micro-Electrode-Dot-Array Digital Microfluidic Biochips: Technology, Design Automation, and Test Techniques.

Digital microfluidic biochips (DMFBs) are being increasingly used for DNA sequencing, point-of-care clinical diagnostics, and immunoassays. DMFBs based on a micro-electrode-dot-array (MEDA) architecture have recently been proposed, and fundamental droplet manipulations, e.g., droplet mixing and splitting, have also been experimentally demonstrated on MEDA biochips. There can be thousands of microelectrodes on a single MEDA biochip, and the fine-grained control of nanoliter volumes of biochemical samples and reagents is also enabled by this technology. MEDA biochips offer the benefits of real-time sensitivity, lower cost, easy system integration with CMOS modules, and full automation. This review paper first describes recent design tools for high-level synthesis and optimization of map bioassay protocols on a MEDA biochip. It then presents recent advances in scheduling of fluidic operations, placement of fluidic modules, droplet-size-aware routing, adaptive error recovery, sample preparation, and various testing techniques. With the help of these tools, biochip users can concentrate on the development of nanoscale bioassays, leaving details of chip optimization and implementation to software tools.

Adaptive and Roll-Forward Error Recovery in MEDA Biochips Based on Droplet-Aliquot Operations and Predictive Analysis

Digital microfluidic biochips (DMFBs) are being increasingly used in biochemistry labs for automating bioassays. However, traditional DMFBs suffer from some key shortcomings: 1) inability to vary droplet volume in a flexible manner; 2) difficulty of integrating on-chip sensors; and 3) the need for special fabrication processes. To overcome these problems, DMFBs based on micro-electrode-dot -array (MEDA) have recently been proposed. However, errors are likely to occur on a MEDA DMFB due to chip defects and the unpredictability inherent to biochemical experiments. We present fine-grained error-recovery solutions for MEDA by exploiting real-time sensing and advanced MEDA-specific droplet operations. The proposed methods rely on adaptive droplet-aliquot operations and predictive analysis of mixing. In addition, a roll-forward error-recovery method is proposed to efficiently utilize the unused part of the biochip and reduce the time required for error recovery. Experimental results on three representative benchmarks demonstrate the efficiency of the proposed error-recovery strategy.

Structural and Functional Test Methods for Micro-Electrode-Dot-Array Digital Microfluidic Biochips

A digital microfluidic biochip (DMFB) is an attractive platform for immunoassays, point-of-care clinical diagnostics, DNA sequencing, and other laboratory procedures in biochemistry. More recently, DMFBs based on a micro-electrode-dot-array (MEDA) architecture have been proposed, and droplet manipulations on MEDA biochips have also been experimentally demonstrated. In order to ensure robust fluidic operations and high confidence in the outcome of biochemical experiments, MEDA biochips must be adequately tested before they can be used for bioassay execution. This paper presents the first approach for testing of MEDA biochips that include both CMOS circuits and microfluidic components. We first present structural test techniques to evaluate the pass/fail status of each microcell (droplet actuation, droplet maintenance, and droplet sensing) and identify faulty microcells. In order to ensure correct operation of functional units, e.g., mixers and diluters, we also present functional test techniques to address fundamental MEDA operations, such as droplet dispensing, transportation, mixing, and splitting. We evaluate the proposed test methods using simulations as well as experiments for fabricated MEDA biochips.