Design Automation Methods and Tools for Microfluidics-Based Biochips

Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, 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. We present 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 microelectronic component in nextgeneration SOCs.

Digital microfluidics is the second-generation lab-on-a-chip architecture based upon micromanipulation of droplets via a programmed external electric field by an individually addressable electrode array. Dielectrophoresis (DEP) and electrowetting-on-dielectric (EWOD) are of the dominant operating principles. The microfluidic mechanics of manipulating electrified droplets are complex and not entirely understood. In this article, we present a numerical simulation method based on droplet electrohydrodynamics (EHD). First we show a systematic validation study comparing the simulation solution with both analytical and experimental data, quantitatively and qualitatively, and in both steady state and transient time sequences. Such comparison exhibits excellent agreement. Simulations are then used to illustrate its application to computeraided design of both EWOD-driven and DEP-driven digital microfluidics.

For a wide variety of micromachined devices, designers need accurate analysis of fluid drag forces for complicated three-dimensional problems. In this paper we describe FastStokes, a recently developed three-dimensional fluid analysis program. FastStokes rapidly computes drag forces on complicated structures by solving an integral formulation of the Stokes equation using a precorrected- FFT accelerated boundary-element method. The specializations of the precorrected-FFT algorithm to the Stokes flow problem are described, and computational results are presented. Timing results are used to demonstrate that FastStokes scales almost linearly with problem complexity, can easily analyze structures as complicated as an entire comb drive in under an hour, and can produce results that accurately match measured data.

This paper presents composable behavioral models and a schematic-based simulation methodology to enable top-down design of electrokinetic Lab-on-a- Chip (LoC) systems. Complex electrokinetic LoCs are shown to be decomposable into a system of elements with simple geometries and specific functions. Parameterized and analytical models are developed to describe the electrical and biofluidic behavior within each element. Electrical and biofluidic pins at element terminals support the communication between adjacent elements in a simulation schematic. An analog hardware description language implementation of the models is used to simulate LoC subsystems for micromixing and electrophoretic separation. Both direct current (DC) and transient analysis can be performed to capture the influence of system topologies, element sizes, material properties, and operational parameters on LoC system performance. Accuracy (relative error generally less than 5%) and speedup (>100×) of the schematic-based simulation methodology is demonstrated by comparison to experimental measurements and continuum numerical simulation.

We present a fast boundary element method (BEM) algorithm that is well-suited for solving electrostatics problems that arise in traditional and Bio-MEMS design. The algorithm, FFTSVD, is Green’s function independent for low-frequency kernels and efficient for inhomogeneous problems. FFTSVD is a multiscale algorithm that decomposes the problem domain using an octree and uses sampling to calculate low-rank approximations to dominant source distributions and responses. Long-range interactions at each length scale are computed using the FFT. Computational results illustrate that the FFTSVD algorithm performs better than precorrected-FFT style algoriwthms or the multipole style algorithms in FastCap.

In this short paper we present a technique for automatically extracting nonlinear macromodels of bioMEMS devices from physical simulation. The technique is a modification of the recently developed Trajectory Piecewise-linear (TPWL) approach, but uses ideas from balanced truncation to produce much lower-order and more accurate models. The key result is a perturbation analysis of an instability problem with the reduction algorithm, and a simple modification that makes the algorithm more robust. Results are presented from examples to demonstrate dramatic improvements in reduced model accuracy and show the limitations of the method.

Development of lab-on-a-chip systems has moved from the demonstration of individual components to a complex assembly of components. Due to the increased complexities associated with model setup, and computational time requirements, current design approaches using spatial and time resolved multiphysics modeling, though viable for component-level characterization, become unaffordable for system-level design. To overcome these limitations, we present models for the system-level simulation of fluid flow, electric field and analyte dispersion in microfluidic devices. Compact models are used to compute the flow (pressure-driven and electroosmotic) and are based on the integral formulation of the mass, momentum and current conservation equations. An analytical model based on the method of moments approach has been developed to characterize the dispersion induced by combined pressure and electrokinetic driven flow. The methodology has been validated against detailed 3D simulations and has been used to analyze hydrostatic pressure effects in electrophoretic separation chips. A 100-fold improvement in the computational time without significantly compromising the accuracy (error less than 10%) has been demonstrated.

Lab-on-a-chip systems can be functionally decomposed into their basic operating devices. Common devices are mixers, reactors, injectors, and separators. In this work, the injector device is modeled using artificial neural networks trained with finite element simulations of the underlying mass transport PDE’s. This technique is used to map the injector behavior into a set of analytical performance functions parameterized by the system’s physical variables. The injector examples shown are the cross, double-tee, and gatedcross. The results are four orders of magnitude faster than numerical simulation and accurate with mean square errors on the order of 10^-4. The resulting neural network training data compares favorably with experimental data from a gated-cross injector found in the literature.

DNA probe arrays, or DNA chips, have emerged as a core genomic technology that enables cost-effective gene expression monitoring, mutation detection, single nucleotide polymorphism analysis and other genomic analyses. DNA chips are manufactured through a highly scalable process, called Very Large-Scale Immobilized Polymer Synthesis (VLSIPS), that combines photolithographic technologies adapted from the semiconductor industry with combinatorial chemistry. As the number and size of DNA array designs continues to grow, there is an imperative need for highly-scalable software tools with predictable solution quality to assist in the design and manufacturing process. In this chapter we review recent algorithmic and methodological advances forming the foundation for a new generation of DNA array design tools. A recurring motif behind these advances is exploiting the analogy between silicon chip design, pointing to the value of technology transfer between the 40-year old VLSI CAD field and the newer DNA array design field.

Lab-on-a-Chip (LoC) devices are a class of microfluidic chip-based systems that show a great deal of promise for complex chemical and biological sensing and analysis applications. We are developing an approach for full-custom LoC design that leverages optimal design techniques and System on a Chip (SoC) physical design methods. We simultaneously consider both the physical design of the chip and the microfluidic performance to obtain complete LoC layouts. We demonstrate our approach by designing multiplexed capillary electrophoresis (CE) separation microchips. We believe that this approach provides a foundation for future extension to LoC devices in which many different complex chemical operations are performed entirely on-chip.

This paper presents general, hardware-independent models and algorithms to automate the operation of droplet-based microfluidic systems. In these systems, discrete liquid volumes of typically less than 1μl are transported across a planar array by dielectrophoretic or electrowetting effects for biochemical analysis. Unlike in systems based on continuous flow through channels, valves, and pumps, the droplet paths can be reconfigured on demand and even in real time. We develop algorithms that generate efficient sequences of control signals for moving one or many droplets from start to goal positions, subject to constraints such as specific features and obstacles on the array surface or limitations in the control circuitry. In addition, an approach towards automatic mapping of a biochemical analysis task onto a droplet-based microfluidic system is investigated. Achieving optimality in these algorithms can be prohibitive for large-scale configurations because of the high asymptotic complexity of coordinating multiple moving droplets. Instead, our algorithms achieve a compromise between high run-time efficiency and a more limited, non-global optimality in the generated control sequences.

This chapter describes a computational approach to designing a digital micro- fluidic system (DMFS) that can be rapidly reconfigured for new biochemical analyses. Such a “lab-on-a-chip” system for biochemical analysis, based on electrowetting or dielectrophoresis, must coordinate the motions of discrete droplets or biological cells using a planar array of electrodes. We earlier introduced our layout-based system and demonstrated its flexibility through simulation, including the system’s ability to perform multiple assays simultaneously. Since array layout design and droplet routing strategies are closely related in such a digital microfluidic system, our goal is to provide designers with algorithms that enable rapid simulation and control of these DMFS devices.

Biochips are emerging as a useful tool for high-throughput acquisition of biological data and continue to grow in information quality and in discovering new applications. Recent advances include CMOS-based integrated biosensor arrays for deoxyribonucleic acid (DNA) expression analysis [35, 17], and active research is ongoing for the miniaturization and integration of protein microarrays [36, 19, 33], tissue microarrays (TMAs) [37, 8], and fluorescence-based multiplexed cytokine immunoassays [41].