BioScript: programming safe chemistry on laboratories-on-a-chip

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform

A droplet routing technique for fault-tolerant digital microfluidic devices

Abstract—Efficient droplet routing is one of the key approaches for realizing fault-tolerant microfluidic biochips. It requires that run-time diagnosis and fault recovery can be made possible in such systems. This paper describes a droplet routing technique for a fault-tolerant digital microfluidic platform. This technique features handling of many microfluidic operations simultaneously and uses on-chip sensors for diagnosis at run-time.\ud Once a fault is detected during the droplet routing, recovery procedures will be started-up immediately. Faulty units on the chip will be marked and isolated from the array so that the remaining droplets can still be routed along a fault-free path to their destinations. This method guarantees a non-stop fault-tolerant operation for very large microfluidic arrays.\u

Droplet routing for digital microfluidic biochips based on microelectrode dot array architecture

A digital microfluidic biochip (DMFB) is a device that digitizes fluidic samples into tiny droplets and operates chemical processes on a single chip. Movement control of droplets can be realized by using electrowetting-on-dielectric (EWOD) technology. DMFBs have high configurability, high sensitivity, low cost and reduced human error as well as a promising future in the applications of point-of-care medical diagnostic, and DNA sequencing. As the demands of scalability, configurability and portability increase, a new DMFB architecture called Microelectrode Dot Array (MEDA) has been introduced recently to allow configurable electrodes shape and more precise control of droplets. The objective of this work is to investigate a routing algorithm which can not only handle the routing problem for traditional DMFBs, but also be able to route different sizes of droplets and incorporate diagonal movements for MEDA. The proposed droplet routing algorithm is based on 3D-A* search algorithm. The simulation results show that the proposed algorithm can reduce the maximum latest arrival time, average latest arrival time and total number of used cells. By enabling channel-based routing in MEDA, the equivalent total number of used cells can be significantly reduced. Compared to all existing algorithms, the proposed algorithm can achieve so far the least average latest arrival time

Synthesis of biochemical applications on digital microfluidic biochips with operation variability

Abstract—Microfluidic-based biochips are replacing the con-ventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis using microfluidics. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets. Researchers have presented approaches for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling and place-ment of the operations in the application. Existing approaches consider that on-chip operations, such as splitting a droplet of liquid, are perfect. However, these operations have variability margins, which can impact the correctness of the biochemical application. We consider that a split operation, which goes beyond specified variability bounds, is faulty. The fault is detected using on-chip volume sensors. We have proposed an abstract model for a biochemical application, consisting of a sequencing graph, which can capture all the fault scenarios in the application. Starting from this model, we have proposed a synthesis approach that, for a given chip area and number of sensors, can derive a fault-tolerant implementation. Two fault-tolerant scheduling techniques have been proposed and compared. We show that, by taking into account fault-occurrence information, we can derive better quality implementations, which leads to shorter application completion times, even in the case of faults. The proposed synthesis approach under operation variability has been evaluated using several benchmarks. I