Design Automation Techniques for Microfluidic Fully Programmable Valve Array Biochips: A Systematic Survey
Year: 2025
Type: article
Abstract: Flow-based microfluidic biochips have attracted much attention over the past two decades. By integrating diverse micro-components, e.g., mixers and filters, on a miniaturized planar substrate, complicated bioassays such as protein crystallization and drug screening can be executed automatically without requiring human invention, thus becoming a promising alternative to traditional cumbersome laboratory equipment. As manufacturing technology advances, it has become possible to implement hundreds of thousands of microvalves within a single chip. This breakthrough has given rise to fully programmable valve array (FPVA) biochips, representing a next-generation platform in flow-based microfluidics that offers enhanced reconfigurability and operational flexibility. Nevertheless, the exponential increase in valve density has introduced significant design complexity when implementing sophisticated assay protocols. As a result, the design automation of FPVAs has emerged as a critical research frontier, attracting considerable attention from both academia and industry. This review article systematically examines recent advances in FPVA design automation, involving computer-aided design methods for architectural synthesis, volume management, sample preparation, automated testing, fault localization, error recovery, and washing optimization. These techniques enable FPVA users to concentrate on assay protocol development while delegating implementation-specific design and optimization tasks to design automation tools. Furthermore, we analyze emerging security implications in FPVAs, particularly focusing on bioassay accuracy and reliability that ensure experimental reproducibility. Finally, potential trajectories for future research are discussed in detail to further promote the integration level and widespread application of FPVAs.
DOI: 10.1145/3768629
Authors: Shuang Qi, Zhiwen Yu, Bin Guo, Sizhao Li, Zipeng Li, Hanbin Ma, Tsungyi Ho, Krishnendu Chakrabarty, Xing Huang
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4414527597
