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Puddle: A Dynamic, Error-Correcting, Full-Stack Microfluidics Platform

Authors:

Ashley P. Stephenson,

Chris Takahashi,

Bichlien H. Nguyen,

Michal Piszczek,

Christine Betts,

Luis CezeAuthors Info & Claims

ASPLOS '19: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems

Pages 183 - 197

https://doi.org/10.1145/3297858.3304027

Published: 04 April 2019 Publication History

Abstract

Microfluidic devices promise to automate wetlab procedures by manipulating small chemical or biological samples. This technology comes in many varieties, all of which aim to save time, labor, and supplies by performing lab protocol steps typically done by a technician. However, existing microfluidic platforms remain some combination of inflexible, error-prone, prohibitively expensive, and difficult to program. We address these concerns with a full-stack digital microfluidic automation platform. Our main contribution is a runtime system that provides a high-level API for microfluidic manipulations. It manages fluidic resources dynamically, allowing programmers to freely mix regular computation with microfluidics, which results in more expressive programs than previous work. It also provides real-time error correction through a computer vision system, allowing robust execution on cheaper microfluidic hardware. We implement our stack on top of a low-cost droplet microfluidic device that we have developed. We evaluate our system with the fully-automated execution of polymerase chain reaction (PCR) and a DNA sequencing preparation protocol. These protocols demonstrate high-level programs that combine computational and fluidic operations such as input/output of reagents, heating of samples, and data analysis. We also evaluate the impact of automatic error correction on our system's reliability.

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Cited By

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Liu GZeng YZhu YCai HGuo WLi ZHo THuang X(2024)Towards Automated Testing of Multiplexers in Fully Programmable Valve Array Biochips2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)10.1109/ASP-DAC58780.2024.10473918(570-575)Online publication date: 22-Jan-2024
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Index Terms

Puddle: A Dynamic, Error-Correcting, Full-Stack Microfluidics Platform

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cover image ACM Conferences

ASPLOS '19: Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems

April 2019

1126 pages

ISBN:9781450362405

DOI:10.1145/3297858

General Chairs:
Iris Bahar
Brown University
,
Maurice Herlihy
Brown University
,
Program Chairs:
Emmett Witchel
University of Texas, Austin
,
Alvin Lebeck
Duke University

Copyright © 2019 Owner/Author.

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Published: 04 April 2019

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April 13 - 17, 2019

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ASPLOS '19 Paper Acceptance Rate 74 of 351 submissions, 21%;

Overall Acceptance Rate 535 of 2,713 submissions, 20%

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Cited By

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https://dl.acm.org/doi/10.1145/3613904.3642751
Liu GZeng YZhu YCai HGuo WLi ZHo THuang X(2024)Towards Automated Testing of Multiplexers in Fully Programmable Valve Array Biochips2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)10.1109/ASP-DAC58780.2024.10473918(570-575)Online publication date: 22-Jan-2024
https://doi.org/10.1109/ASP-DAC58780.2024.10473918
Kawakami TShiro CNishikawa HKong XTomiyama HYamashita S(2023)A Deep Reinforcement Learning Approach to Droplet Routing for Erroneous Digital Microfluidic BiochipsSensors10.3390/s2321892423:21(8924)Online publication date: 2-Nov-2023
https://doi.org/10.3390/s23218924
Xu JFan WMadsen JTanev GPezzarossa L(2023)AI-Based Detection of Droplets and Bubbles in Digital Microfluidic Biochips2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE56975.2023.10136887(1-6)Online publication date: Apr-2023
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