Multitarget Sample Preparation Using MEDA Biochips

Tung-Che Liang*, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Chen-Yi Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Article number8840917
Pages (from-to)2682-2695
Number of pages14
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume39
Issue number10
DOIs
StatePublished - Oct 2020

Keywords

  • Design automation
  • micro-electrode-dot-array
  • microfluidics
  • optimization algorithm
  • sample preparation

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