Sample preparation with multiple dilutions on digital microfluidic biochips

Bhattacharjee, Sukanta; Banerjee, Ansuman; Bhattacharya, Bhargab B.

doi:10.1049/iet-cdt.2013.0053

Cited by 21 publications

(5 citation statements)

References 20 publications

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“…In general, the goal in these algorithms is to minimize the number of mix-split steps (i.e., mixing time), reactant usage, storage requirement, or waste production. In 130 some approaches, the same cost (per unit volume) is assigned to both sample and buffer fluids [1,12,19,20]. These algorithms are primarily focused on the minimization of waste droplets, which indeed minimizes the total cost of input fluids (sample and buffer).…”

Section: K+mentioning

confidence: 99%

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Waste-aware single-target dilution of a biochemical fluid using digital microfluidic biochips

Roy

Chakrabarti

Chakrabarty

et al. 2015

Integration, the VLSI Journal

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A key challenge in design automation of digital microfluidic biochips is to carry out on-chip dilution/mixing of biochemical samples/reagents for achieving a desired concentration factor (CF). In a bioassay, reducing the waste is crucial because the management of waste droplets is cumbersome and expensive; transporting them to the waste reservoir and washing their pathways to clean contaminated regions and remove the residue left by them may increase assay completion time. The existing dilution algorithms attempt to reduce the number of mix-split steps required in the process but focus little on minimization of sample requirement or waste droplets. In this work, we characterize the underlying combinatorial properties of waste generation and identify the inherent limitations of two earlier mixing algorithms twoWayMix [Thies et al., Natural Computing, 2008] and DMRW [Roy et al., TCAD, 2010] in addressing this issue. Based on these properties, we design an improved dilution/mixing algorithm (IDMA) that optimizes the usage of intermediate droplets generated during the dilution process, which in turn, reduces the demand of sample/reagent and production of waste. The algorithm terminates in O(d) steps for producing a target CF with a maximum error of 1 2 d+1 , where d is the an accuracy level of the desired CF. Based on simulation results for all CF values ranging from 1 1024 to 1023 1024 using a sample (100% concentration) and a buffer solution (0% concentration), we present an integrated scheme of choosing the best waste-aware dilution algorithm among four approaches such as twoWayMix, DMRW, REMIA [Huang et al., ICCAD, 2012] and IDMA, for a single target CF. Finally, an architectural layout of a DMF biochip that supports the proposed scheme is designed.

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Section: K+mentioning

confidence: 99%

“…[13] introduced an algorithm called REMIA with an objective of minimizing reactant usage as well as wastage for solving the multi-target dilution problem. Bhattacharjee et al [19,25] proposed a pruning-based dilution algorithm to reduce wastage trations.…”

mentioning

confidence: 99%

Waste-aware single-target dilution of a biochemical fluid using digital microfluidic biochips

Roy

Chakrabarti

Chakrabarty

et al. 2015

Integration, the VLSI Journal

Self Cite

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“…Recently, several other algorithms for diluting a sample to generate serial or linear gradients, or to produce random multiple CFs, with reduced wastage and time, have been reported [Bhattacharjee et al 2013[Bhattacharjee et al , 2014Chiang et al 2013;Mitra et al 2012;Roy et al 2013a]. However, all these methods need the input fluid with a CF of 100%.…”

Section: Prior Work: Dilution and Mixing Algorithmsmentioning

confidence: 99%

Theory and analysis of generalized mixing and dilution of biochemical fluids using digital microfluidic biochips

Roy

Bhattacharya

Ghoshal

et al. 2014

J. Emerg. Technol. Comput. Syst.

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Digital microfluidic (DMF) biochips are recently being advocated for fast on-chip implementation of biochemical laboratory assays or protocols, and several algorithms for diluting and mixing of reagents have been reported. However, all methods for such automatic sample preparation suffer from a drawback that they assume the availability of input fluids in pure form, that is, each with an extreme concentration factor (CF) of 100%. In many real-life scenarios, the stock solutions consist of samples/reagents with multiple CFs. No algorithm is yet known for preparing a target mixture of fluids with a given ratio when its constituents are supplied with random concentrations. An intriguing question is whether or not a given target ratio is feasible to produce from such a general input condition. In this article, we first study the feasibility properties for the generalized mixing problem under the (1 : 1) mix-split model with an allowable error in the target CFs not exceeding 1 2 d , where the integer d is user specified and denotes the desired accuracy level of CF. Next, an algorithm is proposed which produces the desired target ratio of N reagents in O(Nd) mix-split steps, where N (≥ 3) denotes the number of constituent fluids in the mixture. The feasibility analysis also leads to the characterization of the total space of input stock solutions from which a given target mixture can be derived, and conversely, the space of all target ratios, which are derivable from a given set of input reagents with arbitrary CFs. Finally, we present a generalized algorithm for diluting a sample S in minimum (1 : 1) mix-split steps when two or more arbitrary concentrations of S (diluted with the same buffer) are supplied as inputs. These results settle several open questions in droplet-based algorithmic microfluidics and offer efficient solutions for a wider class of on-chip sample preparation problems.A preliminary version of a part of this article appeared in Roy et al. [2013b].

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“…mixture preparation. Subsequently, a few other dilution and mixing algorithms were reported with various optimization goals [13,41,42,[46][47][48].…”

Section: Mixing Algorithms and Biochip Layout Designmentioning

confidence: 99%

Algorithmic Challenges in Digital Microfluidic Biochips: Protocols, Design, and Test

2014

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Abstract. Recent emergence of microfluidic technology has imparted a profound impact on the implementation of miniaturized healthcare chips and systems. In this review article, we will elaborate on several algorithmic challenges that arise while realizing biochemical protocols on a digital microfluidic (DMF) lab-on-a-chip. In particular, we will focus on certain design automation issues of sample preparation, dilution gradient generation, layout planning, and testing of DMF biochips.

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Sample preparation with multiple dilutions on digital microfluidic biochips

Cited by 21 publications

References 20 publications

Waste-aware single-target dilution of a biochemical fluid using digital microfluidic biochips

Waste-aware single-target dilution of a biochemical fluid using digital microfluidic biochips

Theory and analysis of generalized mixing and dilution of biochemical fluids using digital microfluidic biochips

Algorithmic Challenges in Digital Microfluidic Biochips: Protocols, Design, and Test

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