A Decision Tree Mechanism for Microfluidic Sample Preparation for Digital Biochips

Microfluidic technology has achieved a rapid technological advancement and become well admired in miniaturized laboratory works. Effectiveness of laboratory works such as protein and glucose analysis, and pharmaceutical study depends on convenient sample preparation. These processes involve dilution of the primary reactant with buffer fluid in an appropriate proportion to ensure error-free bioassay operations in the future. In this paper, a decision tree-based method is proposed to construct the mixing tree for exploring all possible combinations of concentration values to generate the target sample for different biochemical experiments. This work is also extended for multi-target sample preparation concurrently to reduce the sample preparation time and cost. The simulated result shows that the proposed technique not only reduces the mixing/dilution operations for single-target sample preparation but also minimizes the use of primary reactant compared to the contemporary approaches and an enhanced outcome is also achieved for multi-target sample production.