Genetic Algorithm based Optimization of Single Node in Reformed-Digital Micro Fluidic Biochip

Abstract

Objectives: Optimization of single node / port in the Reformed Digital Micro Fluidic Biochip (RDMFB) has been carried out in this work. The Digital Micro Fluidic Biochip (DMFB) consists of two reservoirs / ports, one for sample (any biological solution) and the other for reagent (chemical solution). In each port two samples and two reagents, in the form of droplet i.e. nano / micro litre volume have been placed in respective ports. Based on application, at each instance only one solution has to be routed from reservoir to mixer and then to detector. In order to implement this, an optimization technique has been posed to decide which one has to be routed first. Methods: The optimization algorithm opted is of an evolutionary algorithm – Genetic Algorithm. It has been implemented for both sample port and reagent port. This algorithm has been opted due to its life science characteristic to get a better and optimal solution for any biological sample when it is being injected or diagnosed. Two samples in the form of droplet i.e. nano / micro litre volume have been used to route, both will be any biological sample which is placed in same node / port, similarly, in reagent port chemical solution has been placed. The port has to decide which one has to be routed based on application with the help of control pin used. Findings: The 15 x 15 array DMFB has been reformed into a new one in order to minimize the number of cells in an array. By this way of a modification, a 12 x 12 array DMFBi.e. RDMFB has been designed. The optimized output has been simulated in Xilinx platform and FPGA synthesis has been done in Plan Ahead software.Application: DMFB plays a vital role in our day-to-day life for various biological diagnoses in clinical laboratory. It is a lab on chip device.