Optimal design of deterministic lateral displacement device for viscosity contrast based cell sorting

TL;DR

This paper presents a systematic optimization approach for designing deterministic lateral displacement devices to efficiently sort cells based on viscosity contrast, aiding rapid disease diagnosis.

Contribution

It formulates the DLD design as a constrained optimization problem and uses CMA-ES to discover optimal pillar configurations for cell sorting.

Findings

Optimized DLD designs effectively separate cells with similar viscosity contrasts.

The approach is the first to systematically optimize DLD device design as a constrained problem.

Simulation results demonstrate the potential for improved cell sorting efficiency.

Abstract

We solve a design optimization problem for deterministic lateral displacement (DLD) device to sort same-size biological cells by their deformability, in particular to sort red blood cells (RBCs) by their viscosity contrast between the fluid in the interior and the exterior of the cells. A DLD device optimized for efficient cell sorting enables rapid medical diagnoses of several diseases such as malaria since infected cells are stiffer than their healthy counterparts. The device consists of pillar arrays in which pillar rows are tilted and hence are not orthogonal to the columns. This arrangement leads cells to have different final vertical displacements depending on their deformability, therefore, it vertically separates the cells. Pillar cross section, tilt angle of the pillar rows and center-to-center distances between pillars define a unique device. For a given pair of viscosity contrast values of the cells we seek optimal DLD designs by fixing the tilt angle and the center-to-center distances. So the only design parameter is the pillar cross section which we parameterize with uniform 5th order B-splines. We propose an objective function to try to capture efficient cell sorting. The objective function is evaluated by simulating the cell flows through a device using our 2D model based on a boundary integral method (Kabacaoglu et al. Journal of Computational Physics, 357:43-77, 2018). We solve the optimization problem using the covariance matrix adaptation evolution strategy (CMA-ES), which is a stochastic, derivative-free algorithm. We present several scenarios where solving the optimization problem finds designs that can separate cells with similar viscosity contrast values. To the best of our knowledge, this is the first study which poses designing a DLD device as a constrained optimization problem and shows that solving this problem systematically discovers optimal designs.