A Hybrid Microfluidic Device for Label Free Manipulation and Size-Independent Separation of Microentities

Abstract

Cancer is the second leading cause of death worldwide and the third in United Arab Emirates, accounting for an estimated 9.6 million deaths across the globe in 2018. The disease is characterized by uncontrolled division of abnormal cells which causes those cells to form solid tumors - lumps or masses of tissues – that impede the normal functionalities of organs. During its progression, the solid tumors shed some of the cancer cells called Circulating Tumor Cells, which are then migrated through the bloodstream to any other location inside the body and cause secondary tumor in a process called metastasis and is the major reason of mortality in cancer-related deaths. Hence, the detection and isolation/enrichment of Circulating Tumor Cells from blood samples is an active field of research since it allows for an early detection of cancer, thus enabling the healthcare workers to fight against the menace effectively. Microfluidics, a technology that utilizes tiny volumes of fluids and samples, has emerged as an attractive method to detect diseases on molecular level. The current project focuses on the design, modeling, and fabrication of a practical microfluidic-based platform that can separate microentities to enable the separation of rare Circulating Tumor Cells from human blood. The separation of microentities is to be performed in a continuous manner by utilizing a hybrid technique employing surface acoustic waves and dielectrophoresis. The technology will not only enable the early detection of cancer but also the effectiveness of the administered treatment for cancer patients. To date, several acoustophoresis and dielectrophoresis based devices for particles manipulation have been fabricated and tested. In this work, a novel design for a hybrid system that employs acoustophoresis and dielectrophoresis has been analyzed and developed. The system was designed, modeled, fabricated, and tested successfully showing an efficient and fast separation of microentities.

Date of Award	2024
Original language	American English
Supervisor	Anas Alazzam (Supervisor)