II PILOT 2
Microrobots for Monitoring and treating Sickle-cell Induced Ischemia
Investigator: Sambeeta Das
Profile
Dr. Sambeeta ‘Sam’ Das is an assistant professor at the University of Delaware in the Mechanical Engineering Department. Before joining the University of Delaware, Dr. Das was a postdoctoral researcher for three years at the University of Pennsylvania. She was part of the GRASP Lab where she worked on microrobotic control and application of microrobots in biological systems. She earned her Ph.D. at the Pennsylvania State University in 2016 and her doctoral research was on directing micro and nanomotors and their applications in lab-on-a chip devices. Prior to her doctoral studies, she earned her Masters with distinction from the University of London and her Bachelors in Physics from Presidency College, India. She is the recipient of multiple awards including a graduate fellowship from the Pennsylvania State University, the overseas research award fellowship from the government of United Kingdom, and the Science and Engineering Excellence Fellowship from the University of London.
Dr. Das’s research is very interdisciplinary spanning multiple fields like robotics, autonomous systems, physics, organic chemistry, materials engineering, soft matter, and biomedical engineering. The goal of her lab is to seamlessly combine these disparate disciplines to address challenges in tissue engineering. Her research activities focus on develop microrobots capable of precision delivery of biochemicals and cellular patterning; for applications in personalized therapeutics, drug delivery, and high throughput biotechnology research.
Project Summary
About 100,000 Americans live with sickle cell disease and 30% of those have HBSC, a genotype that is associated with a 30-70% occurrence of proliferative sickle cell retinopathy. Sickle cell retinopathy occurs due to local ischemia leading to vascular proliferation and vitreous hemorrhage which can result in partial or complete vision loss. Currently, the typical diagnostic and monitoring methods for retinopathy suffer from slow capture time, artifacts, low resolution, unwanted side effects, and/or inability to quantitatively measure blood flow, particularly in small vessels. Thus, in addition to improved diagnosis and monitoring, quantitative blood flow measurements could provide an important clue in predicting, and hence preventing, the onset of circulation interruption. Indeed, average blood flow speed in large vessels in the eye, measured using CDI, has been found to correlate with the degree of severity of diabetic retinopathy. However, data of smaller vessels is currently lacking and would help further elucidate pathology of vascular occlusion. Therefore, it is essential to develop methods for capturing such measurements in smaller vessels.
To address this need, we propose to use microrobots, maneuverable micron-sized objects, to measure the hemodynamics in a range of vessel sizes down to the smallest capillaries. The microrobots we will employ are magnetically driven and, once moved to the location of interest, could be used to quickly obtain information about blood flow speeds. They could also be used repeatedly to monitor changes in flow over the course of minutes to days which provides an advantage over current technologies and could serve as an important diagnostic tool. Due to their actuation methodology, control and path planning algorithms from traditional robotics can be applied to these small-scale particles.
Publications
https://www.ncbi.nlm.nih.gov/myncbi/sam.das.1/bibliography/public/