Diagnostic blood testing is the most ubiquitous clinical procedure in the US, with over 1 billion tests performed annually. The traditional method of blood testing involves performing a venipuncture, transporting samples to a centralized lab, analyzing the samples using large benchtop instruments, and relaying the results to the clinician. This is a labor intensive, time consuming, and expensive process, and unexpected delays often arise due either to difficulties in performing the venipuncture or the time needed to transport and analyze the sample. Particularly in the hospital emergency department (ED), rapid changes in a patient's condition necessitate immediate response, and thus delays can be life threatening. Point of care (PoC) blood testing has emerged as a way to potentially reduce turnaround times, and several devices based on capillary blood draws have achieved commercial translation. However, in comparison to centralized testing, the quantity of available assays remains limited for existing PoC testing, and the accuracy of results obtained with capillary blood remains controversial. Venous blood draws via a venipuncture allows for the collection of a larger volume of blood, yielding more dependable results as the specimen comes directly from the circulation. However to date, no fully automated venous access devices are available, either as independent units, or coupled with POC testing platforms. To address these current limitations, our group is developing a portable, automated device that performs venipuncture and provides quantitative diagnostic results in 15 to 30 minutes at the point of patient care. The portable device will operate by imaging a patient's veins, autonomously introducing a needle into a selected vein, drawing blood into microfluidics chips, and performing on-board blood analysis via an integrated optical imaging platform. A single device will be able to support the throughput of most emergency departments; in this way, the proposed device would serve as an all-in-one portable STAT lab for rapid, automated emergency diagnostics. Outside of emergency medicine, the device could furthermore have strong impact in areas such as ambulatory and outpatient facilities, pediatric and geriatric care, as well as military use.

Public Health Relevance

Our group aims to develop a portable, automated device for rapid venous blood draws and point-of-care diagnostic analysis. The portable device will operate by imaging a patient's veins, autonomously introducing a needle into a selected vein, drawing blood into microfluidics chips, and performing on-board blood analysis via an integrated optical detection platform. Once translated, this technology will have the potential for impact in number of arenas, including pediatric, geriatric, emergency, and military use. The integrative solution will be particularly suited for infant and neonatal applications, where difficult venipuncture and low blood volume requirements greatly challenge the safety and quality of care. Furthermore, the core technological advancements will interest a spectrum of research disciplines, including hematology and diagnostic medicine, BioMEMS and microfluidics, optics, and medical robotics.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB020036-03
Application #
9275983
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Lash, Tiffani Bailey
Project Start
2015-09-20
Project End
2019-05-31
Budget Start
2017-06-01
Budget End
2018-05-31
Support Year
3
Fiscal Year
2017
Total Cost
$650,321
Indirect Cost
$168,485
Name
Rutgers University
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
001912864
City
Piscataway
State
NJ
Country
United States
Zip Code
08854
Shrirao, Anil B; Fritz, Zachary; Novik, Eric M et al. (2018) Microfluidic flow cytometry: The role of microfabrication methodologies, performance and functional specification. Technology (Singap World Sci) 6:1-23
Balter, M L; Leipheimer, J M; Chen, A I et al. (2018) Automated end-to-end blood testing at the point-of-care: Integration of robotic phlebotomy with downstream sample processing. Technology (Singap World Sci) 6:59-66
Shrirao, Anil B; Kung, Frank H; Omelchenko, Anton et al. (2018) Microfluidic platforms for the study of neuronal injury in vitro. Biotechnol Bioeng 115:815-830
Balter, Max L; Chen, Alvin I; Maguire, Timothy J et al. (2017) Adaptive Kinematic Control of a Robotic Venipuncture Device Based on Stereo Vision, Ultrasound, and Force Guidance. IEEE Trans Ind Electron 64:1626-1635
Fromholtz, Alex; Balter, Max L; Chen, Alvin I et al. (2017) Design and Evaluation of a Robotic Device for Automated Tail Vein Cannulations in Rodent Models. J Med Device 11:0410081-410087
Chen, Alvin I; Balter, Max L; Chen, Melanie I et al. (2016) Multilayered tissue mimicking skin and vessel phantoms with tunable mechanical, optical, and acoustic properties. Med Phys 43:3117-3131
Chen, Alvin I; Balter, Max L; Maguire, Timothy J et al. (2016) 3D Near Infrared and Ultrasound Imaging of Peripheral Blood Vessels for Real-Time Localization and Needle Guidance. Med Image Comput Comput Assist Interv 9902:388-396
Balter, Max L; Chen, Alvin I; Colinco, C Amara et al. (2016) Differential Leukocyte Counting via Fluorescent Detection and Image Processing on a Centrifugal Microfluidic Platform. Anal Methods 8:8272-8279
Balter, Max L; Chen, Alvin I; Fromholtz, Alex et al. (2016) System Design and Development of a Robotic Device for Automated Venipuncture and Diagnostic Blood Cell Analysis. Rep U S 2016:514-520
Chen, Alvin I; Balter, Max L; Maguire, Timothy J et al. (2015) Real-time Needle Steering in Response to Rolling Vein Deformation by a 9-DOF Image-Guided Autonomous Venipuncture Robot. Rep U S 2015:2633-2638

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