Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
149 University of North Texas (142037)
Principal Investigator: Kim,Jungkwun
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 117,700
Exceeds $250,000 (Is it flagged?): No
Start and End Dates: 9/1/22 - 6/30/24
Restricted Research: YES
Academic Discipline: Electrical Engineering
Department, Center, School, or Institute: College of Engineering
Title of Contract, Award, or Gift: Collaborative Research: CPS: Medium: A CPS approach to tumor immunomodulation; sensing, analysis, and control to prime tumors to immunotherapy
Name of Granting or Contracting Agency/Entity:
Kansas State University
CFDA Link: NSF
47.070
Program Title:
none
CFDA Linked: Computer and Information Science and Engineering
Note:
Cancer remains the second leading cause of death in the US. Immunotherapy is a cancer treatment that aims to help the body’s immune system fight cancer. While excellent responses have been observed for a large number of patients with varying disease types, a considerably larger number of patients have received little to no benefit from immunotherapy. This varied outcome has been attributed to the highly heterogeneous physical and physiological profile within established tumors that suppress the immune system’s response to tumors. Various physical, chemical, and biological treatment modalities are under investigation for altering the tumor environment from a state where immune effects are suppressed, to one supportive of an anti-tumor immune response. However, these approaches are hampered by the lack of techniques for monitoring the tumor state in response to candidate treatments. Technologies that enable continuous monitoring of the tumor’s immune state, and thereby guide precise delivery of interventions to drive tumors to an immunostimulatory state, offer the promise of unlocking the full potential of immunotherapies. A cyber-physical systems (CPS) perspective is uniquely suited to addressing this challenge, treating the tumor as an “in-body CPS” with the development of sensors and analytical techniques for longitudinal assessment of the tumor, coupled with co-located methods for delivering physical/chemical treatments for modulating the environment within the tumor towards an immunostimulatory state. This project will investigate a CPS framework for immunomodulation of the tumor microenvironment (TME), integrating: (1) a unique 3D micro-array sensor and treatment (MIST) device consisting of a sensing/actuation platform for longitudinal sensing and control of physical and physiological parameters within the TME; (2) novel model-informed machine learning techniques for determining tumor immune state from TME physical/physiologic characteristics; and (3) model-guided therapy via the MIST device for driving the TME to an immunostimulatory state. Advanced 3D fabrication technology will provide implantable micromachined multimodal sensing devices to enable longitudinal in vivo sensing of TME parameters such as tissue oxygenation, pH, pressure, and metabolism, and co-located treatment on a single device. Data gathered from implantable sensors will be fused with computational models of biophysical parameters informed by tumor-specific vasculature maps using a graph neural tensor completion approach. The novel hybrid machine learning approach for data imputation and fusion will systematically incorporate uncertainties and provide the basis to infer the immune state of a tumor, validated against gold-standard molecular biomarkers of immune state in experimental small animals. A graph-based clustering approach integrated with a recurrent neural network will be used for the prediction of tumor state changes. Finally, we will evaluate the efficacy of model-guided delivery of energy-based interventions to transform the TME to a pro-immunogenic state and the impact of these interventions on immunotherapy outcomes in small animals.
Discussion: No discussion notes