Project Awardees
The Advanced Research Projects Agency for Health (ARPA-H) funds individual research projects that align with ARPA-H’s research focus areas but fall outside the scope of an ARPA-H program or initiative.
Projects are most often awarded through Mission Office Innovative Solution Openings (ISO) and historically through the Open BAA announcement. As of March 2024, ARPA-H is no longer accepting submissions for the Open BAA solicitation.
ARPA-H is pleased to announce the following project awardees.
D3PH: Decentralized Diabetes Data Platform for Senior Health Management
The D3PH project will develop edge computing technology to create advanced machine learning models that will predict and improve diabetes foot ulcer (DFU) risk prediction and wound healing prediction for senior citizens with diabetes in multiple long-term care clinics. While the goal is to pilot the technology for diabetes complications, success would enable availability of important technology for federated data sharing, and model development and deployment, that could be used for countless conditions, enabling efficient and affordable preventative health interventions. This will ensure advanced disease and health prediction models and improved health outcomes, decreased costs, and a decreased need for acute interventions throughout the medical system.
Tissue Preservation under Stress
Traumatic tissue injuries can happen unexpectedly and lead to life-threatening conditions. Despite advancements in wound care, millions of Americans lack immediate access to specialized medical facilities, increasing the risk of chronic wounds or death. Aging populations and individuals with underlying health conditions like diabetes and obesity are at greater risk of developing chronic wounds that fail to properly heal. The Tissue Preservation under Stress project seeks to develop cutting-edge technologies aimed at preserving the health and function of biological tissues under urgent stress or injury conditions. These therapies have the potential to significantly improve health care access for all Americans, especially in trauma care in under-resourced and rural communities. The TPS effort is a two-year focused effort on advanced development to translate these technologies toward clinical trials.
Cyber Health Intelligence (CHI): Sensing and Self-Healing Cyber Vulnerabilities in Healthcare Ecosystems
The Cyber Health Intelligence: Sensing and Self-Healing Cyber Vulnerabilities in Healthcare Ecosystems project will extend a previously DoE-funded framework - Common Weakness Enumerations (CWE) - into the healthcare sector. This technology, applied to the full ecosystem of connected things in healthcare and combined with novel orchestration and machine learning capabilities will dramatically improve cyber defenses. MD Anderson will achieve this by combining a) the digital ecosystem of healthcare at MD Anderson, b) a proven approach using machine learning technologies to enumerate and characterize cyber vulnerabilities and corresponding weaknesses, and c) an approach to facilitate weakness prioritization and mitigation through interactive prompting.
Eliminating Out-of-Hospital Adverse Events for Everyone with Congenital Heart Disease (CHD)
This project seeks to create a noninvasive, integrative hardware and software monitoring solution that prevents low cardiac output syndrome (LCOS), the leading cause of postoperative mortality in children and adults with congenital heart disease (CHD). This wearable technology would allow for continuous, high quality data acquisition of cardiac output information from children with congenital heart disease, leveraging a novel multi-modal approach that integrates four different sensors on a non-invasive patch. These advances in hardware integration will be combined with machine learning methods to match the combined sensor signals and cardiac output.
MEDAGuard: Medical Device Functionality Shielding Against Adverse Effects of Authorized Updates by Leveraging EM Side-Channels
The MEDAGuard: Medical Device Functionality Shielding Against Adverse Effects of Authorized Updates by Leveraging EM Side-Channels project will observe electromagnetic (EM) emissions from medical devices to detect when a device behaves abnormally. By analyzing embedded information with EM signals, MEDAGurad can enhance systems assurance for medical devices such as remote patient monitors. This "cyber smoke detector” compares captured signals with a baseline model derived from a known, properly functioning system version. Any deviations from expected behavior trigger an alert, indicating abnormal system activity or unexpected side-effects of updates, patches, etc. MEDAGuard stands as a notable leap forward in monitoring and attestation domain, especially for critical medical devices where system stability is vital. This sets it apart from state-of-the-art-systems, which often demand shared hardware or network connections with the device under scrutiny. In contrast, MEDAGuard relies solely on physical proximity.
Nutrition Based Satiety Modulation
Obesity and diet-related diseases have a significant negative impact on individual and public health outcomes, health care costs, and productivity. This effort ensures that Americans will have access to safe, affordable, and effective satiety modulators to control obesity. The Nutrition Based Satiety Modulation project aims to identify, characterize, and develop precision delivery nutrition platforms, beginning with testing generally recognized as safe (GRAS) compounds that confer satiety modulation/potentiation. Unlike recently developed pharmaceuticals such as GGLT2 inhibitors and GLP-1R agonists, VitaKey products will leverage natural mechanisms to modulate the body’s natural satiety responses to food intake. The goal is to formulate compounds that can be safely added to foods for broad distribution. The development and evaluation of natural, health-focused, nutrition-based satiety modulators could be scaled to provide an affordable and accessible solution for obesity treatment. If successful, this initiative has the potential to achieve GLP-1/GIP agonist effectiveness comparable to current pharmaceutical weight-loss treatments, without the associated side effects, and at significantly reduced cost. By developing these interventions, VitaKey will dramatically reduce many chronic diseases such as diabetes, cardiovascular disease, and cancer.
WHEAT: Wheat-Based High-efficiency Enzyme and API Technology
This project aims to develop a new way to make active pharmaceutical ingredients (API) in a cell-free manner using wheat germ extract (WGE), a key ingredient derived from agricultural wheat. To date, cell-free production has been plagued by low yield and inability to synthesize APIs with the required quality attributes. This project proposes using an abundant and cost-effective reagent in cell-free manufacturing. WGE is a significantly cheaper cell free production system than the competing front-runner biomass of E. coli and has the potential to be cost competitive with traditional chemical synthesis approaches. If successful, the team will have demonstrated a paradigm shift in domestic API manufacturing.
AI-Enabled Generation of Antigen-Specific Antibodies
Antibodies are effective as preventive and therapeutic measures against cancers, autoimmune disorders, and other diseases. This project aims to develop novel Artificial Intelligence (AI)-based algorithms and technologies to create novel monoclonal antibody candidates for further translational efforts and clinical validation against multiple diseases. The efforts are supported by LIBRA-seq, a single-cell technology developed by the team that enables high-throughput mapping of antibody sequence to antigen specificity for a large number of antigens and B cells at a time. Initial focus is on several priority targets to include cancer and autoimmune disease therapeutic development. For each target, lead AI-generated antibody candidates will be validated in vitro and in vivo, and one antibody candidate among all targets will be selected to perform IND-enabling studies. The results will serve as proof-of-concept for the ability of AI-based approaches to design efficacious monoclonal antibodies, will confirm the generalizability of the proposed strategies, and will showcase their broad potential impact to virtually any area where monoclonal antibodies can play an important role.
γδ CAR T-Cellular Vaccine for Solid Cancers
The treatment of solid tumors including colorectal cancer, non-small cell lung cancer, prostate cancer, and breast cancer, remains a challenge. Although chimeric antigen receptor (CAR) T-cell therapies have achieved success in treating hematologic cancers, these therapies show limited effectiveness against solid tumors. This project seeks to develop a novel approach targeting solid cancers using a Dual-action Antigen-presenting CAR γδ T-cell (DACART) therapy that combines the strengths of current advances in cancer vaccination. The team aims to leverage the advancement of four key technologies: CAR T-cell therapies, including successful therapies for blood cancers and novel strategies for solid tumors; dendritic cell (DC)-based cancer vaccines; techniques for engineering and expanding γδ T cells pioneered at Luminary Therapeutics; and efficient transposon-based cell engineering systems. The project aims to deliver a single, off-the-shelf, cost-effective cell therapy that effectively kills solid tumors while stimulating an endogenous antitumor immune response with low rate of relapse.
AdVAntage: Adenovirus Vectors Assembly for synthetic manufacturing advantage
The current production of adeno-associated virus-based gene therapy products heavily relies on cell-based manufacturing, which is inherently restrictive and inefficient. To address this issue, the project aims to establish a platform for producing cell-free gene therapy viral vectors using micro-fluidic flow chemistry. This approach will offer a more precise, scalable, and cost-effective process of gene therapy manufacturing. In addition, it will ensure a safer and more predictable product for usage in human subjects by eliminating contaminants derived from the cell-based origin. The strategy of the project involves producing viral components using cell-free systems, which will then be combined in a microfluidic flow cell to facilitate the autoassembly of viral particles. This flow cell will precisely regulate the crucial factors necessary for viral assembly in a system that reduces product manipulation for operators and manufacturing cost.