WounDx™: Revolutionizing Wound Care to Improve Warfighter Readiness and Reduce Costs

A new biomarker-based tool developed by USU researchers aims to improve treatment decisions for complex extremity injuries in military and civilian patients.

A graphic illustration showing a person in a lab coat holding a tablet with a glowing human figure projected above it. The background includes overlapping images of a DNA helix, a brain outline, chemical structures, and pills, all in shades of blue and white, suggesting a medical or scientific context.
Researchers from USU's SC2i and HJF have developed WounDx™ to help surgeons make
quick, accurate treatment decisions for complex extremity injuries. (Graphic credit: Sofia
Echelmeyer, USU)

April 22, 2025 by Vivian Mason

Combat casualties often experience complex extremity injuries involving extensive soft tissue damage, bone fractures, and potential limb loss, requiring specialized medical care and reconstruction. While many wounds are treated surgically by cleaning and closing the edges with strips, sutures, or staples, often with grafts or flaps, a new method is emerging to support healing.

Researchers from the Uniformed Services University’s (USU’s) Surgical Critical Care Initiative (SC2i) and the Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF) have developed WounDx™ to help surgeons make quick, accurate treatment decisions for these injuries. WounDx™ is a biomarker-based clinical decision support tool designed to optimize the timing of wound closure. This software aims to improve care for wounded warfighters, reduce costs, enhance resource availability, and contribute to medical readiness.

A man in a suit and tie smiles at the camera with a blurred building and trees in the background.
Dr. Seth Schobel (Courtesy photo)
Currently, no diagnostic tool exists to accurately predict the optimal timing for wound closure. However, ongoing research on WounDx™ at the Uniformed Services University—led by Dr. Seth Schobel, scientific director of SC2i and associate professor in the Department of Surgery, along with USU School of Medicine Dean Dr. Eric Elster and SC2i collaborators Dr. Henry Robertson, Dr. Felipe Lisboa, Dr. Michael Rouse, and Dr. Scott Grey—has significant implications for both military and civilian healthcare systems. Schobel, a bioinformatician, has dedicated nearly 10 years to this project. On February 7, 2025, the FDA granted SC2i's WounDx™ an Investigational Device Exemption, permitting a clinical trial to begin in June/July 2025 to test the device's safety and effectiveness. This marks a significant milestone for the team.

Specifically, WounDx™ provides surgeons with a wound-specific probability of normal healing if closed at the next surgical encounter. It includes a diagnostic assay kit and a machine learning model embedded in software to predict optimal wound closure timing. Machine learning utilizes artificial intelligence and statistical techniques to derive information from large datasets. The current prediction model was developed using a subset of clinical characteristics and effluent biomarkers taken before, during, and after debridement.

Research included combat casualties treated at Walter Reed National Military Medical Center and civilian acute trauma patients treated at Grady Memorial Hospital in Atlanta, Georgia. Additional collaborators included the Naval Medical Research Center, Emory University, Duke University, Decision Q Corporation, and HJF. These partners supported patient enrollment, bioprocessing, biobanking, sample assays, data capture, and participated in analytical activities for the SC2i machine learning models.

“Digging deeper and understanding the mechanisms behind why a wound is going to fail or why a wound is going to successfully heal is really very important and is of great interest to me,” explains Schobel. “This type of research is important because it has the potential to impact patient care and help drive down costs.” 

WounDx™ combines information from biomarkers and data about extremity wounds sustained by combat casualties. This information is processed in a machine learning model, providing clinicians with guidance on whether wounds should be closed or left open. The device also assists clinicians in deciding the optimal timing for closure. Schobel elaborates, “By using WounDx™, we can collect a sample from the wound, run it through the diagnostic kit, and then combine all of that in the cloud using dedicated software and the machine learning model. From there, a report is output that lets us know, according to our model, if the wound should be closed or not.”

Diagram illustrating the Critical Injury Cycle. It depicts the process from immediate response to injury, through acute resuscitation, debridement & critical care, and regeneration medicine & rehabilitation, leading to return to duty. The diagram also includes a table of SC2i Clinical Decision Support Tools (CDSTs), categorized as In-Development and Deployed, listing various medical conditions and protocols. Stages of treatment such as assessing tissue viability, assessing systemic response, assessing bioburden, prophylaxis and therapy, timing of wound closure, timing of regenerative medicine, and treatment of complications are also shown within the cycle.
The process from immediate response to injury, through acute resuscitation, debridement &
critical care, and regeneration medicine & rehabilitation, leading to return to duty.
(Image courtesy of SC2i)

USU researchers developed WounDx™ to analyze an individual's wound healing immune response and compute a risk-of-failure score based on cytokine levels in the wound discharge. This is crucial because the molecular characteristics of a wound can be more indicative of readiness for closure than the current standard of care, which is visual inspection.

Wound dehiscence, or separation, occurs when a surgical wound fails to heal properly and the incision edges separate. This complication has been reported in 15%–30% of combat-related and civilian trauma wounds. Differentiating between wounds likely to proceed through normal versus delayed healing is essential to prevent worsening dehiscence, infection, and other complications. Therefore, a surgeon’s decision regarding the timing of closure for large, traumatic extremity wounds significantly impacts positive patient outcomes.

Wound dehiscence is defined as a loss of more than 10% of a skin graft, dehiscence of a primary closure requiring debridement, failure of a tissue flap requiring repeat surgery, or the need for subsequent amputation. Consequences include lengthy delays to definitive closure, increased pain, nutritional setbacks, higher costs, and potential further loss of function if amputation is needed. 

WounDx™ is expected to reduce wound dehiscence rates from 23% to 10%, potentially leading to substantial cost savings (around $60,000 per patient) and other benefits such as decreased pain, fewer complications, and better outcomes. Future research aims to improve patient care and reduce costs further by applying precision medicine to wound healing. Schobel explains that precision medicine uses patient-specific information to guide care for large extremity wounds, ensuring precise treatment based on an individual's biology. He notes the challenge of obtaining sufficient data for machine learning modeling, which requires continuous patient enrollment and significant resources.

“Traumatic wounds remain the leading cause of battlefield injury, as well as a significant problem in noncombat injuries,” says Elster. “By understanding the underlying biologic responses to injury, we have been able to develop this biomarker-based clinical decision support tool to increase our ability to provide definitive wound closure sooner than current approaches.”

With WounDx™, USU researchers and collaborators seek to improve care for the warfighter, reduce costs, shorten hospital stays, and accelerate recovery. Schobel remains enthusiastic about exploring and understanding the mechanisms behind the predictive model. Future research also aims to expand this application to surgical ICU patients by predicting severe systemic complications. Schobel finds gratification in scientific investigation. “I really like investigating scientific problems and trying to interpret data,” remarks Schobel. “It's gratifying to know that I might be the first person who realized something about a data set or a biological problem, and then was able to share those findings via publication that would aid in the care of the warfighter.”