Toward a Closed Loop, Integrated Biocompatible Biopolymer Wound Dressing Patch for Detection and Prevention of Chronic Wound Infections

Abstract

Chronic wound infections represent a significant burden to healthcare providers globally. Often, chronic wound healing is impeded by the presence of infection within the wound or wound bed. This can result in an increased healing time, healthcare cost and poor patient outcomes. Thus, there is a need for dressings that help the wound heal, in combination with early detection of wound infections to support prompt treatment. In this study, we demonstrate a novel, biocompatible wound dressing material, based on Polyhydroxyalkanoates, doped with graphene platelets, which can be used as an electrochemical sensing substrate for the detection of a common wound pathogen, Pseudomonas aeruginosa . Through the detection of the redox active secondary metabolite, pyocyanin, we demonstrate that a dressing can be produced that will detect the presence of pyocyanin across clinically relevant concentrations. Furthermore, we show that this sensor can be used to identify the presence of pyocyanin in a culture of P. aeruginosa . Overall, the sensor substrate presented in this paper represents the first step toward a new dressing with the capacity to promote wound healing, detect the presence of infection and release antimicrobial drugs, on demand, to optimized healing.

Soft Bioelectronics for Therapeutics

“…Integrated with AI technologies, intelligent closed-loop systems can improve diagnostic and therapeutic accuracy by accelerating the decision-making process, which provides an unconventional therapeutic paradigm for disease management . For example, Ward et al reported a closed-loop wound dressing patch, which comprised a pyocyanin sensor, artificial neural network-assisted antibiotics toxicity prediction platform, and controllable dosing modules . Through a series of tests, the sensor can be used to detect pyocyanin and release antimicrobial drugs on demand to realize optimized healing.…”

“…294 For example, Ward et al reported a closed-loop wound dressing patch, which comprised a pyocyanin sensor, artificial neural network-assisted antibiotics toxicity prediction platform, and controllable dosing modules. 295 Through a series of tests, the sensor can be used to detect pyocyanin and release antimicrobial drugs on demand to realize optimized healing. However, some challenges still remain.…”

Biomaterial strategies to combat implant infections: new perspectives to old challenges

“…In a recent review, Lv et al analysed the use of different machine-learning algorithms, like naive Bayes (NB), decision trees (DT), random forests (RF), support vector machines (SVM), and artificial neural networks (ANN), in terms of their usefulness for designing new antibiotics or synergistic drug combinations towards AMR [383]. In another recent work, Ward et al analysed the use of a neural network-based feedback control system to regulate the release of critical dosage of Ag-ions from PHA-graphene nanocomposites for chronic wound treatment [384]. In particular, the predictive capability of such algorithms to determine the timeline and amount of antimicrobial agents to induce toxic effect against P. aeruginosa in a wound bed was briefly analysed.…”

Wearable Bioelectronics for Chronic Wound Management

“…They developed a closed loop wound patch integrated with a PYO sensor, ANN-assisted antibiotics toxicity prediction, and controllable dosing modules. [189] A series of studies in AI algorithms such as prediction of sepsis, hospital-acquired infections, and antibiotics resistance were also conducted, which could be useful for chronic wound care. [186,190] In summary, AI provides data-driven approaches to facilitate wound management.…”