Purpose (stating the main purposes and research question): Anthropogenic resource use contributes to pollution, violent conflict over scarce resources, loss of biodiversity, and diminished quality of life for humans. Moreover, the “safe” amount of carbon dioxide—350 parts per million—has been exceeded. The health care industry is responsible for 4–5% of total world emissions,[i] which is similar to the global food sector.[ii] Health care carbon emissions come from health care infrastructures, supply chains and health care delivery. Increasingly, health care delivery is reliant on technologies which require the use of artificial intelligence to provide supportive care, such as triage algorithms, electronic patient records, and robotics.[iii] While these technological innovations have advanced health care significantly, they also contribute to the negative effects on the environment, among others, through carbon emissions. The environmental impacts of artificial intelligence (AI) in health care—in particular—are understudied. This research seeks to fill this gap. Methods: Our team ran an exploratory search in Scopus and PubMed to identify studies that integrate environmental sustainability, artificial intelligence, and health. Results: Our research initially yielded 735 studies. 77 of these studies focused on an environmental concern of a health technology or AI-application in a health care setting, but most of the articles in this subset addressed lowering energy consumption of a specific technology, such as a sensor or monitoring technology. Conclusions: While there have been studies looking at AI in health care; sustainability in AI; and sustainability in health care, little attention has been paid to the interface between all three. [i] Karliner, J., Slotterback, S., Boyd, R., Ashby, B., & Steele, K. 2019. Health Care’s Climate Footprint: How the Health Sector Contributes to the Global Climate Crisis and Opportunities for Action Healthcare Without HarmARUP; September. [ii] Pichler, P. P., Jaccard, I. S., Weisz, U., & Weisz, H. 2019 International Comparison of Health Care Carbon Footprints, Environmental Research Letters 14, no. 6: 064004. [iii] Khaliq, Abdul, Ali Waqas, Qasim Ali Nisar, Shahbaz Haider, and Zunaina Asghar. 2022. Application of AI and robotics in hospitality sector: A resource gain and resource loss perspective. Technology in Society 68: 101807.

With the development of wearable technologies, the interfacial properties of skin and devices have become much more important. For research and development purposes, porcine skin is often used to evaluate device performance, but the differences between in vivo, in situ and ex vivo porcine skin mechanical properties can potentially misdirect investigators during the development of their technology. In this study, we investigated the significant changes to mechanical properties with and without perfusion (in vivo versus in vitro tissue). The device focus for this study was a skin-targeting Nanopatch vaccine microneedle device, employed to assess the variance to key skin engagement parameters – penetration depth and delivery efficiency – due to different tissue conditions. The patches were coated with fluorescent or ¹⁴C radiolabelled formulations for penetration depth and delivery efficiency quantification in vivo, and at time points up to 4 h post mortem. An immediate cessation of blood circulation saw mean microneedle penetration depth fell from ∼100 μm to ∼55 μm (∼45%). Stiffening of underlying tissues as a result of rigor mortis then augmented the penetration depths at the 4 h timepoint back to ∼100 μm, insignificantly different (p = 0.0595) when compared with in vivo. The highest delivery efficiency of formulation into the skin (dose measured in the skin excluding leftover dose on skin and patch surfaces) was also observed at this time point of ∼25%, up from ∼2% in vivo. Data obtained herein progresses medical device development, highlighting the need to consider the state and muscle tissues when evaluating prototypes on cadavers.

Skin-targeting microscale medical devices are becoming popular for therapeutic delivery and diagnosis. We used cryo-SEM, fluorescence lifetime imaging microscopy (FLIM), autofluorescence imaging microscopy and inflammatory response to study the puncturing and recovery of human skin ex vivo and in vivo after discretised puncturing by a microneedle array (Nanopatch®). Pores induced by the microprojections were found to close by ~25% in diameter within the first 30 min, and almost completely close by ~6 h. FLIM images of ex vivo viable epidermis showed a stable fluorescence lifetime for unpatched areas of ~1000 ps up to 24 h. Only the cells in the immediate puncture zones (in direct contact with projections) showed a reduction in the observed fluorescence lifetimes to between ~518–583 ps. The ratio of free-bound NAD(P)H (α1/α2) in unaffected areas of the viable epidermis was ~2.5–3.0, whereas the ratio at puncture holes was almost double at ~4.2–4.6. An exploratory pilot in vivo study also suggested similar closure rate with histamine administration to the forearms of human volunteers after Nanopatch® treatment, although a prolonged inflammation was observed with Tissue Viability Imaging. Overall, this work shows that the pores created by the microneedle-type medical device, Nanopatch®, are transient, with the skin recovering rapidly within 1–2 days in the epidermis after application.