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Updated: May 23, 2026

Generation of a Three-dimensional Full Thickness Skin Equivalent and Automated Wounding
Published on: February 26, 2015
Temporal In Vitro Models of Skin Wound Healing Components: A Cell-Specific Framework for Acute and Chronic Repair
Dipti Kalshetti1, Mahmud Amin1, Ridham Varsani1
1Department of Oral Biology, Surgery, and Biomedical Engineering, University at Buffalo, Buffalo, New York, USA.
Significance:
Wound healing is as much about opportunity (Gk. Karios) and sequence (Gk. Chronos). The sequential healing responses involve concerted responses of cells of various lineages along with both soluble (cytokines and growth factors) and insoluble (matrix composition and topology) that are precisely coordinated for ultimate healing. This motivated the current scoping review to examine the biological relevance and utility of current in vitro models of wound healing, focusing on specific cellular responses.
Recent Advances:
We examined PubMed, Web of Science, and EBSCO of Science for the years 2020-2025, using keywords in vitro wound healing and individual cell type, namely epithelial cells, keratinocytes, fibroblasts, macrophages, platelets, and endothelial cells. This identified 126 relevant studies were selected and categorized by healing stage, cell types, and prototypical biological responses such as proliferation, migration, and lineage-specific functions.
Critical Issues:
This analysis outlined the utility of a temporal framework to organize current in vitro models as acute-initial, early and late, and chronic-delayed. Existing two-dimensional and three-dimensional models focus on platelet function (hemostasis), neutrophil or macrophage chemotaxis and phagocytosis (inflammation), epithelium (closure), fibroblast (matrix synthesis, contraction), and endothelial (angiogenesis). While these models provide key insights into specific phases, cell functions, and molecular mechanisms, they do not fully replicate the integrated, multiorgan processes of wound healing observed in vivo.
Future Directions:
Sequential combinations of these models lend themselves to the advances in artificial intelligence, machine learning, and robotic automation that are integral to developing prognostic and therapeutic wound care agents.
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