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Evolutionary Life-cycles in Skin Replacement Technologies

Climov M1,2, Panayi AC2, Borah G1, Orgill DP2 Affiliations: 1. Plastic Surgery Division, Department of Surgery, Ruby Memorial Hospital, West Virginia University, Morgantown, WV 2.Tissue Engineering and Wound Healing Laboratory, Plastic Surgery Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
Plastic Surgery Program, Department of Surgery, Ruby Memorial Hospital, West Virginia University, Mo
2018-01-30

Presenter: Mihail Climov

Affidavit:
" I concur that Mihail made the designated contributions to this project"

Director Name: Aaron Mason

Author Category: Resident Plastic Surgery
Presentation Category: Basic Science Research
Abstract Category: General Reconstruction

Introduction: Skin Replacement Technologies (SRTs) emerged as skin alternatives for burns, large excisions or trauma. The number of original publications represents the available knowledge on a subject and can be modeled as a logistic S-curve which depicts the technology's evolution life-cycle. The Technology Innovation Maturation Evaluation (TIME) model is used to study the life-cycle of biotechnologies.

Methods: PubMed and other databases were searched 1900-2015 to review pertinent publications. All skin replacement or regeneration products on the US market were included. The TIME model was applied to assess evolutionary patterns for each technology.

Results and Discussion: Three SRT clusters were identified: processed biologics technologies (PBT), extracellular matrix technologies (EMT), and cell-based technologies (CBT). Publications on EMTs and CBTs start decades after PBTs, however are greater in number and follow an ascending trend. PBTs reached a plateau, suggesting near-senescence. The CBT curve was non-logarithmic and the TIME model could not be applied. The technology initiation point (Ti) for PBTs was 1939 and the establishment point (Te) 1992. For EMT, Ti was 1966 and Te 2010. 61 products were identified (49 EMTs, 7 CBTs, 5 PBTs). PBTs appeared 11 years before Te and EMTs four years after Te.

Conclusion: Innovation is an indicator of the evolution of a technology, which indirectly demonstrates that SRTs are an innovation-based industry. EMT has the most products and is the most efficient cluster. Successful technology in SRT should be designed as an innovative platform that is simple, cost-efficient, easily regulated and clinically efficient.

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