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Biophysical and Biological Characterization of a New Line of Hyaluronan-based Dermal Fillers: A Scientific Rationale to Specific Clinical Indications

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Publisher Elsevier
Date 2016 Aug 16
PMID 27524055
Citations 29
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Abstract

Chemico-physical and biological characterization of hyaluronan-based dermal fillers is of key importance to differentiate between numerous available products and to optimize their use. These studies on fillers are nowadays perceived as a reliable approach to predict their performance in vivo. The object of this paper is a recent line of hyaluronic acid (HA)-based dermal fillers, Aliaxin®, available in different formulations that claim a complete facial restoration. The aim of the study is to provide biophysical and biological data that may support the clinical indications and allow to predict performance possibly with respect to similar available products. Aliaxin® formulations were tested for their content in soluble HA, water uptake capacity, rheological behavior, stability to enzymatic degradation, and for in vitro capacity to stimulate extracellular matrix components production. The formulations were found to contain a low amount of soluble HA and were equivalent to each other regarding insoluble hydrogel concentration. The different crosslinking degree declared by the producer was consistent with the trend in water uptake capacity, rigidity, viscosity. No significant differences in stability to enzymatic hydrolysis were found. In vitro experiments, using a full thickness skin model, showed an increase in collagen production in the dermoepidermal junction. Results support the claims of different clinical indications, the classification of products regarding hydro-, lift-action and the specifically suggested needle gauge for the delivery. The biological outcomes also support products effectiveness in skin structure restoration. These data predicted a better performance regarding hydro-action, tissue integration, clinical management during delivery, and a high durability of the aesthetic effect when compared to data on marketed similar products.

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