Formulation by Design: Multiobjective Optimization of a Synergistic Essential Oil Blend with Bioactivities for Skin Healing Applications

Growing interest in natural therapies has increased the demand for essential oils; however, the complex interactions within their mixtures that dictate their final efficacy remain poorly understood. This study aimed to optimize a blend of ginger, cinnamon, tea tree, and geranium essential oils to develop an active ingredient, with synergistic multifunctional bioactivities, that was relevant to cutaneous healing. Initially, the composition and cytotoxicity for individual oils were determined; subsequently, a D-optimal mixture design was employed to evaluate three biological responses related to skin recovery: ultraviolet B radiation absorption, red blood cell lysis inhibition, and catalase enzyme activity. GC-FID analysis revealed the following major components (% w/w): cinnamon (cinnamaldehyde, 77.56%), ginger (α-zingiberene, 33.77%), geranium (citronellol, 33.6%), and tea tree (terpinen-4-ol, 38.38%). Dose–response data from essential oils tested against Detroit ATCC 551 skin fibroblasts revealed a clear cytotoxic hierarchy (IC50 µg/mL): cinnamon (21.03) > ginger (25.3) > tea tree (41.67) > geranium (92.51). Cinnamaldehyde content was the primary contributor to photoprotective capacity, with a maximum sun protection factor (SPF) of 4.5. Inhibition against erythrocyte membrane lysis was not attributable to a single component; maximum protection (98.4%) was achieved through synergy between oxygenated monoterpenoids (geranium and tea tree), sesquiterpenes (ginger), and aromatic aldehydes (cinnamon). Highest catalase activity (160.86 kU/g Hb) was reached in mixtures with high cinnamaldehyde and eugenol contents, whereas an antagonistic effect was observed between tea tree and geranium oils. Finally, an optimal formulation (desirability = 0.927) was identified (% w/w): 31.7% ginger, 39.1% cinnamon, 14.5% tea tree, and 14.7% geranium. Experimental validation confirmed no significant difference compared with developed predictive models. This optimized mixture constitutes a bioactive natural component with potential for use in products aimed at promoting skin health, warranting further investigation into direct models of skin healing.