Commentary finds predictive models and biomarkers improve safety in aesthetic dermatology, suggesting AI can optimize treatment protocols.
As aesthetic dermatology integrates increasingly advanced injectable and energy-based interventions, the need for biologically informed decision-making becomes critical. Complications such as granulomas, fibrosis, and post-inflammatory hyperpigmentation (PIH) still affect subsets of patients due to interindividual biological variability. This commentary explores the dual role of biomarkers (measurable indicators of process, risk, or response) and hallmarks (phenotypic patterns summarizing underlying biology) in identifying patients at risk of complications, offering real-world applications such as tape stripping to evaluate our molecular patient profile. The potential of artificial intelligence (AI) to interpret complex biological signatures is discussed, along with broader implications for long-term personalization in cosmetic care. By aligning treatment protocols with skin biology, aesthetic dermatology would shift toward a predictive and preventive model, ensuring safety, precision, and durable results.
No takes yet. Share an insight, caveat, or question.
Haykal et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: