In Silico Clinical Studies on the Efficacy of Blue Light for Treating Psoriasis in Virtual Patients

Abstract

Background: Treatment of psoriasis with blue light reduces the symptoms of this skin condition. Despite the therapeutic effects of blue light, no clear guidelines have been established regarding the irradiation settings. We have previously developed a computational model that enables the study of the impact of the irradiation parameters on the efficacy of this therapeutic approach. This model reproduces the clinically observed response of the average psoriasis patient to irradiation with blue light, but it does not capture the interpatient variations. The inclusion of the interpatient dissimilarities in the model would provide insight into the variability in treatment efficacy among patients. Methods: In this study, a set of ∼500,000 virtual patients (VPs) that captures the variability in the clinical investigations is generated based on data from two clinical studies and the previously developed model for blue light irradiation of psoriatic skin. First, the minimum number of VPs needed to obtain the same change from baseline (cfb) distribution as in the clinical studies is defined and analyzed. Then, these VPs are used in a series of in silico clinical investigations that explore whether the treatment response of psoriasis patients can be improved by modifying the settings of the therapeutic protocol. Results: The results suggest that a minimum of 2500 VPs are required to reproduce the cfb distribution observed in vivo. The results from the simulations performed with the VPs predict that the treatment efficacy can be increased for all patients by implementing a therapeutic protocol with daily treatment, and a higher fluence and length of treatment than the currently used settings. These results also suggest that there is no additional benefit to increasing fluence >200 J/cm2. Conclusion: This study demonstrates the potential role of in silico clinical studies in the field of dermatology.