Personalising biologic therapy in psoriasis: Development, validation and user-testing of a precision dosing dashboard

Rising numbers of individuals receiving psoriasis biologics achieve clear/nearly clear skin (disease control). Trial data indicate some maintain control with lower doses, especially those with higher serum drug concentrations. This indicates potential for Model-Informed Precision Dosing (MIPD), an advanced therapeutic drug monitoring technique, in guiding dose minimisation. We developed, validated, and user-tested a precision dosing dashboard. We applied a MIPD approach leveraging Bayesian estimation to predict individual pharmacokinetic (PK) parameters for personalised dosing recommendations. A PK model of the exemplar biologic risankizumab, derived from phase I-III psoriasis trial data (13123 observations/1899 patients), was externally validated using real-world UK psoriasis data. The Bayesian model (posterior prediction: mean absolute error 0.89 mg/L; mean percentage error 19.55%; root mean square error 1.24 mg/L; R2 0.86) had superior predictive power to the basic PK model (prior prediction). The model was incorporated into an interactive dashboard, enabling input of individual patient data (serum drug concentrations, model covariates). UK healthcare professionals rated the dashboard user-friendly and acceptable. Mean time to generate a dosing interval was 2 minutes. Our dashboard has potential to incorporate other biologics and extend across disease contexts (non-response, other inflammatory diseases) for optimal real-world impact of precision dosing on health and cost outcomes.