BT34 Minimizing drug exposure in psoriasis using a therapeutic drug monitoring dashboard
Authors: Thomas Charlotte M , Standing Joseph F , Smith Catherine , Mahil Satveer K , Warren Richard B , Barker Jonathan , Norton Sam , Arkir Zehra , Tsakok Teresa , Arenas-Hernandez Monica 
Published: June 2024

Abstract
There are growing numbers of individuals with psoriasis who have clear or nearly clear skin (i.e. disease control) on high-cost biologic drugs. They currently continue biologic treatment indefinitely, resulting in a long-term drug and healthcare burden. Prior research indicates that some sustain disease control on less frequent doses than the current ‘one-size-fits-all’ standard dosing regimen, particularly those with higher serum drug concentrations. This indicates a role for therapeutic drug monitoring (TDM) in enabling personalized drug minimization strategies. We sought to develop a TDM dashboard, incorporating a pharmacokinetic (PK) model to deliver real-time predictions for informing personalized dosing decisions. We searched the PKPDAI and PubMed databases for models describing population pharmacokinetics of the exemplar psoriasis biologic risankizumab. The PK model was run using the MAPBAYR R package, incorporating serum drug concentrations as Bayesian priors. The model was validated using an independent real-world psoriasis dataset (n = 30, BSTOP study) by calculating the mean prediction error (MPE) and root-mean-square error (RMSE). Finally, the model was incorporated into a bespoke TDM dashboard, developed using open-source R Shiny software. We identified a two-compartment PK model with first-order absorption and elimination processes derived from pooled phase I–III risankizumab clinical trial data (13 123 observations from 1899 patients, 71% male, median age 47 years, median bodyweight 87 kg). The PK model was developed using a nonlinear mixed-effects modelling approach and accounted for interindividual variability in drug clearance, volume of distribution, absorption constant and bioavailability. Covariates incorporated into the model included body­weight and serum concentrations of anti-risankizumab antibody, albumin, creatinine, and high-sensitivity C-reactive protein. We validated the model using the independent real-world psoriasis dataset (MPE 0.74 mg L−1, RMSE 2.77 mg L−1) and incorporated it into a bespoke TDM dashboard (i.e. a real-time dosing interval calculator). The TDM dashboard is a user-friendly online interface that generates personalized dose interval recommendations following input of relevant variables (date of last dose, serum drug concentration, covariates and Psoriasis Area and Severity Index score) and a graphic of the PK profile. A randomized controlled feasibility trial (launch Q2 2024) will determine the patient and clinician acceptability and real-world practicality of TDM dashboard-informed biologics dosing. The dashboard enables proactive TDM, so that drug exposure can be minimized in individuals with psoriasis who have clear or nearly skin for ≥ 12 months on risankizumab. A pharmacodynamic turnover model is being developed to link to the PK model, with the potential to include other biologic drugs for optimal impact on overall drug exposure, healthcare burden and cost.