Personalizing Biologic Therapy in Psoriasis: Development, Validation, and User Testing of a Precision-Dosing...

Area of Science:

• Pharmacology
• Immunology
• Biotechnology

Background:

• Many patients receiving biologic therapy for psoriasis achieve disease control.
• Some patients can maintain disease control with reduced biologic doses, particularly those with higher serum drug concentrations.
• This suggests potential for model-informed precision dosing to guide dose minimization strategies.

Purpose of the Study:

• To develop, validate, and user-test a precision dosing dashboard for optimizing biologic therapy in psoriasis.
• To apply a model-informed precision dosing approach using Bayesian estimation for personalized dosing recommendations.
• To assess the predictive power of a pharmacokinetic model and the usability of the developed dashboard.

Main Methods:

• Developed a pharmacokinetic model for risankizumab using Phase I-III psoriasis trial data.
• Externally validated the model using real-world UK patient data.
• Incorporated the validated model into an interactive dashboard for personalized dosing recommendations via Bayesian estimation.
• Conducted user testing with UK healthcare professionals.

Main Results:

• The Bayesian pharmacokinetic model demonstrated superior predictive power compared to a basic model (posterior prediction R² = 0.86).
• The developed dashboard was rated as user-friendly and acceptable by healthcare professionals.
• The average time to generate a dosing interval using the dashboard was 2 minutes.

Conclusions:

• Model-informed precision dosing, facilitated by the developed dashboard, shows promise for optimizing biologic therapy in psoriasis.
• The dashboard enables efficient, personalized dosing recommendations, potentially improving health and cost outcomes.
• The approach has potential for broader application across different biologics and inflammatory diseases.