Pharmacokinetic-pharmacodynamic modelling of risankizumab using chronic plaque psoriasis real-world data
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Thomas, Charlotte M.
Wei, Jessica Ruoheng
Baudry, David
Arkir, Zehra
Coker, Bola
Dasandi, Tejus
Powell, Kingsley
Arenas-Hernandez, Monica
Leung, Jenny
Rawstron, Krystal
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2026
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AIM: Risankizumab is a high-cost biologic treatment for chronic plaque psoriasis, an immune-mediated inflammatory disease presenting with painful red scaly skin lesions. Inter-individual heterogeneity in treatment response may be better addressed with personalised rather than fixed dosing. We sought to develop a pharmacokinetic/pharmacodynamic (PK/PD) model to characterise the relationship between risankizumab exposure and treatment response. METHODS: A sequential population PK/PD model was developed using real-world data (UK Biomarkers of Systemic Treatment Outcomes in Psoriasis study) comprising serial PK and Psoriasis Area and Severity Index (PASI) measures. Models were built using R (V4.3.1) and nlmixr2 (V2.1.1.9). One and two-compartment PK models were tested. A maximal effect turnover model was used to describe PASI, with drug effect on lesion development rate (K(in)). RESULTS: The dataset (82 serum risankizumab concentrations; 101 PASI observations) comprised 50 patients with psoriasis (median weight 79.3 kg; age 47 years). PK data were described by a one-compartment model with first-order absorption/elimination. Absorption rate (K(a)) was fixed from the literature (0.229). Estimated clearance was 0.34 L/day, and volume of distribution 12.9 L. Baseline PASI at model initiation, drug potency (EC(50)) and lesion recovery rate (K(out)) were estimated at 23.4, 0.11 mg/L and 0.05 day(-1), respectively. CONCLUSIONS: Pharmacokinetic parameters were similar to risankizumab clinical trials. K(out) estimates aligned with other psoriasis turnover models, highlighting the capture of disease dynamics that may be applied across drugs. This model may inform personalised dosing based on individual patient characteristics, drug exposure and response, to optimise treatment outcomes.
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British journal of clinical pharmacology