Abstract

Underdosing of adalimumab can result in non-response and poor disease control in patients with rheumatic disease or inflammatory bowel disease. In this pilot study we aimed to predict adalimumab concentrations with population pharmacokinetic model-based Bayesian forecasting early in therapy. Adalimumab pharmacokinetic models were identified with a literature search. A fit-for-purpose evaluation of the model was performed for rheumatologic and inflammatory bowel disease (IBD) patients with adalimumab peak (first dose) and trough samples (first and seventh dose) obtained by a volumetric absorptive microsampling technique. Steady state adalimumab concentrations were predicted after the first adalimumab administration. Predictive performance was calculated with mean prediction error (MPE) and normalised root mean square error (RMSE). Thirty-six patients (22 rheumatologic and 14 IBD) were analysed in our study. After stratification for absence of anti-adalimumab antibodies, the calculated MPE was -2.6% and normalised RMSE 24.0%. Concordance between predicted and measured adalimumab serum concentrations falling within or outside the therapeutic window was 75%. Three patients (8.3%) developed detectable concentrations of anti-adalimumab antibodies. This prospective study demonstrates that adalimumab concentrations at steady state can be predicted from early samples during the induction phase. The trial was registered in the Netherlands Trial Register with trial registry number NTR 7692 ( www.trialregister.nl ).

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