Application of pharmacometric methods to quantify the effects of methotrexate in rheumatoid arthritis

Abstract

Rheumatoid arthritis (RA) is a common inflammatory disease that affects between 0.5% and 1% of adults in developed countries. It is a chronic and progressive disorder that is characterised by systemic inflammation in joints, and may lead to reduced physical function in patients. Methotrexate (MTX) is the first-line treatment for RA, and is often given in low doses (i.e. 5-25 mg once per week) over a long term. Active polyglutamated metabolites of MTX (MTXPGs) also play a part in the therapeutic benefits of MTX. Some clinical studies, but not all, have found that MTXPGs in red blood cells (RBCs) are correlated with clinical response in RA. MTX when used alone or in combination is associated with effective disease control. Disease activity score in 28 joints (DAS28) is a commonly used and a validated measure of treatment response in patients with RA. In this thesis, the overall objective was to quantify the treatment effect of MTX in RA using pharmacometric methods. Among the RBC MTXPGs, it was uncertain which one or combination of polyglutamates were potential biomarkers of MTX treatment effect in RA, and the specific objectives included to: (1) determine the potential biomarkers of MTXPGs in RBCs based on the simulated drug activities, (2) quantify the relationship between the potential biomarkers and DAS28, (3) optimise blood sampling schedules of RBC MTXPGs for the future studies of MTX clinical response in RA, and (4) determine whether the MTX treatment effect could be delineated from other RA treatments under an observational study. In the specific objective (3), a pharmacokinetic (PK) model of MTX that was available for describing the disposition of MTXPGs in RBCs was simplified for the potential biomarkers, and the reduced model structure was used to determine optimal blood sampling schedules of MTX. In the model simplification example above, the states in the MTX PK model representing individual MTXPGs were manually lumped for the reduced model structure. This method could not be extended easily to simplify models with a larger number of states or larger scales. Methods to automate the simplification process were explored and developed using a large-scale physiologically based pharmacokinetic (PBPK) model of fentanyl that was identified from the literature. In conclusion, different clinical aspects relating to MTX treatment for RA were explored using pharmacometric methods; similar applications may be extended to other diseases and therapeutics. Automated model simplification processes were developed and may be extended to simplify general large-scale models.