Chronic inflammatory bowel disease is characterized by long-term inflammation of the intestine that lasts for a lifetime. We distinguish two types of disease: Crohn's disease and ulcerative colitis. When we cannot distinguish between the two types of disease, we talk about indeterminate colitis. For more severe forms of the disease, biologics have been used recently. One of them is also infliximab. Despite successful treatment with biologics, only these have quite a few side effects (eg infections, allergic reactions, etc.). The effectiveness of therapy depends on the concentration of the active substance in the blood, as well as the occurrence of side effects, so the optimization of dosing regimens for patients is crucial.
The purpose of the master's thesis is to collect and edit data on the treatment of chronic inflammatory bowel disease at the Clinical Department of Gastroenterology, University Medical Center Ljubljana and use them to evaluate literature population pharmacokinetic models for infliximab. Among the published models, we want to select the most appropriate to describe the pharmacokinetics of infliximab in a group of patients with IBD who were treated with infiximab at the University Medical Center Ljubljana between 2017 and 2020.
We collected data on 172 patients who were treated with infliximab for chronic inflammatory bowel disease at the Gastroenterology Clinic in Ljubljana in the selected observation period. Data were collected on patient type, date of birth, sex, current infliximab therapy, prior biologic therapy, concomitant systemic corticosteroids or thiopurines, C-reactive protein and calprotectin measurements, Harvey-Bradshaw index and Mayo infusions, infliximab during the observation period, body weight on the day of infusion, and measurements of infliximab blood levels. Data were edited and prepared for analysis by nonlinear modeling of mixed effects. We sought available literature population pharmacokinetic models for infliximab, in patients with chronic inflammatory bowel disease. We found 23 models collected in one article. We selected two of them and evaluated them based on our data. We found that both models describe the collected data quite well, but for further work the data will need to be adjusted in more detail, as in this analysis we took into account the date and time of the analysis instead of the actual time of collection. These two times may differ in some patients, which may partly explain the poorer agreement in our analysis than in the models in the literature.
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