< Back to previous page

Project

Pharmacometric models for improved therapeutic drug monitoring of ceftriaxone, posaconazole and infliximab

 In clinical drug development, “one dose fits all” is a key objective. However, variability in exposure (E) and response (R) is common and can result in suboptimal treatment of individual patients. To hit a predefined E/R target in each patient, “therapeutic drug monitoring” or TDM is often implemented. TDM helps improving attainment of a desired E/R target by guiding individualised drug dosing based upon drug concentrations. “Population models” can be employed to further maximise the success of TDM. These models are increasingly used in drug development as they provide a quantitative description of the time course of drug disposition and effects, but more than describing existing data, these models can be applied to predict what will happen in the future and dosing can be adapted accordingly. The dictum of “one dose fits all” has been shown problematic in severely ill patients. Particular pathophysiological situations in these patients often result in underexposure, making it difficult to properly handle diseases using standard dosing. Using data from clinical trials, the applicant will develop population models and implement these in a TDM software tool to investigate improved outcomes of - critically ill patients with overwhelming community acquired pneumonia on ceftriaxone therapy; - critically ill patients with influenza on posaconazole prophylaxis to prevent invasive aspergillosis; - patients with acute severe ulcerative colitis receiving infliximab induction therapy.
 

Date:1 Oct 2019 →  30 Sep 2022
Keywords:Pharmacometrics, Therapeutic drug monitoring, Personalised medicine, Computer-assisted dose finding, Pharmacokinetics-pharmacodynamics
Disciplines:Computational biomodelling and machine learning, Gastro-enterology, Infectious diseases, Pharmacokinetics, Clinical pharmacy