ir. Robin Michelet
Robin Michelet is doing research as a PhD student at the Laboratory for Medical Biochemistry and Clinical Analysis within the field of application-driven mathematical modelling to pre-clinical and clinical PK/PD research and its bio-analytical support.
Main research interest: Top-down (Population analysis), Bottom-up (Physiologically-based) and Middle-out modelling approach of pharmacokinetic and pharmacodynamic data.
During drug development testing and/or evaluation knowledge about the pharmacokinetics and pharmacodynamics (PK/PD) of the compound under study are of pivotal importance. These data are classically obtained using clinical trials on healthy adult volunteers or adult patients. It is known that the physiology of children is vastly different compared to adults and is not constant over time: children undergo growth and maturation. This phenomenon requires paediatric research in order to map the distinct PK and/or PD behaviour in paediatrics vs. adult. Since children are not small adults, adult data cannot be readily extrapolated to paediatric populations. To cope with this, paediatric clinical trials are necessary. However, due to the ethical and logistical constraints, these trials are hard, rare and yield less informative data. Other approaches are thus necessary.
A number of scaling techniques have surfaced in recent years in an attempt to predict the PK/PD in children, mainly divided in 2 categories: top-down scaling and mechanism-based bottom-up scaling. Top-down methods such as Population PK/PD modelling and simulation use adult PK data in combination with observable covariates such as bodyweight, age and creatinine clearance to account for the growth and development differences. Structural models are combined with stochastic models to obtain a mixed effects model, describing the PK/PD of a certain drug in a certain population. Bottom-up methods such as Physiologically-based pharmacokinetic (PBPK) modelling and simulation use a full knowledge of physiological, anatomical and biochemical ontogeny.
The importance of the technique of modelling is that if this would become reliable, clinical trial design would have enough data to fine tune the dosing calculation and thus could avoid unnecessary sampling and dosing regimens. In this research a combination of modelling tools, in vitro and in vivo generated data will be used to explore the PK/PD of the model drugs Propofol, Desmopressine, Ciprofloxacin and Lisinopril in paediatric populations. For this, in vitro transporter and metabolism assays will be carried out in conjunction with PBPK models to provide mechanistic insight into the ADME of the proposed model drugs. Additionally, population modelling will be applied to clinical trial data and compared to PBPK predictions for validation purposes. The combination of these two techniques will result in an optimisation of the knowledge gain and thus give paediatric (pre-) clinical research a boost.
This PhD is affiliated with Work Package 4 of the multidisciplinary SBO-IWT project SAFEPEDRUG (www.safepedrug.eu), which aims to reinvent the strategy for paediatric drug research based on top-down and bottom-up approaches. In this work package, modelling tools are applied to extrapolate in vitro data (bottom-up) and adult clinical data (top-down) to a paediatric setting.
Laboratory of Medical Biochemistry and Clinical Analysis (LMBKA), Department of Bio-analysis
Campus Heymans
Ghent University
Ottergemsesteenweg 460, B-9000 Ghent, Belgium
Tel +32 (0) 9 264 81 14
Fax +32 (0) 9 264 81 97
E-mail: robin.michelet@ugent.be