Springe direkt zu Inhalt

Davide Bindellini

Bild: Davide Bindellini

Institute of Pharmacy

Clinical Pharmacy & Biochemistry

Freie Universität Berlin

Address
Kelchstr. 31
12169 Berlin
Email
davide.bindellini[at]fu-berlin.de

Curriculum Vitae

since 05/2021

PhD student at the Graduate Research Training Program “PharMetrX: Pharmacometrics & Computational Disease Modelling“ at the Dept. of Clinical Pharmacy & Biochemistry supervised by Prof. Dr. Charlotte Kloft at the Freie Universitaet Berlin.

09/2018-01/2021   

M.Sc. Biomedical Sciences at Leiden University, the Netherlands; 6-months junior research project at Leiden University Medical Center (LUMC), Leiden; 8-months master thesis internship at Leiden Academic Centre for Drug Research (LACDR), Leiden.

10/2014-12/2017 

 B.Sc. Pharmaceutical Biotechnology at Università degli studi di Milano, Italy; Erasmus semester at Leiden University, the Netherlands.


Pharmacometrics of special populations - paediatrics and obese patients

 

In drug therapy, special patient populations, such as paediatric and obese patients, often demonstrate differences in pharmacokinetic(s) (PK) and pharmacodynamic(s) (PD) compared to healthy adults, the population in which most clinical PK/PD studies are conducted. Therefore, the standard treatment options might not prove safe and efficacious in individuals belonging to special patient populations. My dissertation project will primarily focus on evaluating therapy optimisation of (i) hormonal replacement therapy in paediatric patients affected by congenital adrenal insufficiency (CAH), and (ii) antiinfective therapy in (morbidly) obese patients.

CAH is caused by a deficiency of the steroid enzyme 21-hydroxylase, which is involved in the cortisol biosynthesis pathway. The lack of this enzyme also affects the production of other hormones, such as sex hormones and mineralocorticoids causing symptoms as virilisation, hirsutism, premature pseudo puberty, prematurely ended longitudinal growth and electrolyte imbalance. Hydrocortisone is used as replacement therapy in CAH; when designing such therapy, it is essential to account for cortisol´s complex PK (e.g. circadian rhythm) and its impact on PD. In fact, too high and too low cortisol concentrations can cause Cushing´s syndrome and worsen disease progression, respectively.

The impact of obesity on antibiotic PK and PD is still understudied and sometimes contradicting results have been reported. In order to guarantee safe and effective antibiotic treatment for obese and nonobese patients, it is essential to take into account information regarding the antibiotic, the pathogen, and the patient by relating individual antibiotic exposure to pathogen-specific exposure targets. Additionally, it is important to evaluate if drug penetration to the target site differs between (morbidly) obese and nonobese patients in order to appropriately optimise treatment. In this case the evaluated target-site is the interstitial space fluid of the adipose tissue, in which the antibiotic concentration can be measured by the minimally invasive method microdialysis.

As it can be complicated to collect PK/PD data in these special patient populations, pharmacometric modelling and simulation can be used to study these populations and evaluate dosing regimen adjustment to optimise their treatments. In particular, nonlinear mixed-effects modelling allows to deal with sparse data, which is often the case with special populations. Concerning model development, in a first step the population specific concentration-time profile and the different levels of variability between and within patients will be characterised. In a second step, patient specific covariates (e.g. markers of organ function or disease status) will be identified, which explain inter- and intraindividual variability and their impact on model parameters will be quantified. Additionally, more complex mechanistic models which also leverage literature data, such as quantitative systems pharmacology models, will be developed and evaluated. Lastly, by exploiting the developed models, therapy optimisation can be assessed for these populations.

Concerning hormone replacement therapy in paediatric patients, my objective is to expand existing models by leveraging additional already available PK data and PD data from further clinical studies, improving hydrocortisone exposure prediction to provide a better overall therapy evaluation. Similarly, for the obese population, PK data from a large clinical study including plasma and target-site concentrations for several antibiotics will be exploited to develop PK models. Finally, for both populations, using the developed models for simulations will allow to evaluate therapy optimisation and whether dosing adjustments are needed.