Kokaraki Venetia
Struttura di afferenza: CLASSE STS


Venetia Kokaraki is a Marie-Curie early stage researcher in the frame of NEUROSOME project, an innovative training network funded by the Horizon 2020 and a PhD candidate of UME programme (Understanding and Managing Extremes) in IUSS – School for Advanced Study in Pavia, Italy. She graduated from the Department of Applied Mathematics at the University of Crete (Greece) in 2012. She enhanced her knowledge through her Master’s Degree in Operational Mathematics in Department of Mathematics and Applied Mathematics at the University of Crete in 2015. Being a member of the research team of the project ASMOPH, ‘Excellence I’ in Institute of Applied and Computational Mathematics (IACM), she was able to conduct her postgraduate dissertation entitled “Stochastics and Monte Carlo simulations for the description of time series of drug concentration in the blood of volunteers”. Furthermore, she had been working for almost three years as a researcher in the Laboratory of Toxicology and forensic Chemistry of University of Crete medical school, where several projects of statistical analysis and risk assessment were conducted.

My research project in NEUROSOME focuses on developing the proper modelling framework for estimating population external and internal exposure to xenobiotics, aiming to link external exposure metrics used in association studies to internal dosimetry metrics used in different toxicological testing strategies and identified omics signatures. The work will include the development of lifetime generic physiology-based biokinetic (PBBK) models for humans and animal models, able to describe internal exposure on susceptible developmental stages. Also the model will take into account interaction of multiple chemicals (mixtures interaction) at the level of metabolism, including enzyme inhibition and mechanism-based inhibition.

LinkedIn Profile: http://linkedin.com/in/veta-kokaraki-a23aa19b


Cumulative risk assessment of pesticide residues in different Iranian pistachio cultivars: Applying the source specific HQS and adversity specific HIA approaches in Real Life Risk Simulations (RLRS)