VANGELIS KARALIS

VANGELIS KARALIS

Dr. Vangelis Karalis is an Associate Professor of Clinical Pharmacy - Pharmacokinetics at the Department of Pharmacy, National and Kapodistrian University of Athens. He holds a degree in Pharmacy, an MSc in Clinical Pharmacy, and a PhD in Pharmacokinetics. His research interests span the application of data science in clinical and pharmaceutical research. Among others, his interests include artificial intelligence applications in clinical research, in silico clinical trials, modeling and simulation in drug research/development, and bioequivalence studies. Dr. Karalis possesses advanced computational skills, demonstrating proficiency in programming across various languages and the use of a wide range of software.
VANGELIS
KARALIS
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Department of Pharmacy, National and Kapodistrian University of Athens, University Campus, Athens, Greece
+30 210 72724267
- Karalis V (2024) Artificial intelligence in drug discovery and clinical practice, From Current to Future Trends in Pharmaceutical Technology, 215-255.
- Karalis V (2024) The Integration of Artificial Intelligence into Clinical Practice, Applied Biosciences 3 (1), 14-44.
- Karalis, V.D. On the Interplay between Machine Learning, Population Pharmacokinetics, and Bioequivalence to Introduce Average Slope as a New Measure for Absorption Rate (2023) Applied Sciences (Switzerland), 13 (4), art. no. 2257.
- Karalis, V.D. Machine Learning in Bioequivalence: Towards Identifying an Appropriate Measure of Absorption Rate (2023) Applied Sciences (Switzerland), 13 (1), art. no. 418.
- Karalis V. An In-Silico Approach Toward the Appropriate Absorption Rate Metric in Bioequivalence. Pharmaceuticals 2023, 16(5), 725.
- Soulele K, Karalis V. Development of a joint population pharmacokinetic model of ezetimibe and its conjugated metabolite. Eur J Pharm Sci. 128: 18-26 (2019)
- Soulele K, Karalis V. On the Population Pharmacokinetics and the Enterohepatic Recirculation of Total Ezetimibe. Xenobiotica. 27: 1-11 (2018)
- Karalis V. The Role of the Upper Sample Size Limit in Two-Stage Bioequivalence Designs. Int J Pharm. 456:87-94 (2013)
Pharmacometrics, In silico clinical studies, Modeling and Simulation, Machine learning, Pharmacokinetics, Clinical Pharmacokinetics, Bioequivalence studies, Clinical study design, Biostatistics, Clinical Pharmacy
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