Ivana Adamov, M. Pharm.
Position: Teaching Assistant
Organizational unit: Department of Pharmaceutical Technology and Cosmetology
Room: B 300b
Phone: +381 11 3951 356
Email: ivana.adamov@pharmacy.bg.ac.rs
Ivana Adamov was born on February 19, 1994 in Zrenjanin, where she graduated from the Medical High School (pharmaceutical technician), as a holder of the diploma "Vuk Karadžić". She enrolled at the Faculty of Pharmacy in Belgrade in the 2013/2014 school year and graduated in 2019 with an average grade of 9.58. In the school year 2020/2021, she started PhD studies at the Faculty of Pharmacy, University of Belgrade (accredited program in 2020) with a focus on the scientific field of Pharmaceutical Technology. During the 2019/2020 school year, she attended specialist academic studies in Industrial Pharmacy and passed all exams provided by the SAS curriculum with an average grade of 10. Ivana was engaged as a teaching associate at the Department of Pharmaceutical Technology and Cosmetology, where she participated in the realization of practical classes within the compulsory subjects Pharmaceutical Technology 2, Pharmaceutical Technology 3, Industrial Pharmacy and the elective subject Dosage Forms for Pediatric Population. In November 2020, she was elected a researcher, and since February 2022 she has been employed as an assistant at the Department of Pharmaceutical Technology and Cosmetology. Ivana's research activity is based on the formulation and characterization of pharmaceutical drug dosage forms manufactured by innovative technologies in the field of 3D printing of pharmaceutics. Fluent in English.
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Adamov I, Stanojević G, Medarević D, Ivković B, Kočović D, Mirković D, Ibrić S. Formulation and characterization of immediate-release oral dosage forms with zolpidem tartrate fabricated by digital light processing (DLP) 3D printing technique. Int J Pharm. 2022; 624:122046.
- Stanojević G, Medarević D, Adamov I, Pešić N, Kovačević J, Ibrić S. Tailoring Atomoxetine Release Rate from DLP 3D-Printed Tablets Using Artificial Neural Networks: Influence of Tablet Thickness and Drug Loading. Molecules. 2020; 26(1).