Projects / Programmes
Advanced 3D cell models: Bridging the gap between in vitro and in vivo experimental systems (hep3DGenTox)
Code |
Science |
Field |
Subfield |
1.03.00 |
Natural sciences and mathematics |
Biology |
|
Code |
Science |
Field |
1.06 |
Natural Sciences |
Biological sciences |
3D in vitro cell model, genotoxicity, 3D scaffolds, spheroids
Data for the last 5 years (citations for the last 10 years) on
September 26, 2023;
A3 for period
2017-2021
Data for ARIS tenders (
04.04.2019 – Programme tender,
archive
)
Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
WoS |
530 |
17,095 |
14,989 |
28.28 |
Scopus |
581 |
19,475 |
17,099 |
29.43 |
Researchers (16)
no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
1. |
19116 |
PhD Špela Baebler |
Biotechnical sciences |
Researcher |
2020 - 2023 |
302 |
2. |
28476 |
PhD Nataša Drnovšek |
Engineering sciences and technologies |
Researcher |
2020 - 2023 |
87 |
3. |
09892 |
PhD Metka Filipič |
Natural sciences and mathematics |
Retired researcher |
2020 - 2023 |
584 |
4. |
56798 |
Katarina Fras |
|
Technical associate |
2022 - 2023 |
7 |
5. |
12688 |
PhD Kristina Gruden |
Biotechnical sciences |
Researcher |
2020 - 2023 |
954 |
6. |
26457 |
PhD Andraž Kocjan |
Engineering sciences and technologies |
Researcher |
2020 - 2023 |
288 |
7. |
29297 |
PhD Katja Kološa |
Natural sciences and mathematics |
Researcher |
2020 - 2023 |
35 |
8. |
34200 |
PhD Matjaž Novak |
Natural sciences and mathematics |
Researcher |
2022 - 2023 |
64 |
9. |
04292 |
PhD Saša Novak Krmpotič |
Engineering sciences and technologies |
Researcher |
2020 - 2023 |
658 |
10. |
39119 |
PhD Martina Štampar |
Natural sciences and mathematics |
Researcher |
2020 - 2021 |
79 |
11. |
32094 |
PhD Alja Štern |
Natural sciences and mathematics |
Researcher |
2020 - 2023 |
60 |
12. |
39320 |
PhD Maja Zagorščak |
Interdisciplinary research |
Researcher |
2020 - 2023 |
52 |
13. |
55689 |
Sonja Žabkar |
|
Technical associate |
2022 - 2023 |
10 |
14. |
20767 |
PhD Bojana Žegura |
Natural sciences and mathematics |
Head |
2020 - 2023 |
315 |
15. |
27522 |
PhD Anže Županič |
Engineering sciences and technologies |
Researcher |
2020 - 2023 |
169 |
16. |
15640 |
PhD Vera Župunski |
Natural sciences and mathematics |
Researcher |
2020 - 2023 |
172 |
Organisations (3)
Abstract
According to the current legislation genotoxicity testing is obligatory for new chemicals and products such as drugs, cosmetics, additives, pesticides etc. The international regulations for genotoxicity testing require in the first stage a battery of in vitro tests with bacteria and mammalian cells, and when positive results are obtained follow-up in vivo experiments are conducted. According to the proposed strategy of the EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) to “Avoid and Reduce Animal Use in Genotoxicity” can be achieved by enhancing the performance of the in vitro testing battery and by developing improved in vitro experimental models so that fewer in vivo follow-up studies are necessary. It has been estimated that approximately 80 % of in vitro genotoxicity tests in the EU are false positives and consequently, a high number of experimental animals is sacrificed, which could be avoided by more reliable in vitro test systems. An important reason for the false positive results obtained with current in vitro tests conducted in two-dimensional (2D) cell models is the lack of phase I and II metabolic enzymes that catalyse the activation and detoxification of genotoxins. Therefore it is essential to develop improved in vitro cell-based systems that will more realistically mimic the in vivo cell behaviours and will provide more predictive results to in vivo conditions. In this respect, three-dimensional (3D) cell cultures have gained increasing interest due to improved cell-cell and cell-matrix interactions and preserved complex in vivo cell phenotypes. Moreover, hepatic 3D cell models exhibit higher level of liver-specific functions including metabolic enzymes compared to 2D models. However, despite obvious advantages 3D systems have so far not been developed and validated for genotoxicity testing. Therefore the aim of hep3DGenTox project is to develop advanced physiologically more relevant human 3D in vitro cell models with improved hepatic characteristics and increased metabolic capacity. In the project we will develop spheroids from human hepatic cell lines under static (forced floating method) and dynamic (bioreactors) conditions as well as on bio-printed scaffolds prepared from various biocompatible materials. The most promising newly developed 3D in vitro models will be characterised (cell growth, expression of metabolic phase I and II enzymes at gene and protein level etc) and validated for genotoxicity testing using chemicals from the ECVAM list developed by an expert group working on the validation of new in vitro genotoxicity tests. We expect that more reliable results (i.e. less false positives) will be obtained with the newly developed hepatic 3D cell models. Because of this their use in genotoxicity testing will contribute substantially to the reduction of the use of laboratory rodents and to a more reliable safety evaluation of chemicals and products that is needed for efficient human health protection. Furthermore the advanced 3D in vitro cell models will be useful for acute and chronic toxicity studies. The innovative and ambitious project will be realized in the frame of a collaboration of Slovenian scientists from the National Institute of Biology, from the Institute Jozef Stefan and Faculty of Chemistry and Chemical Technology, University of Ljubljana with the collaboration with foreign experts from University of Southern Denmark and CelVivo, biotech company from Denmark, University of Lisbon, Portugal and Medical University of Vienna, Austria through their complementary expertise in the fields of 3D in vitro models, genetic toxicology, molecular biology, and “omics” technologies. We believe that newly developed hepatic 3D cell models will represent promising tool for generating more predictive genotoxicity data for human exposure to various compounds as well as accelerating preclinical development of new drugs with a better safety and efficacy profile and will bridge the gap