PhD defence
Computational toxicology and engineered nanomaterials: Using machine learning to predict adverse effects
- S. Balraadjsing
- Date
- Tuesday 13 October 2026
- Time
- Location
-
Academy Building
Rapenburg 73
2311 GJ Leiden
Supervisor(s)
Summary
Nanomaterials are increasingly used in everyday products and modern technologies. Because these extremely small particles can eventually enter rivers, lakes and oceans, it is important to understand their effects on aquatic life. However, there are many different types of nanomaterials, each with potentially different effects, and testing them all on animals is costly, time-consuming and raises ethical concerns.
This PhD thesis investigated whether computer models can help predict the harmful effects of metallic nanomaterials on aquatic organisms. To do this, existing scientific data were collected and used to develop machine learning models to predict toxicity. The models were able to make reliable predictions, even when relatively limited amounts of data were available. At the same time, the research identified important limitations of these models and showed that their reliability depends strongly on the quality of the underlying data. The research also revealed that smaller aquatic organisms are generally more sensitive to metallic nanomaterials than larger organisms.
These findings demonstrate that computer-based approaches can be a valuable complement to traditional toxicity testing. They can help assess environmental risks more efficiently and identify which experiments are most useful or necessary. In this way, computational methods may contribute to reducing the number of animals used in scientific research. Overall, this research shows how combining scientific data, machine learning and an understanding of differences between aquatic organisms can support more efficient and sustainable environmental risk assessment.
PhD dissertations
Approximately one week after the defence, PhD dissertations by Leiden PhD students are available digitally through the Leiden Repository, that offers free access to these PhD dissertations. Please note that in some cases a dissertation may be under embargo temporarily and access to its full-text version will only be granted later.
Press enquiries (journalists only)
+31 (0)71 527 1521
nieuws@leidenuniv.nl
General information
Beadle's Office
pedel@bb.leidenuniv.nl
+31 71 527 7211