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Filippo Di Tillio
Leiden Univeristy

Filippo Di Tillio was born in Pescara (Italy) on the 19th of October 1996. With a lifelong passion for mathematics, he chose to explore this interest in his university studies. He obtained a bachelor's degree in mathematics from Università degli Studi dell’Aquila in Italy and later completed a double master’s degree in mathematics/applied mathematics, from Università degli Studi dell’Aquila and Karlstads Universitet in Sweden. His initial interest in biology transpired during his master's thesis, and he then decided to pursue said field in his Ph.D. career.

He is presently a Ph.D. candidate at Leiden University, conducting research under the guidance of Joost Beltman. His research involves the development of quantitative adverse outcome pathway (qAOP) models for various case studies. During the first year of his Ph.D. program, he focused on establishing a conceptual mathematical framework based on ordinary differential equations (ODEs) for qAOPs. Furthermore, he devised a method for mapping transcriptomics data into key event (KE) data, which can be employed for modeling purposes. At present, his research revolves around constructing a qAOP model for nephrotoxicity, based on in vitro cisplatin data.

Beyond his academic endeavors, he has a strong passion for music, with years of experience playing the bass guitar. He is equally enthusiastic about powerlifting and dedicates a significant portion of his time to lifting weights at the gym. He is actively learning the ropes of coaching in this field and may contemplate transforming this passion into a second career.

OpenTox 2023 Virtual Conference

Development of a gene expression-based quantitative AOP for nephrotoxicity 

Adverse Outcome Pathways (AOPs) represent a popular concept in toxicology that establishes a connection between a Molecular Initiating Event (MIE) and an Adverse Outcome (AO), defined as an apical endpoint at the tissue, organ, or population level, through various Key Events (KEs). Here, we focus on the development of a Quantitative AOP (qAOP) - a mathematical model that aims to define the quantitative relations between MIE, KEs, and AO - for nephrotoxicity. As a mathematical modeling framework, we chose to employ Ordinary Differential Equations (ODEs) because these naturally describe time-related events. We based this model on a previously developed AOP for cisplatin-induced kidney toxicity, describing the accumulation of cisplatin in cells (MIE) and its link to KEs such as "DNA Damage," "Oxidative Stress," "Inflammation," ultimately culminating in "Cell Death" (taken as AO). To develop the qAOP, we utilized time-course RNA-seq data for RPTEC/TERT1 cells exposed to cisplatin. We employed a mapping procedure based on various methods and tools, including co-regulated gene network analysis (implemented in-house as the 'TXG-MAPr'). In this approach, gene sets are defined through correlation analysis and then linked to KEs via enrichment analysis. A quantitative measure for each KE is derived from the gene expression change compared to baseline, weighted according to their Pearson correlation. Our qAOP describes the KE relations well and suggests that the KE 'Oxidative Stress' needs to be reconsidered as part of the AOP. Thus, our qAOP effectively discerns the mechanisms of cisplatin nephrotoxicity and offers the potential to improve in vitro-in vivo extrapolations and make predictions regarding other platinum-based compounds.