Pancreatic ductal adenocarcinoma (PDAC) is the most intractable solid cancer with a 5-year survival below 8%. More than 80% of patients with PDAC are diagnosed with an unresectable tumor and are therefore not eligible for surgery. PDAC cells reprogram their metabolism to survive in their harsh hypoxic and nutrient deprived microenvironment, and this metabolic shift favors the survival of the most aggressive cells and their dissemination at distant sites. The metabolic changes associated with the metastatic progression of the PDAC remain crucial opened-questions.

Numerous observations show that the cellular metabolism, the mechanism of the circadian clock and cell cycle are three processes that interact in the normal cells. It is suspected that the cross influences between these processes are modified in tumor cells but we don't know how. Understanding this complex network is therefore an important issue both fundamentally and biomedically. The objective of this project is to build a mathematical formal model of cellular metabolism capable of taking into account temporal fluctuations of metabolites (ATP, glucose, NAD+) and cellular models allowing real-time and single-cell analysis of major metabolic pathway activity (AMPK, AKT/PI3K, redox NADH/NAD+).

The general objective of HyClock project is (i) to offer the proof of principle that hybrid modelling outperforms classical formal methods for studying the properties of the mammalian CTS and (ii) to apply this approach to better understand the circadian clock-cell cycle-cancer connection and their impact on cancer chronopharamcology and chronotherapeutics.

The HyClock project gathers a multidisciplinary team of experts in computer sciences, mathematical modelling, chronobiology and chronopharmacology to develop novel formal methods and hybrid modelling frameworks and to apply them to the analysis and understanding of the mammalian circadian clock. Our goal is to perform a sufficient number of abstractions in order to be able to exhaustively identify the possible parameter values, using computer aided formal reasoning while preserving a good quality of the model, in such a way that the abstractions do not damage its predictive capacity. This novel modelling strategy will be first used to predict and analyse how the coupled circadian clock-cell cycle network responds to physiological synchronisation in healthy cells with consequences on proliferation. Second, we will investigate in vivo using experimental design guided by these hybrid models how we can reinforce CTS coordination of the host through synchronisation, in order to improve the tolerability to treatments using the widely used anticancer targeted agent everolimus (mTOR inhibitor) and cytostatic chemotherapeutic agent irinotecan as model drugs.

This project starts from the observation that existing modeling frameworks for biological systems are relatively poor for handling time information. The goal is here to combine 3 complement current approaches (static models, time series models and chronometric models) in order to provide a wider framework for the interpretation of biological data.

The goal of this project is the modeling of the circadian clock in humans taking into account time information. The initial idea is based on the observation that the time information is generally underused because it does not yet exist modeling framework that can handle it correctly.

Construction of the necessary constraints for a discrete model of a genetic network to be compatible with a known experimental trace.