An active area of research in pharmacology and drug discovery applies to functional selectivity (or biased agonism, biased signaling): the ability of a ligand to selectively activate some signal transduction pathways as compared to the native ligand acting at the same receptor. At the theoretical level, biased signaling is supported by the concept of conformational selectivity: a given receptor may adopt several conformations, that can be stabilized by its interaction with a ligand, and each of these conformations potentially activates the downstream signaling pathways with different efficacies. At the practical level, experimentalists seek to quantify ligand bias in order to classify ligands according to their selectivity. One popular method uses the so-called operational model to fit dose-response curves. In this presentation, I will review the main limitations of this methodology, recently pointed out by our group and others. Our objective is then to design a method that fully take into account the kinetic nature of signaling pathways and as well as their possible cross-talks. Kinetic experiments, that measure the activity of several downstream effectors of a receptor after ligand binding with respect to time, are now widely available. I will explain how one can exploit such data and dynamical reaction network modeling with suitable statistical framework to provide a complete “bias map” of a ligand, compared to the native ligand, that successfully answer to our objective. Going further, we can extend this methodology to take into account recently discovered compartmentalised signaling, which can eventually lead to spatial or location signaling bias. We have thus build a dynamical model that incorporate endocytosis/recycling event and spatial specificity, helping to quantify kinetic experiments under various receptor trafficking perturbations. The methodology is illustrated with kinetic BRET measurements of effectors of the Follicle Stimulation Hormone Receptor (FSHR), stimulated by either the Follicle Stimulation Hormone (FSH) or low molecular weight allosteric ligands. References: Claire Alamichel, Juan Calvo, Erwan Hingant, Saoussen Latrach, Nathan Quiblier and Romain. Yvinec. Modeling compartmentalization within intracellular signaling pathway. 2024. ⟨hal-04098543v2⟩ Francesco de Pascali, Mohammed Akli Ayoub, ..., Romain Yvinec and Eric Reiter. Pharmacological characterization of low molecular weight biased agonists at the follicle stimulating hormone receptor. International Journal of Molecular Sciences, 2021, 22 (18), pp.1-23. ⟨10.3390/ijms22189850⟩. ⟨hal-03351267⟩