Virtual webinars will be delivered to keep the interaction between the network and to allow collaboration to continue during the coronavirus outbreak. Beneficiaries, partner organisations and ESRs will deliver webinars, and this will be to present results, deliver training, discuss a research paper, etc. The sessions will be recorded so that participants who cannot attend can still take part, and slides will also be made available. Microsoft Teams will be used for the webinars.
The first QuanTII webinar took place on 20 May 2020 – it was delivered by Paolo Vicini from Kymab (P7), and was well attended by network members.
Title: Systems Pharmacology and Pharmacometrics: How Mathematics, Statistics and Data Science Are Impacting Drug Discovery and Development
Abstract: Modern drug discovery and development are rapidly becoming more reliant on rigorously quantitative approaches. In addition to established statistical testing and experimental design techniques, new approaches include pharmacometrics and systems pharmacology. Pharmacometrics is a collection of quantitative tools applied to clinical drug development and trial design, including mixed effect models for drug exposure and response, and covariate (explanatory variables) selection methods to quantify the impact of demographic, disease status and genetic variation on drug dosing, concentration and effect. Systems pharmacology is an evolution of systems biology, and seeks to harness quantitative, time-dependent pathway models to predict and quantify the effects of pharmacological interventions on downstream biomarkers, ultimately aiding rational target and drug candidate selection. This presentation will describe modern drug discovery and development pipelines and the role of pharmacometrics and systems pharmacology, highlighting in particular their interdisciplinary nature and the extent to which they borrow from other disciplines, including mathematics, statistics and computer science.
The second webinar was given by Léa Sta (ESR 3) and was attended by all ESRs, three partners, as well as external participants consisting of MSc/PhD students at the University of Leeds and Imperial College London, and an academic from Comillas Pontifical University.
Title: An analytical study of a IL-7R model
Abstract: IL-7 is a cytokine necessary for the survival of T cells. Its receptor (IL-7R) is composed of the common gamma chain and a specific alpha chain. When signalling, the IL-7R uses the JAK-STAT pathway, thus the intracellular molecule JAK3 is necessary for IL-7 signalling. Gregoire Altan-Bonnet’s team, at NIH, made the following counter-intuitive observation: when the number of gamma chains on the surface of a cell increases, IL-7 signalling decreases. They also observed that an increasing number of gamma chains per cell increases the EC50 while the amplitude of the dose response first increases then decreases. We developed a mathematical model which explains the drop in IL-7 responsiveness by the formation of dummy complexes when the number of JAK3 molecules is limiting, and whose its amplitude behaves like in the experiment. We make use of an algebraic tool known as the Groebner basis to derive analytical expressions for the steady states of our model. These expressions allow us to make a full mathematical study and to compute asymptotic expressions. In particular, we can compute analytically the amplitude and the EC50 of the dose-response, providing insights that may be relevant for biologists interested in cytokine signalling. Our methods can be extended to other dimeric receptor models.
ESR 6, Giulia Belluccini, gave the fourth QuanTII webinar on 10 September at 11am UK time, via MS Teams.
It was attended by ESRs and partners, as well as an academic and PhD students from the University of Leeds.
Title: Multi-compartmental models for T cell proliferation and death
Abstract: Many biological processes are modelled using Markov chains, therefore the inter-event times, i.e. the times between consecutive events, are assumed to be exponentially distributed. This hypothesis fails when cell proliferation plays a key role. Indeed, the history-dependence nature of the cell cycle breaks the Markov property.
In this talk I will present a mathematical model for the cell cycle which guarantees the validity of the Markov property and includes cell proliferation and death. The idea behind is to divide the cell cycle into several compartments, each of whom is exponentially distributed and independent on the others.
Then, cell generations will be introduced in the model to infer the parameters with CFSE data, making use of Bayesian methods.
After that, I will consider an alternative scenario where the cell decides its fate at birth.