Videos and presentation materials from other INI events are also available.
Event | When | Speaker | Title | Presentation Material |
---|---|---|---|---|
IDPW04 |
7th July 2020 14:00 to 16:00 |
Raluca Eftimie, Grant Lythe, Farzad Fatehi Chenar |
Session 1 |
|
IDPW04 |
7th July 2020 14:05 to 14:30 |
Grant Lythe |
Stochastic dynamics of Francisella Tularensis infection
Jonty Carruthers, Martin Lopez-Garcia, Grant Lythe, Carmen Molina-Paris (Leeds). Joseph Gillard, Thomas R Laws, Roman Lukaszewski(Dstl)With a mouse infection model, agent-based computation and mathematical analysis, we study the pathogenesis of Francisella Tularensisinfection. A small initial number of bacteria enter host cells and proliferate inside them, eventually destroying the host cell and releasing numerous copies that infect other cells. Our analysis of disease progression is based on a stochastic model of a population of infectious agents inside one host cell, extending the birth-and-death process by the occurrence of catastrophes: cell rupture events that affect all bacteria in a cell simultaneously. We compare our analysis with the results of agent-based computation and, via Approximate Bayesian Computation, with experimental measurements carried out after of murine aerosol infection with the virulent SCHU S4 strain of the bacterium.If I have time, I will also talk about Ebola, still a significant risk to humankind. Synthetic virology has been used to clone and manufacture two deletion defective genomes. These genomes were tested with Ebola virus using in vitro cell culture and shown to inhibit viral replication. From in vitro experimental data, we identify parameters in a mathematical model of the infection. We examine the time an infected cell spends in the eclipse phase (the period between infection and the start of virus production), as well as the rate at which infectious virions lose infectivity.
|
![]() |
IDPW04 |
7th July 2020 14:30 to 15:00 |
Raluca Eftimie |
Modelling virus infections in the context of cancer therapies (and other diseases)
Over the past years oncolytic viruses have
generated much interest in cancer therapy, mainly due to the fact
that once a virus is injected into the patient it can actively search for
cancer cells and destroy them. However, the anti-tumour effect of
oncolytic viruses is greatly diminished by anti-viral immune responses (both
innate and adaptive responses), as well as by physical barriers inside
the tumour. Using various single-scale and multi-scale mathematical modelling approaches, we will investigate the delicate balance between anti-viral and anti-tumour immune responses in the context of virus-tumour-immune interactions. |
|
IDPW04 |
7th July 2020 15:00 to 15:30 |
Farzad Fatehi Chenar |
Multiscale within-host modelling of SARS-CoV-2 infection reveals benefits and risks of early Remdesivir treatment
The
SARS-CoV-2 outbreak has infected over ten million, and killed over 500,000,
individuals worldwide, making the development of antiviral treatments against
this virus a priority. Recent studies have identified Remdesivir as an
effective antiviral treatment option for COVID-19. I will present a new
stochastic agent based model for the intracellular dynamics of a SARS-CoV-2
infection that includes details on all essential steps of a viral life cycle,
from viral entry to virion release. Using this model, I evaluate the effect of
Remdesivir on the production of new virions. In a next step, I propose an
intercellular model to study the viral dynamics within the body of an infected
patient. The intercellular model is fitted to data recording the progress of viral
load in 12 patients with COVID-19, showing how differing strengths of immune
response can explain the variety of infection spans seen in patients. Coupling
the intra- and intercellular models allows for a comparative analysis of
Remdesivir therapy for patients with different types of immune response.
|
|
IDPW04 |
7th July 2020 15:30 to 16:00 |
Discussion | ||
IDPW04 |
8th July 2020 12:00 to 13:00 |
Session 2 - PLENARY TALK by Ruth Bowness - University of St. Andrews - Modelling within-host tuberculosis infection using a hybrid multiscale individual-based model
Tuberculosis (TB)
is an infectious disease caused by Mycobacterium tuberculosis. Despite
significant recent advances, TB is the biggest infectious killer globally -
someone dies from the disease every 18 seconds. I will describe a hybrid
multiscale individual-based model that has been developed to study disease
progression and treatment in the human lung. The model contains discrete agents
which model the spatio-temporal interactions (migration, binding, killing etc.)
of bacteria and immune cells. Chemokine and oxygen dynamics are also included,
as well as Pharmacokinetic/Pharmacodynamic models, which are incorporated into
the model via PDEs. In this work, I explore concepts of relapse and latent TB
disease, and their effect on treatment outcome.
|
![]() |