dynamics of disease – day 3

I missed day 2 due to travel costs.  Day 3 kicked off with Professor Hans Westerhoff presenting his vision of the systems biology of disease and 7 billion virtual humans.  Present day diseases are molecular diseases, incorporating multiple genes and therefore nodes in the network.  Modern diseases are therefore “network diseases”.  Treatments should therefore target multiple nodes of the network and not the individual molecule.  Professor Westerhoff presented his vision for linking global networks of data to provide diagnostic tools on individuals for personalized medicine.  There was then an outline of his concepts of network fragility, which looked quite similar to network sensitivity to me, but provide a mathematical prediction of intervention points in the network, based on the fragility of the network around that node, or hub with regard to the flux through the network.

Thomas Eissing, from Bayer next gave a very informative talk on the application of multi-scale modelling in medicine and pharmacology.  His group work in a consultancy role for pharma customers and are able to make multi-scale models of diseases, using pharmacokinetics (PK) (what the molecule does) and pharmacodynamics (PD) (what the molecule does to the body) to reduce clinical trials group sizes, and target more refined network intervention points for disease therapies.  Their group has developed a number of modelling tools to assist them, such as PK.Sim, and Mobi, with network topology and flux balance analysis to build static models of the “virtual human” which can be refined into dynamical models as hypothesis generation leads to experimental data.

This was the most interesting talk for me, with real-world practical applications to some of the theories outlined by Professor Westerhoff.  The group has been able to build multi-scale virtual liver models for studying tumour development, incorporating signal transduction models into cell models, and then into organ scale models with “virtual lab rats”.  Superimposing PK data onto these models then provides dynamic time course simulations to estimate drug efficacy, and also the required treatment time which can dramatically reduce the time scale of clinical trials.

Later in the day, Yusur Al-Nuaimi, one of the doctoral training centre students presented her work on systems biology approaches to human hair cycle.  Yusur had gained her Ph.D the previous day, and had recently published her work in this field (pubmed ID’s 20590819 and 19725870).  A mathematical approach firstly identified a delayed feedback loop in the life cycle of the hair follicle, and this was explored experimentally with clock genes for anagen and catagen transition, revealing an autonomous timing mechanism in the hair follicle.

The meeting finished with a presentation from Roger Traub (IBM) on the cellular mechanism of epilepsy, showing how modelling approaches can be used to try and understand the complex high frequency, low amplitude (200Hz) oscillations in brain activity that leads to seizures.  Roger Traub also used a cellular automaton model to show coordinated oscillations in populations of cells during seizures.