How mechanistic in silico modelling can improve our understanding of TB disease and treatment

Funding: Medical Research Council [grant number MR/P014704/1], The Academy of Medical Sciences (AMS), the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy (BEIS), the British Heart Foundation and the Global Challenges Research Fund (GCRF) [grant number SBF003\1052] and the PreDiCT-TB consortium (IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.TB is one of the top 10 causes of death worldwide and the leading cause of death from a single infectious agent. Decreasing the length of time for TB treatment is an important step towards the goal of reducing mortality. Mechanistic in silico modelling can provide us with the tools to explore gaps in our knowledge, with the opportunity to model the complicated within-host dynamics of the infection, and simulate new treatment strategies. Significant insight has been gained using this form of modelling when applied to other diseases – much can be learned in infection research from these advances.Publisher PDFPeer reviewe