Convergence science enhances the translational pathway by providing new methodologies to address clinically relevant questions and interrogate patient samples. If often focuses on late stages of translation, convergence can also be successfully implemented to Discovery Research. 





Qatar Complex Fluids Laboratory with Confocal laser scanning microscope equipment with display of 2D High resolution confocal images of carbonate rocks

Navigating complex data and improving data collection

Discovery science is a scientific methodology which explores large-scale experimental data to formulate new hypotheses by the observation of quantitative and qualitative patterns and correlations. Particularly popular in biology and medical research through the emergence of multi-OMICS and multi-modal approaches and artificial intelligence, it requires complex innovative analytic pipelines and cutting-edge computational science. Convergence science can enhance discovery research either directly, by providing new methodologies and promoting new analytic practices, or indirectly by augmenting the quality and breadth of data collection. By exploiting key mechanisms in the establishment of disease, we can provide the rational basis for the development of strategies to prevent, detect, diagnose and treat cancers. There are fundamental gaps in our understanding the mechanisms of tumour development, progression and metastasis, which are in part due to a lack of methodologies and technologies that can track microscale events in vivo. We believe the synergy between convergence and discovery sciences can allow substantial progress in how we collect, analyse and interpret biological data to grow our understanding of cancer. 






Monitoring the living

Convergence science allows the development of technologies and tools to explore the living through novels lenses by merging biological and EPS expertise. Major technological advances can be achieve in:

  • Visualising biological processes of cancer progression to understand tumour heterogeneity and evolution
  • Understanding the physical relationship between the tumour and its environment through the recapitulation of the tumour microenvironment, including the interplay with the immune system
  • Monitoring of processes in vivo to understand mechanism of action of therapeutics, emergence of resistance and combination strategies without modifying the behaviour of the therapy itself
  • Promoting of an iterative forward and reverse-translational model that will push new therapies towards approval through biologically-informed patient selection and stratification
'Night of the Living Glia' by Amy Birch and Alex RenziehauA confocal microscope image of brain cells from a mouse model of Alzheimer's disease.