Our work seeks to continue to determine the mechanistic elements underlying the immune system’s response to foreign antigen which determine the fate of transplanted allogenic cells, tissues and organs into human patients.  As well, there are many influencing factors on the immune system which have come to be recognized as increasing importance, which alter the phenotypic milieu and interactions between self and non-self tissues. These include the microbiome, the intrinsic nonself commensal organisms that live within and are extrinsic to, the human body which intimately affect how we perceive, process and react to the outside world, the rise of glyco-reactive species on the surface of cells which have been demonstrated to have increasing importance in allorecognition and which appear to be amenable to experimental manipulation.

Artificial intelligence and Machine Learning techniques are increasingly used in the domain of Kidney Transplantation, given the extreme complexities of accounting for input donor and organ variables, procurement and logistics, implantation complications and hemodynamics, recipient baseline factors and the influence of immune suppression and residual immune reactivity on outcomes. With success rates greater than 95% and standard 20 year graft survival outcomes, incremental gains come with continuous ML derived insights into optimizations along the chain of care.  The center continues to develop and refine AI and machine learning methods to analyse the rich data intensive environment which is kidney transplantation and immunology.