Next Generation Pathology in translational research: steps towards implementation of digitalization and multiplexing in the clinics

Histopathology has undergone two major revolutions since it became a global and accepted clinical discipline in the first half of the 20th Century: the introduction of immunohistochemistry (IHC) in the 70s and of molecular techniques in the early 2000s have redefined the field of precision medicine. IHC, after not having changed significantly for more than 40 years, is finally evolving from a onemarker-at-the-time technique to measuring multiple markers at the same time in the same tissue slide – a method that is known as multiplex immunohistochemistry (mIHC). On the opposite of mIHC, single IHC stainings cannot capture the complexity of human tissue at the level needed for the progression towards personalized medicine. We are now at the verge of a third revolution in histopathology: Digital Pathology (DP). Coming on the back of Artificial Intelligence (AI) and mIHC, DP has the potential to both challenge traditional practice and improve patient diagnostics and treatment. AI can automate several of the highly time-consuming tasks for the pathologists, allowing them to spend more time on highlevel tasks. In my previous work, I participated in the development of a mIHC technique, that I successufully implemented in the Laboratory for Translational Cell and Tissue Research. My actual work is focused on developing effective tools for translating mIHC, AI and DP in the clinical context and applying these techniques to melanoma research.