Medical laboratory in autoimmunity 2017

Abstract

AbstractWith big data algorithms and artificial intelligence (AI) at stake the optimal assembly of the most appropriate lab assays selected to diagnose, treat and follow up patients suffering from well-delineated disease may get lost. The physician ordering a lab test, instead of asking for a good composition of screening tests is tempted to order a large number of assays, including genome sequencing hoping to find the diagnostic evidence for his/her patient at once. Four major specialities of medical laboratory assays, i.e. clinical chemistry, hematology, immunology and microbiology are embraced by genome sequencing techniques and have attained the degree of robotics, facilitating assays to such a degree, that the prescriber is free of concern as to how costly/complicated an investigation might become. Diagnostics with autoimmune diseases is not an exemption and autoantibody screening using multiplex assays or therapeutic drug monitoring to adjust treatments of inflammatory/autoimmune diseases is bound to become more and more informative even more so as the pharmacodynamics of modern pharmaceutical agents are explored. As the most appropriate therapeutical agents to monitor in the lab, biological response modifiers, immunosuppressants and monoclonal antibodies are at the forefront and we need to explore their efficacy and side effect profiles not only using phase III clinical studies but also by using postmarketing surveillance. Behind the profiles provided by big data and artificial intelligence, the therapeutically-induced regained immune balance can thus be traced to the single best lab assay. The next decade promises a series of new assays, e.g. inflammasome profiles, lymphocyte markers by fluorescence activated cell sorters as well as single cell secretome analysis.