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Transfusion of red blood cells (RBCs) is one of the most valuable and widespread treatments in modern medicine. Lifesaving RBC transfusions are facilitated by the cold storage of RBC units in blood banks worldwide. Currently, RBC storage and subsequent transfusion practices are performed using simplistic workflows. More specifically, most blood banks follow the "first-in-first-out" principle to avoid wastage, whereas most healthcare providers prefer the "last-in-first-out" approach simply favoring chronologically younger RBCs. Neither approach addresses recent advances through -omics showing that stored RBC quality is highly variable depending on donor-, time-, and processing-specific factors. Thus, it is time to rethink our workflows in transfusion medicine taking advantage of novel technologies to perform RBC quality assessment. We imagine a future where lab-on-a-chip technologies utilize novel predictive markers of RBC quality identified by -omics and machine learning to usher in a new era of safer and precise transfusion medicine. [ABSTRACT FROM AUTHOR]

The article discusses the need for objective tools to assess the quality of stored red blood cells (RBCs) for transfusion medicine. The authors highlight the potential of lab-on-a-chip (LOC) technologies to quantitatively evaluate RBC quality using multidimensional metrics. They acknowledge the development of a point-of-care device called Erysense, which assesses the flow properties and morphological abnormalities of stored RBCs. However, they also mention limitations and challenges that need to be addressed, such as the need for extensive validation, automation of the workflow, and addressing storage lesions. The authors suggest that while scalable strategies for in vitro erythropoiesis are promising, other steps can be taken to address blood shortages and improve transfusion practices. [Extracted from the article]