Platelet transfusion is critical for severely bleeding, functionally abnormal platelets, or low platelet counts due to oncology medications, and nearly 7 million units are transfused in the United States and Europe annually. In the United States, platelets can only be stored for 5 days due to concerns over contamination with pathogenic organisms. This results in waste of 15% of the platelet supply in the US. New photochemical methods have been developed for pathogen inactivation, however they may adversely affect the platelet quality and thus transfusion efficacy. Platelet additive solutions have the possibility to prevent and reverse this loss of quality and improve the efficacy of pathogen inactivation techniques. While the benefits are well known, there has been little progress in developing new platelet additive solutions for increasing quality and safety of platelet transfusion because there is a lack of broad understanding of the biochemical decline following pathogen inactivation techniques. We have developed computational tools that utilize high-throughput metabolite profiling data to gain a global understanding of platelet metabolic decline. The proposed program will generate time-course global, quantitative metabolite profiling to track intracellular and extracellular platelet metabolites following pathogen inactivation. We will apply our recently developed computational platform to this data to fully interpret and analyze platelet metabolite profiles following pathogen inactivation techniques. This robust platform utilizes statistical analysis, systems biology of metabolic networks, and data-driven models to gain a deep biochemical understanding that will be employed to quantitatively predict optimal additive solutions to alleviate pathogen inactivation techniques. Each predicted solution will be evaluated based on biological efficacy, cost, and regulatory hurdles. Predicted additives will be chosen for experimental validation and testing in Phase II.
Platelet transfusion units can only be stored for five days in the United States due to concerns over contamination with pathogenic organisms. New technologies have emerged to pathogen inactivate platelet units, however the technique may adversely affect platelet quality. As part of this proposal, novel computational methods will be developed and applied to comprehensively understand the degradation of platelets after pathogen inactivation and to predict new additive solutions that prevent or revert degradation thus increasing platelet transfusion quality and extending shelf life.
