Improving safety and efficacy of platelet transfusion through systems biology

 描述（由申请人提供）：血小板输注对严重出血患者至关重要，在美国和欧洲每年输注近700万单位。在美国，血小板只能储存5天，导致15%的供应浪费。短储存时间是细菌污染和血小板质量考虑的结果。尽管已经开发了许多用于细菌检测和病原体灭活的方法，但是用于提高储存血小板质量的方法较少。血小板添加剂溶液有可能提高储存质量和持续时间，减少血浆相关过敏反应，影响病原体减少技术的有效性，并节省血浆，然后可将其用作额外的输血产品。虽然益处是众所周知的，但在开发新的血小板添加剂溶液以提高血小板输注的质量和安全性方面进展甚微，因为缺乏对储存期间生化下降的广泛理解。人们一直有兴趣利用高通量代谢物和蛋白质谱来全面了解血小板代谢下降，但复杂数据集的数据分析一直是一个艰巨的挑战。该计划将开发第一个强大的计算平台，涉及统计分析，系统生物学， 代谢和信号网络，以及数据驱动的动力学模型，以充分解释和分析血小板代谢物和蛋白质谱在一个完整的网络背景。该计划将利用最近生成的时程全球定量代谢物分析来跟踪细胞内和 标准储存条件下的细胞外血小板代谢物和文献中可用的蛋白质组学研究。深入的生物化学的理解将被用来定量预测最佳的添加剂解决方案的基础上的生物功效，成本和监管机构的障碍。预测的添加剂将被选择用于第二阶段的实验验证和测试。

 DESCRIPTION (provided by applicant): Platelet transfusion is critical for severely bleeding patients 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 resulting in a waste of 15% of their supply. Short storage duration is a consequence of bacterial contamination and platelet quality considerations. Though many methods have been developed for bacterial testing and pathogen inactivation, fewer have been developed for improving quality of stored platelets. Platelet additive solutions have the possibility to increase storage quality and duration, reduce plasma-related allergic reactions, impact the efficacy of pathogen reduction techniques, and save plasma which can then be used as an additional transfusion product. 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 biochemical decline during storage. There has been interest to utilize high-throughput metabolite and protein profiling for global understanding of platelet metabolic decline but data analysis of complex datasets has been a daunting challenge. The proposed program will develop the first, robust computational platform involving statistical analysis, systems biology of metabolic and signaling networks, and data-driven kinetic models to fully interpret and analyze platelet metabolite and protein profiles in a complete network context. The program will utilize recently generated time-course global, quantitative metabolite profiling to track intracellular and extracellular platelet metabolites under standard storage conditions and available proteomic studies in literature. The deep biochemical understanding obtained will be employed to quantitatively predict optimal additive solutions based on biological efficacy, cost, and regulator hurdles. Predicted additives will be chosen for experimental validation and testing in Phase II.