Improving red blood cell transfusion through systems biology

通过系统生物学改善红细胞输注

基本信息

批准号：
9049084
负责人：
Aarash Bordbar
金额：
$ 102.93万
依托单位：
SINOPIA BIOSCIENCES, INC.
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-11-19 至 2018-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9049084
关键词：
Accounting Affect Algorithms Area Biochemical Pathway Biological Preservation Blood Banks Caring Cell physiology Cells Cellular Metabolic Process Cellular Morphology Clinical Complex Computational Technique Computer Simulation Computing Methodologies Data Data Analyses Data Set Effectiveness Enzymes Erythrocyte Transfusion Erythrocytes Formulation Generations Hospital Costs Hospitalization Hospitals In Vitro Intervention Kinetics Lesion Life Measures Medicine Metabolic Metabolic Pathway Methods Modeling Morbidity - disease rate Observational Study Outcome Patient-Focused Outcomes Patients Phase Preclinical Testing Process Publishing Randomized Clinical Trials Reaction Records Rheology Safety Staging Statistical Data Interpretation Supplementation Systems Biology Techniques Technology Testing Transfusion United States Update Validation Work base clinically relevant commercialization cost improved interest metabolic profile metabolomics model design new technology novel open innovation prevent product development programs public health relevance research study statistics success time use

项目摘要

DESCRIPTION (provided by applicant): Red blood cells (RBC) stored in approved additive solutions undergo a set of metabolic and physicochemical changes referred to as `storage lesions' reducing the efficacy and safety of older transfused RBC units. Though the consequences of the storage lesion are slowly becoming well documented, a major reason for delayed progress in developing new technologies for quality and safety of RBC transfusion is the lack of global understanding of metabolic decline during storage. There has been interest to utilize high-throughput metabolite profiling for global understanding of RBC metabolic decline but data analysis of complex datasets has been a daunting challenge. In Phase I of this program, we developed the first, robust computational platform involving statistical analysis, systems biology of metabolic networks, and data-driven kinetic models to fully interpret and analyze RBC metabolite-profiles in a complete network context. Using time-course global, quantitative metabolite profiling, we determined that RBCs undergo a clinically relevant non-linear decay process and computationally identified key metabolic enzymes that drive this decay process. Based on the computational results, we have devised two novel additive solution strategies to mitigate the decay process and improve the safety and accuracy of RBC transfusion. In this proposal, we will validate the computationally determined additive solutions for efficacy in alleviating the non-linear decay process through 1) metabolomics experiments, and 2) non-metabolic RBC physiology experiments including cell rheology and microparticle generation. A successful additive solution will be progressed to media refinement and preclinical testing.

描述（由适用提供）：存储在认可的添加剂溶液中的红细胞（RBC）经历了一组代谢和物理变化，称为“储存病变”，降低了较旧的输管RBC单位的效率和安全性。尽管储存病变的后果正在逐渐得到充分的文献记载，但在开发新技术以提高新技术的质量和安全性，这是RBC输血的质量和安全性的主要原因是缺乏全球对存储期间代谢下降的理解。使用高通量代谢物分析来全球了解RBC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。在该程序的第一阶段，我们开发了涉及统计分析，代谢网络的系统生物学以及数据驱动的动力学模型的第一个强大的计算平台，以在完整的网络环境中充分解释和分析RBC代谢物 - 培训。使用时间表全球定量代谢物分析，我们确定在临床相关的非线性衰减过程和计算鉴定的关键代谢酶下，RBC驱动了这一衰减过程。根据计算结果，我们设计了两种新型的添加溶液策略，以减轻衰减过程并提高RBC输血的安全性和准确性。在此提案中，我们将验证计算确定的添加剂解决方案，以通过1）代谢组学实验来减轻非线性衰减过程，以及2）非代谢RBC生理学实验，包括细胞性性变性和微粒生成。成功的添加剂解决方案将发展为媒体的改进和临床前测试。