Improving red blood cell transfusion through systems biology
Improving red blood cell transfusion through systems biology
批准号:
9049084
负责人:
Aarash Bordbar
金额:
$102.93万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-11-19 至 2018-05-31
关键词:
AccountingAffectAlgorithmsAreaBiochemical PathwayBiological PreservationBlood BanksCaringCell physiologyCellsCellular Metabolic ProcessCellular MorphologyClinicalComplexComputational TechniqueComputer SimulationComputing MethodologiesDataData AnalysesData SetEffectivenessEnzymesErythrocyte TransfusionErythrocytesFormulationGenerationsHospital CostsHospitalizationHospitalsIn VitroInterventionKineticsLesionLifeMeasuresMedicineMetabolicMetabolic PathwayMethodsModelingMorbidity - disease rateObservational StudyOutcomePatient-Focused OutcomesPatientsPhasePreclinical TestingProcessPublishingRandomized Clinical TrialsReactionRecordsRheologySafetyStagingStatistical Data InterpretationSupplementationSystems BiologyTechniquesTechnologyTestingTransfusionUnited StatesUpdateValidationWorkbaseclinically relevantcommercializationcostimprovedinterestmetabolic profilemetabolomicsmodel designnew technologynovelopen innovationpreventproduct developmentprogramspublic health relevanceresearch studystatisticssuccesstime use
中文摘要
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英文摘要
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.
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海外基金