PROJECT SUMMARY/ABSTRACT Hematopoietic stem cell transplantation (HSCT) offers an advanced treatment option for conditions that are otherwise incurable. Pulmonary complications are common following HSCT and severely compromise its overall success rate. The most severe end of this spectrum is acute respiratory distress syndrome (ARDS), which occurs in 5% of patients following HSCT, with a mortality >60%. As effective treatments for ARDS are lacking, developing new ways to prevent ARDS is likely to be more successful in improving patient outcomes. Two critical knowledge gaps make developing successful prevention strategies difficult: 1) an inability to reliably identify high-risk patients before ARDS has developed and; 2) an incomplete understanding of the mechanisms and subtypes of post-HSCT ARDS. The scientific objectives of this application are to address these critical knowledge gaps through the following Specific Aims: 1) Develop and validate a risk-prediction model incorporating pre-transplant, post-transplant and in- hospital risk factors that can help identify which patients are most likely to develop post-HSCT ARDS. 2) Prospectively evaluate metabolomics in patients at high-risk of developing post-HSCT ARDS and utilize clinical, biomarker and metabolomics data to explore endophenotypes of post-HSCT ARDS. Aim 1 leverages highly innovative data extraction techniques to develop a real-time continuous ARDS risk surveillance system for patients who undergo HSCT. Aim 2 evaluates the role of metabolomics, an emerging analytic tool, in advancing mechanistic understanding of why patients develop post-HSCT ARDS, as well as whether recently described ARDS endophenotypes can be identified post-HSCT ARDS. The applicant’s long-term goals are to: 1) become an independent translational clinician-scientist leading a multidisciplinary research team focused on improving outcomes of patients who develop respiratory complications after HSCT, and 2) develop effective strategies to prevent post-HSCT ARDS, one of the most significant post-transplant complications today. The training goals of the applicant are to develop advanced skills in statistics, biomedical modeling, machine learning, and metabolomics to facilitate these long-term goals. To address these training needs, the applicant has constructed a comprehensive career development plan that includes targeted didactic opportunities in the areas of training need above, with additional “hands-on” experience in all of these areas. The mentorship team and research environment is uniquely well suited to the applicant’s needs, combining expertise in critical care informatics and metabolomics at a high-volume academic transplant center. The proposal supports the NIH mission by striving to improve outcomes of patients who develop respiratory failure after transplantation, while training a junior investigator in the essential skills necessary for his transition to research independence.