Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=3&sort=-principal_investigator
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1405&sort=-principal_investigator", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=4&sort=-principal_investigator", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=-principal_investigator" }, "data": [ { "type": "Grant", "id": "15779", "attributes": { "award_id": "1R01AI197146-01", "title": "SCH: A structural causal framework for adaptive experiments", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 32567, "first_name": "MEGHAN ANN", "last_name": "HARTWICK", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-06", "end_date": "2029-07-31", "award_amount": 299422, "principal_investigator": { "id": 32855, "first_name": "Ivan", "last_name": "Diaz", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32856, "first_name": "Michele", "last_name": "Santacatterina", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2643, "ror": "", "name": "NEW YORK UNIVERSITY SCHOOL OF MEDICINE", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Adaptive randomized clinical trials are critical in infectious disease research, offering flexibility to adjust sample sizes, introduce new interventions, discontinue ineffective treatments, and target specific subgroups to enhance treatment efficacy. This adaptability is particularly valuable in rapidly evolving public health crises, such as the development of treatments for emerging infectious diseases like COVID-19. However, adaptive trials present significant challenges, including unclear inferential targets, statistical biases from temporal and spatial variability, complexities in handling dynamic data structures, and an increased risk of false-positive findings. These concerns are reflected in recent FDA guidance on estimands, which emphasizes the need for clearly defined inferential targets, and on adaptive designs, which acknowledges that statistical bias in adaptive trials remains an understudied issue. Despite these recognized challenges, current research lacks a principled framework for structurally representing and unbiasedly estimating causal effects in adaptive trials. This project will develop a structural causal framework for adaptive trials, leveraging modern causal inference and statistical techniques alongside secondary data from the Adaptive COVID-19 Treatment Trial (ACTT)—an adaptive trial evaluating novel therapeutics in hospitalized COVID-19 patients—to enable transparent, efficient, and statistically unbiased estimation of causal effects. To achieve this, we propose the following specific aims: Aim 1: Develop a structural causal approach that deals with temporal variability. Aim 2: Extend our framework to handle spatial variability. Aim 3: Expand our framework to handle complex data structures, including failure-time and missing data, while dealing with false-positive results. Our project aligns with NIAID’s mission by advancing key methodologies for infectious disease clinical trials, particularly in adaptive designs for pandemic response, emerging pathogens, and the development of antiviral treatments. While our primary focus is on infectious disease trials, our methods have broader applicability to other disease areas, such as schizophrenia. We show this by also leveraging secondary data from schizophrenia studies, including the DECIFER trial, the RAISE study, and the EPINET study. RELEVANCE (See instructions): This research aims to improve how adaptive clinical trials are designed and analyzed. By developing methods that address key challenges in adaptive trials, our work will help ensure more accurate and reliable results, ultimately leading to better treatments and public health responses to emerging infectious diseases.", "keywords": [ "Address", "Area", "COVID-19", "COVID-19 patient", "COVID-19 treatment", "Clinical Trials", "Clinical Trials Design", "Communicable Diseases", "Data", "Disease", "Emerging Communicable Diseases", "Ensure", "Failure", "Hospitalization", "Infectious Diseases Research", "Instruction", "Intervention", "Methodology", "Methods", "Mission", "Modernization", "National Institute of Allergy and Infectious Disease", "Public Health", "Reliability of Results", "Research", "Risk", "Sample Size", "Schizophrenia", "Statistical Bias", "Structure", "Subgroup", "Techniques", "Time", "Treatment Efficacy", "Work", "antiviral drug development", "complex data", "design", "emerging pathogen", "experimental study", "flexibility", "improved", "ineffective therapies", "novel therapeutics", "pandemic response", "randomized clinical trials", "response", "spatiotemporal", "therapy development", "treatment trial" ], "approved": true } }, { "type": "Grant", "id": "15778", "attributes": { "award_id": "1R50CA305057-01", "title": "A System to Support Development and Success of NCI-Sponsored Trials for Rare Diseases", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Cancer Institute (NCI)" ], "program_reference_codes": [], "program_officials": [ { "id": 32853, "first_name": "SONYA", "last_name": "ROBERSON", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-11", "end_date": "2030-07-31", "award_amount": 122610, "principal_investigator": { "id": 32854, "first_name": "Kim A", "last_name": "Reiss Binder", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2627, "ror": "", "name": "UNIVERSITY OF PENNSYLVANIA", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "R50 Abstract – Reiss Gastrointestinal maligancies remain lethal and difficult-to-treat, with poor outcomes for many patients. In spite of this, we are in a moment of a scientific and clinical revolution with the development of biomarker-driven therapies for selected patients. With these advances come multiple new questions for the field, many of which the NCTN infrastructure is optimally suited to address. To date, I have demonstrated a strong commitment to clinical and translational research for populations of patients with rare subsets or biomarkers, including via the development and implementation of NCI-trials at my own institution: I am the international study chair and lead accruer for EA2192 as well as the study champion and lead national accruer for SWOG-2001. On the larger scale, I hold leadership roles within the Abramson Cancer Center (ACC) at the University of Pennsylvania and at the NCTN. I serve as the co-chair of the ECOG- ACRIN GI Committee, I am the co-leader of the ACC Cancer Therapeutics Program and I am the co-leader of the ACC Pancreatic Clinical Trial Program. These leadership positions are optimal platforms upon which to spearhead programs that (1) formally and longitudinally assist junior and mid-career oncology faculty in their quests to develop investigator-initiated studies and (2) develop a program at the NCTN that focuses on developing realistic trials for rare populations and then on accruing them successfully. To date, I have demonstrated a persistent and strong commitment to the NCI research enterprise. I have been involved with NCI-related research since my early career, initially attending meetings and later developing my own protocol, EA2192. Based on my steady engagement and input, I was appointed as the co-chair of the GI Committee in 2022 alongside Jordan Berlin (see LOS). Together, we have made a commitment to improving the process of clinical trial development, a mission that will be critical in order for the NCTN to remain competitive in an ever-changing landscape. Over the past three years, we have employed multiple initiatives including boosting the education of our investigators about the NCTN process, leaning on the excellent Working groups chairs to fine-tune concepts prior to Committee Presentation and providing substantial assistance during the submission process. With the support of the R50 Research Specialist award, I will build further on this approach in two ways: At the ACC, I will develop a sustainable program for early and mid-career investigators to provide longitudinal support in the development of investigator-initiated trials, with a particular focus on rare disease studies that can be best executed via the ECOG-ACRIN system. Within the NCTN, I will employ a novel program assisting investigators in the development and successful enrollment of trials for rare disease populations, a subset of studies that have lost ground since the COVID pandemic. Specifically, I will create a living resource for NCTN investigators that focuses on methods to design practical, feasible studies and will provide longitudinal support to those across the NCTN who are developing studies in this space. My ultimate goal is to develop and implement pragmatic clinical trials that address key questions in the field of gastrointestinal malignancies, particularly for patients with rare subsets of disease.", "keywords": [ "Abramson Cancer Center at the University of Pennsylvania", "Address", "American College of Radiology Imaging Network", "Award", "Berlin", "Biological Markers", "COVID-19 pandemic", "Cancer Biology", "Cancer Center", "Clinical", "Clinical Research", "Clinical Trials", "Development", "Disease", "Eastern Cooperative Oncology Group", "Education", "Faculty", "Feasibility Studies", "Genomics", "Goals", "Infrastructure", "Institution", "International", "Jordan", "Knowledge", "Lead", "Leadership", "Malignant Neoplasms", "Malignant neoplasm of gastrointestinal tract", "Methods", "Mission", "Oncology", "Outcome", "Pancreas", "Patient Selection", "Patients", "Persons", "Population", "Positioning Attribute", "Pragmatic clinical trial", "Process", "Program Sustainability", "Protocols documentation", "Rare Diseases", "Research", "Research Personnel", "Resources", "Role", "Selection for Treatments", "Southwest Oncology Group", "Specialist", "System", "Therapeutic", "Thinness", "Translational Research", "biomarker development", "biomarker driven", "cancer subtypes", "career", "design", "gastrointestinal", "improved outcome", "investigator-initiated trial", "meetings", "novel", "patient population", "process improvement", "programs", "success", "trial enrollment", "working group" ], "approved": true } }, { "type": "Grant", "id": "15777", "attributes": { "award_id": "1R01AR085033-01", "title": "Improving the diagnosis and outcome of diffuse alveolar hemorrhage in systemic lupus erythematosus", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 32850, "first_name": "MARIE", "last_name": "MANCINI", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-06", "end_date": "2030-06-30", "award_amount": 538755, "principal_investigator": { "id": 32851, "first_name": "WESTLEY H", "last_name": "REEVES", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32852, "first_name": "Haoyang", "last_name": "Zhuang", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2642, "ror": "", "name": "UNIVERSITY OF FLORIDA", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "The variable clinical manifestations of SLE patients are largely unexplained. Although severe diffuse alveolar hemorrhage (DAH) with pulmonary capillaritis is unusual in lupus, more than half of patients with this complication die and focal lung hemorrhage occurs in 30-66% of patients. Using a mouse model (pristane-induced lupus) developed in our laboratory, we will ask why C57BL/6 (B6) mice are susceptible to pristane-induced DAH/vasculitis whereas BALB/c and DBA/2 mice are resistant. DAH is initiated by lung endothelial cell (EC) injury followed by recruitment of bone marrow-derived monocytes to the lung. We found that dysregulation of the extrinsic coagulation pathway also is involved and that lung disease is abolished by early treatment with MEK1/2 or ERK1/2 inhibitors. The overall hypothesis is that genetically- determined lung microvascular EC injury evolves into DAH because of monocyte infiltration into the lung and abnormal regulation of the extrinsic coagulation pathway. Aim 1 addresses susceptibility to DAH. We will ask whether EC injury and bleeding are lung-specific and investigate gene expression patterns associated with DAH by single-cell RNA-sequencing. Genes conferring susceptibility/resistance to EC injury and bleeding be mapped in recombinant inbred BXD (B6 X D2) mice. Aim 2 examines the MEK1/2-ERK1/2 pathway in pristane-induced DAH. We will define the sequence of events leading to DAH and develop blood-based diagnostic tests for the diagnosis of incipient DAH prior to the onset of bleeding. This is important, because the disease process is irreversible once hemorrhage begins. We will look for tests that distinguish early DAH (pre-bleeding) from other forms of lung injury, such as sepsis with acute respiratory distress syndrome. Aim 3 translates what is learned in mice to human DAH. We hypothesize that the disease process is similar except that the initial EC injury is caused by respiratory viral infections rather than pristane. We will ask if a predisposition to lung EC injury determines susceptibility, as in mice, and whether diagnostic approaches developed in the mouse model are relevant to human DAH. Lung EC injury will be examined in SLE patients with influenza or COVID infection and the role of mild bleeding disorders will be explored. The ability to diagnose incipient DAH (pre- bleeding) may permit future therapeutic trials using FDA-approved MEK1/2 inhibitors, such as trametinib, which are highly effective in pristane-induced DAH.", "keywords": [ "ANCA vasculitis", "Acute Respiratory Distress Syndrome", "Address", "Adopted", "Alveolar", "Antineutrophil Cytoplasmic Antibodies", "Autoantibodies", "Autoimmune", "Autoimmune Diseases", "BALB/cJ Mouse", "Biological Assay", "Blood", "Blood Coagulation Disorders", "Blood Vessels", "Bone Marrow", "C57BL/6 Mouse", "COPA syndrome", "Cell Line", "Clinical", "Coagulation Process", "Complex", "Complication", "DBA/2 Mouse", "Data", "Defect", "Dependence", "Development", "Diagnosis", "Diagnostic tests", "Diffuse", "Disease", "Disease susceptibility", "Early Diagnosis", "Early treatment", "Endothelial Cells", "Environmental Risk Factor", "Enzyme-Linked Immunosorbent Assay", "Event", "Exanthema", "Exhibits", "FDA approved", "Future", "Gene Expression", "Gene Expression Profile", "Genes", "Genetic", "Genetic Predisposition to Disease", "Hemorrhage", "Hemostatic function", "Human", "Immune", "Immunologics", "Inbred BALB C Mice", "Inbreeding", "Infiltration", "Inflammation", "Inherited", "Injury", "Intervention", "Kidney", "Laboratories", "Learning", "Life", "Link", "Lung", "Lung Diseases", "Lupus", "Lupus Nephritis", "MAP2K1 gene", "MAPK3 gene", "Malignant Neoplasms", "Maps", "Mediating", "Mitogen-Activated Protein Kinases", "Modeling", "Monitor", "Mouse Strains", "Mus", "NUP214 gene", "Outcome", "Pathogenesis", "Pathway interactions", "Patients", "Plasma", "Predisposition", "Pristane", "Process", "Prognosis", "Public Health", "Qualifying", "Recombinants", "Regulation", "Resistance", "Respiratory Tract Infections", "Retinal blind spot", "Role", "SARS-CoV-2 infection", "Sepsis", "Serum", "Severity of illness", "Systemic Lupus Erythematosus", "Testing", "Therapeutic Trials", "Tissues", "Translating", "Vascular Diseases", "Vasculitis", "Viral Respiratory Tract Infection", "cell injury", "diagnostic strategy", "ds-DNA", "experience", "genome wide association study", "immune function", "improved", "influenza infection", "inhibitor", "injured", "lung injury", "lung microvascular endothelial cells", "monocyte", "mouse model", "novel therapeutics", "prevent", "protein expression", "pulmonary", "recruit", "sepsis induced ARDS", "single-cell RNA sequencing", "treatment response" ], "approved": true } }, { "type": "Grant", "id": "15776", "attributes": { "award_id": "1R35GM160065-01", "title": "Statistical Approaches to Unlock Protein Function from Deep Mutational Scans", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 32565, "first_name": "GUOQIN", "last_name": "YU", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2030-07-31", "award_amount": 420984, "principal_investigator": { "id": 32849, "first_name": "Harold", "last_name": "Pimentel", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 818, "ror": "", "name": "UNIVERSITY OF CALIFORNIA LOS ANGELES", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Understanding how genetic variants impact protein function is essential for unraveling the mechanisms underlying both basic biology and disease, particularly for rare genetic variants. Of the 4.6 million missense variants found in large population studies, only about 2% have clinical interpretations. Due to their rarity, these variants are exceptionally challenging to study through observational methods. However, Deep Mutational Scanning (DMS) offers a high-throughput method for testing thousands of protein variants by generating a mutant library and obtaining a phenotypic readout for each mutation in one sequencing assay. Initially focused on fitness-based readouts, DMS has expanded to include fluorescence-based methods for protein profiling, binding assays, and more. It has been crucial for studying proteins like SARS-CoV-2, BRCA1, and drug-metabolism transporters like OCT1. With over 1,000 protein datasets publicly available, a recent study highlights technical advances by independently assaying over 500 additional proteins in one study. Unfortunately, the development of statistical methods to interpret and analyze these technologies has not kept pace. For example, DMS with fluorescence-activated cell sorting (DMS-FACS), which has been used for nearly a decade to measure protein abundance and other functional phenotypes, still lacks dedicated analysis methods. As a result, analyses are often ad hoc, and small sample sizes (typically three replicates) make standard statistical methods unsuitable. Our recent work demonstrates that naive approaches miss many real effects and lead to many false discoveries. We propose three statistical areas to improve DMS analysis and interpretation through accurate sample comparisons, epistasis analysis, and causal inference. First, we will develop methods to analyze DMS-FACS for assessing how genetic variants affect molecular phenotype targeted by FACS, and enabling precise comparisons between experimental conditions. Second, we will develop methods to improve genetic interaction (epistasis) analysis and interpretation within proteins, and thus ask which protein regions are acting in concert. Third, we open a new area of research for DMS, aiming to identify the causal impact of variants through measured pathways, including complex traits. In summary, we will solve the analysis gap for DMS-FACS, epistasis DMS, and causally link DMS data through structural causal models by leveraging our expertise in DMS data and small sample statistics. Leveraging our expertise in DMS data and small sample statistics, we will create reliable, robust tools for common workflows while also enabling new types of analyses that improve the interpretation of DMS, epistasis, and phenotypic relationships. With strong collaborations with assay developers and DMS experts, along with a proven track record in developing tools for high-throughput sequencing in small sample contexts, we are well-positioned to lead this effort.", "keywords": [ "2019-nCoV", "Affect", "Area", "BRCA1 gene", "Binding", "Biological Assay", "Biology", "Clinical", "Collaborations", "Complex", "Data", "Data Analyses", "Data Set", "Dedications", "Development", "Disease", "Fluorescence", "Fluorescence-Activated Cell Sorting", "Genetic", "Genetic Epistasis", "High-Throughput Nucleotide Sequencing", "Lead", "Libraries", "Link", "Measures", "Methods", "Missense Mutation", "Molecular", "Mutation", "Pathway interactions", "Phenotype", "Population Study", "Positioning Attribute", "Protein Region", "Proteins", "Research", "Sample Size", "Sampling", "Statistical Methods", "Statistical Models", "Technology", "Testing", "Variant", "Work", "causal model", "drug metabolism", "fitness", "genetic variant", "improved", "molecular phenotype", "mutant", "mutation screening", "protein function", "protein profiling", "statistics", "tool", "trait" ], "approved": true } }, { "type": "Grant", "id": "15774", "attributes": { "award_id": "1R44AI191836-01", "title": "Development of a monoclonal therapy for neonatal herpes", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 32845, "first_name": "JULIE", "last_name": "DYALL", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-08", "end_date": "2026-07-31", "award_amount": 248531, "principal_investigator": { "id": 32846, "first_name": "Michael H", "last_name": "Pauly", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32847, "first_name": "Kevin John", "last_name": "Whaley", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2641, "ror": "", "name": "ZABBIO, INC.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Neonatal infections caused by herpes simplex virus 1 or 2 (HSV-1, HSV-2) result in significant morbidity and mortality. Current medical treatment of neonatal HSV infections (nHSV) is limited to small molecule antivirals such as acyclovir, but even with high dose treatment, mortality subsequent to disseminated disease remains high (30%), and central nervous system (CNS) disease is associated with ∼70% neurological morbidity and 25% mortality. Monoclonal antibodies (mAbs) offer a class of intervention that provides immediate protection and a well-established development path, with over 200 mAb products licensed by U.S. and European regulatory bodies. Passive immunization with mAbs has been shown to be effective against a wide variety of infectious agent, with mAbs against Ebola virus, SARS-CoV-2, and Respiratory Syncytial Virus (RSV) approved by the FDA. Members of the ZabBio team have previously advanced 3 mAb products to clinical trials, including one which contained the broadly neutralizing HSV mAb, HSV8, which is the focus of this product development Fast Track SBIR proposal for neonatal HSV infection. More recently, ZabBio scientists have collaborated with Drs. Margaret Ackerman and David Leib (Dartmouth) who have demonstrated the utility of HSV8 in a mouse model of nHSV. These data support the hypothesis that HSV8 may be a useful clinical intervention for nHSV in humans. Phase 1 of this proposal contains 2 aims: 1) Assess the neutralization potency of HSV8 against a panel of HSV-1 and HSV-2 isolates from neonatal herpes patients; 2) Test whether HSV8 selects for HSV-1 and HSV-2 escape mutants. These two aims will result in a rigorous Go/No decision for proceeding to Phase 2. In Phase 2, the proposal transitions to traditional product development with 3 aims: 1) Manufacture HSV8 under cGMP in the Nicotiana benthamiana based Rapid Protein Production Platform (RP3) system; 2) Submit pre-IND to FDA; 3) Perform IND-enabling pharmacology/toxicology studies. This work scope will culminate in an Investigational New Drug (IND) submission.", "keywords": [ "2019-nCoV", "Acyclovir", "Adult", "Anti-viral Agents", "Atopobium vaginae", "Biological Assay", "Central Nervous System Diseases", "Chemistry", "Clinical", "Clinical Pathways", "Clinical Treatment", "Clinical Trials", "Collaborations", "Congenital herpes simplex", "Cyclic GMP", "Data", "Development", "Disease", "Dose", "Ebola virus", "Escape Mutant", "European", "FDA approved", "Feedback", "Film", "Herpesvirus 1", "Human", "Human Herpesvirus 2", "Incubated", "Infectious Agent", "Intervention", "Investigational Drugs", "Licensing", "Medical", "Monoclonal Antibodies", "Monoclonal Antibody Therapy", "Morbidity - disease rate", "Neonatal", "Neurologic", "Nicotiana", "Passive Immunization", "Patients", "Pharmaceutical Preparations", "Pharmacology and Toxicology", "Phase", "Phase I Clinical Trials", "Predisposition", "Production", "Proteins", "Research Design", "Respiratory syncytial virus", "Rodent", "Running", "Safety", "Scientist", "Simplexvirus", "Small Business Innovation Research Grant", "System", "Techniques", "Testing", "Tissues", "Toxicokinetics", "Virus", "Work", "cross reactivity", "efficacy study", "manufacture", "member", "monoclonal antibody production", "mortality", "mouse model", "mutant", "neonatal infection", "neonatal mice", "phase 1 study", "product development", "small molecule", "trial planning", "vaginal microbicide", "virology" ], "approved": true } }, { "type": "Grant", "id": "15771", "attributes": { "award_id": "1R01AI185685-01A1", "title": "Multi Parametric Total-Body Imaging of Immune Activation in Post Acute Sequelae of SARS-CoV-2 (PASC)", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 32843, "first_name": "JOSEPH J", "last_name": "BREEN", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2029-07-31", "award_amount": 808672, "principal_investigator": { "id": 32844, "first_name": "Negar", "last_name": "Omidvari", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2639, "ror": "", "name": "UNIVERSITY OF CALIFORNIA AT DAVIS", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Post-acute sequelae of SARS-CoV-2 infection (PASC) is a persisting health challenge characterized by a range of symptoms affecting multiple organ systems, which continues to impact approximately 10% of COVID-19 survivors. Multiple, potentially overlapping, mechanisms have been identified that may play a role in PASC. However, with no effective preventative measures or treatments, there is a critical unmet need for understanding the pathophysiology of PASC; as previous studies, often limited by focus on peripheral blood biomarkers only or confined to single organ systems, have not sufficiently and quantitatively investigated the multisystemic and immune-related complexities of this condition in non-blood tissue. The long-term objective of this project is to bridge this knowledge gap by providing insight into the immune and systemic manifestations of PASC, through the innovative use of total-body dynamic positron emission tomography (PET) with the 18F-AraG radiotracer, which particularly offers selectivity towards activated T cells. To achieve this, we will use the dynamic PET images obtained from a high-sensitivity total-body PET scanner to develop, optimize, and validate a kinetic model for 18F-AraG in different anatomical sites and tissue types for multi parametric quantification of uptake. We expect that this will not only improve the quantification accuracy compared to standard static imaging, but also can shed light on the underlying mechanisms of uptake. The multi parametric imaging will be firstly used to identify sites of immunological perturbation in PASC patients, offering a total-body view of tissue-level manifestations of PASC. For this, we will compare the kinetic parameters of different tissues between symptomatic PASC participants and a control group consisting of individuals with a complete COVID-19 recovery. Second, we will integrate the multiparametric imaging data with peripheral blood assays, aiming to assess the correlations between certain 18F-AraG kinetic parameters and biomarkers of inflammation, immune dysregulation, and endothelial dysfunction in peripheral blood. Particularly, to identify vascular alterations in tissue and their association with endothelial markers in blood, we will use vascular permeability modeling to estimate the blood flow in different tissues from the early frames of the kinetic data. Third, we will employ a longitudinal design to quantify changes in 18F-AraG kinetic parameters and correlate them with evolving PASC symptom profiles over time. We will include two follow-up scans of the PASC participants at 4 months and 8 months after the baseline scans with systematic symptom assessments, focusing on individual patient trajectories. Through this, we expect to establish a direct and meaningful connection between molecular imaging data and clinical manifestations. In summary, the incorporation of cutting-edge imaging technology with quantitative modeling techniques for non- invasive evaluation of total-body immune response, combined with the longitudinal design of the study promises to provide unprecedented insights into this complex condition and would extend well beyond the confines of the PASC condition, offering frameworks and tools that could as well be used for other post-viral conditions.", "keywords": [ "2019-nCoV", "Affect", "Anatomy", "Autoimmunity", "Autopsy", "Biological Assay", "Biological Markers", "Biopsy", "Blood", "Blood Vessels", "Blood coagulation", "Blood flow", "Blood specimen", "Body System", "COVID-19", "COVID-19 patient", "COVID-19 survivors", "Cardiovascular system", "Cells", "Clinical", "Complex", "Control Groups", "Controlled Study", "Data", "Endocrine", "Endothelium", "Evaluation", "Functional disorder", "Guanine", "Health", "Image", "Imaging Techniques", "Imaging technology", "Immune", "Immune response", "Immunologic Markers", "Immunologics", "Individual", "Inflammation", "Kinetics", "Knowledge", "Latent virus infection phase", "Link", "Long COVID", "Masks", "Measures", "Modeling", "Monitor", "Organ", "Outcome", "Participant", "Patients", "Persons", "Phenotype", "Positron-Emission Tomography", "Post-Acute Sequelae of SARS-CoV-2 Infection", "Preventive measure", "Preventive treatment", "Quality of life", "Questionnaires", "Radiopharmaceuticals", "Recovery", "Regional Anatomy", "SARS-CoV-2 infection history", "Sampling", "Scanning", "Site", "Symptoms", "System", "T-Cell Activation", "Techniques", "Technology", "Time", "Tissues", "Tracer", "Vascular Permeabilities", "Viral", "Virus Diseases", "acute COVID-19", "blood-based biomarker", "endothelial dysfunction", "follow-up", "forging", "gastrointestinal", "health care burden", "healthy volunteer", "imaging agent", "imaging approach", "imaging biomarker", "imaging study", "immune activation", "immune imaging", "improved", "individual patient", "innovation", "insight", "kinetic model", "longitudinal design", "molecular imaging", "multiparametric imaging", "neuropsychiatry", "pandemic response", "peripheral blood", "personalized diagnostics", "personalized intervention", "personalized medicine", "pre-pandemic", "predictive marker", "pulmonary", "quantitative imaging", "radiotracer", "reactivation from latency", "sample collection", "tool", "treatment strategy", "uptake" ], "approved": true } }, { "type": "Grant", "id": "15770", "attributes": { "award_id": "1R21AI194218-01", "title": "Genomic Surveillance of Mpox through the Development of a Wastewater Intelligence Model and Data Analytics Platform", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 32841, "first_name": "JANE M", "last_name": "KNISELY", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-07", "end_date": "2027-07-31", "award_amount": 416625, "principal_investigator": { "id": 32842, "first_name": "Edwin C.", "last_name": "Oh", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2638, "ror": "", "name": "UNIVERSITY OF NEVADA LAS VEGAS", "address": "", "city": "", "state": "NV", "zip": "", "country": "United States", "approved": true }, "abstract": "A critical challenge in pandemic preparedness is the rapid identification of viral outbreak sources and tracking mutations that lead to new variants. Current public health surveillance methods, relying on resource-intensive laboratory testing of patient specimens, often yield incomplete data due to underreporting. The recent mpox outbreak in the Democratic Republic of the Congo—with over 22,000 suspected cases since January 2023 and the emergence of a new strain (clade 1b)—underscores the need for more effective surveillance tools. To address these limitations, we and others have developed wastewater approaches to screen municipal sewage for viral levels and variants. This method capitalizes on the shedding of pathogens like SARS-CoV-2 and mpox into sewer systems through bodily fluids, providing a comprehensive, real-time snapshot of community infection levels and viral evolution. Over the last five years, our team has built and implemented a comprehensive wastewater COVID-19 surveillance program that includes a community engagement responsive element and serves 2.4 million residents and 50 million annual tourists in Southern Nevada. In Summer 2022, we adapted this program to pilot a study tracking the clade IIb mpox outbreak in Las Vegas. Building on these achievements and developing novel reagents for clades I and II, we have a time-sensitive opportunity to test our central hypothesis: that enhanced wastewater surveillance, coupled with new computational tools, can enable rapid detection of mpox variants from both clades, facilitate assessment of antiviral drug efficacy, and inform strategic prioritization of vaccination sites. This high-risk, high-reward proposal extends our previous successful approaches with SARS-CoV-2, influenza, and drug use in wastewater, potentially breaking new ground in mpox research. Our proposal directly responds to the 2022 and 2024 mpox public health emergency of international concern declarations and aligns with NIAID's 2024 mpox research agenda. The identification of even a single mpox outbreak or treatment-resistant strain through our wastewater studies would significantly advance innovative research in genomic epidemiology and public health surveillance, potentially transforming our approach to managing emerging infectious diseases.", "keywords": [ "2019-nCoV", "Achievement", "Address", "Anti-viral Agents", "Area", "Biological Sciences", "Body Fluids", "COVID-19 surveillance", "Clinical", "Communities", "Coupled", "DNA", "Data", "Data Analytics", "Databases", "Democratic Republic of the Congo", "Detection", "Development", "Disease Outbreaks", "Dose", "Drug usage", "Early Diagnosis", "Effectiveness", "Elements", "Emerging Communicable Diseases", "Ensure", "Evolution", "Genome", "Genomics", "Hour", "Human", "Individual", "Infection", "Influenza", "Intelligence", "International", "Intervention", "Laboratories", "Linear Regressions", "Location", "Methods", "Modeling", "Monitor", "Monkeypox", "Monkeypox virus", "Municipalities", "Mutation", "National Institute of Allergy and Infectious Disease", "Patients", "Pilot Projects", "Plants", "Population Surveillance", "Public Health", "Reagent", "Research", "Resources", "SARS-CoV-2 genome", "SARS-CoV-2 variant", "Sampling", "Sewage", "Site", "Source", "Specimen", "Surveillance Methods", "Surveillance Program", "System", "Testing", "Time", "Vaccination", "Vaccines", "Variant", "Viral", "analysis pipeline", "clinical sequencing", "community engagement", "computational pipelines", "computerized tools", "drug efficacy", "emerging pathogen", "genome sequencing", "genomic data", "genomic epidemiology", "genomic variation", "health equity promotion", "high reward", "high risk", "innovation", "insight", "novel", "pandemic preparedness", "pathogen", "programs", "public health emergency", "rapid detection", "resistant strain", "response", "southern nevada", "tool", "transmission process", "urban area", "viral DNA", "viral detection", "viral outbreak", "wastewater samples", "wastewater surveillance", "whole genome" ], "approved": true } }, { "type": "Grant", "id": "15769", "attributes": { "award_id": "1K23HL181397-01", "title": "Optimal Ventilator Management in Patients with ARDS on ECMO", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Heart Lung and Blood Institute (NHLBI)" ], "program_reference_codes": [], "program_officials": [ { "id": 32586, "first_name": "ROYA", "last_name": "KALANTARI", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2030-07-31", "award_amount": 178846, "principal_investigator": { "id": 32840, "first_name": "Mazen Faris", "last_name": "Odish", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2637, "ror": "", "name": "UNIVERSITY OF CALIFORNIA, SAN DIEGO", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Research Plan: Acute respiratory distress syndrome (ARDS) is a severe and common condition that affects 10% of patients in the intensive care unit (ICU), and was a major cause of morbidity and mortality during the COVID-19 pandemic. While mechanical ventilation is often necessary for ARDS, it can also induce additional lung injury known as ventilator induced lung injury (VILI). VILI may be minimized by using low tidal volumes/driving pressure and with positive end expiratory pressure (PEEP). Some patients with severe and refractory ARDS require veno-venous extracorporeal membrane oxygenation (V-V ECMO), the highest level of life support which provides oxygen and removes carbon dioxide from the blood using an external device. A major benefit of ECMO is thought to be the ability to minimize VILI; however, the optimal ventilator settings for patients with ARDS on ECMO are not known. Current guidelines use a one-size-fits-all approach. Our central hypothesis is that personalized PEEP adjusted by measuring intrathoracic pressures via esophageal manometry (Pes) will decease VILI as assessed by biomarkers of inflammation (main outcomes IL-6 and sRAGE). To carry out these aims, we plan to prospectively randomize 62 patients with ARDS on V-V ECMO and neuromuscular blockade and perform serial biomarker measurements with PEEP of 10 cmH2O (ECMO guidelines) vs. PEEP guided by esophageal manometry. In addition to biomarkers of VILI, we will assess differences in other physiological outcomes including pulmonary mechanics and gas exchange. Although this proposal focuses on patients on ECMO, we believe the knowledge gained will have relevance for all patients with ARDS. Career Development Plan: The goal of the PI, Dr. Mazen Odish, is to personalize ARDS and ventilator strategies for those on ECMO based on physiology and biomarkers. The PI has an interest in applied physiology and critical care, this award will help him refine these skills and develop new skills in clinical trials, statistics, and patient-oriented research, to test rigorously methods to care for critically ill patients with ARDS with or without ECMO. To obtain these new skills Dr. Odish and his excellent and multi-disciplinary mentoring/advisory team (led by Drs. Owens and Malhotra, plus outstanding statistical and methodologic support) has three main training goals. 1) Pulmonary mechanics and biomarkers during ARDS, 2) control of breathing and measurement of work of breathing during ARDS/mechanical ventilation, and 3) clinical trial design and statistical training. These training activities are tailored for the PI to achieve his goals and maximize career development towards becoming an independent physician scientist. Furthermore, his structured course work will lead to a Masters of Advanced Studies in Clinical Research. Dr. Odish is at the right place and time in his career to align his clinical expertise in ECMO and ARDS with his research goals to understand optimal ventilator settings and therapies. Eventually his work and new skill set may improve the lives of all people suffering from respiratory illness.", "keywords": [ "Acute Respiratory Distress Syndrome", "Advisory Committees", "Affect", "Arteries", "Atelectasis", "Automobile Driving", "Award", "Biological Markers", "Blood", "Body Weight", "Breathing", "COVID-19 pandemic", "Carbon Dioxide", "Clinical", "Clinical Research", "Clinical Trials", "Clinical Trials Design", "Critical Care", "Critical Illness", "Development Plans", "Devices", "Esophagus", "Extracorporeal Membrane Oxygenation", "Functional disorder", "Gases", "Goals", "Guidelines", "Heart and Lung machine", "Heterogeneity", "Hour", "Hypoxemia", "Induction of neuromuscular blockade", "Inflammation", "Injury", "Intensive Care Units", "Interleukin-6", "Knowledge", "Life", "Lung", "Lung Compliance", "Manometry", "Measurement", "Measures", "Mechanical ventilation", "Mechanics", "Mediator", "Mentors", "Meta-Analysis", "Methodology", "Methods", "Morbidity - disease rate", "Multiple Organ Failure", "Organ", "Outcome", "Oxygen", "Patient Care", "Patients", "Persons", "Physicians", "Physiological", "Physiology", "Positive-Pressure Respiration", "Process", "Prone Position", "Pulmonary Gas Exchange", "Randomized", "Recommendation", "Recording of previous events", "Refractory", "Research", "Research Design", "Resolution", "Respiratory Failure", "Respiratory System", "Respiratory physiology", "Rest", "Risk", "Scientist", "Stress", "Structure", "Testing", "Tidal Volume", "Time", "Training", "Training Activity", "Venous", "Ventilator", "Ventilator-induced lung injury", "Vision", "Work", "Work of Breathing", "career", "career development", "esophagus pressure", "healing", "improved", "improved outcome", "individual patient", "interest", "lung injury", "mortality", "multidisciplinary", "patient oriented research", "personalized approach", "pressure", "prevent", "primary outcome", "prospective", "pulmonary", "radiological imaging", "respiratory", "skills", "soluble RAGE", "statistics", "theories", "ventilation" ], "approved": true } }, { "type": "Grant", "id": "15768", "attributes": { "award_id": "75N92023D00011-0-759202500001-1", "title": "COPD GENE - GENETIC EPIDEMIOLOGY OF COPD - TASK AREA A: YEAR 3 - AUGUST 10, 2025 - AUGUST 9, 2026", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Heart Lung and Blood Institute (NHLBI)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2025-08-10", "end_date": "2026-08-09", "award_amount": 9292344, "principal_investigator": { "id": 32839, "first_name": "LEE S", "last_name": "NEWMAN", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2636, "ror": "", "name": "NATIONAL JEWISH HEALTH", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "Genetic Epidemiology of COPD (COPDGene) is a multi-site longitudinal cohort study of current and former smokers to better understand risk factors, natural history, and genetic contributions of chronic obstructive pulmonary disease (COPD) as well as other smoking-related diseases. The purpose of this acquisition is to fund a 15-year follow-up in-person clinical visit (Visit 4) of this cohort, to be re-enrolled from approximately 19 active Clinical Study Centers. A Visit 4 of COPDGene subjects is needed to identify clinical, physiological, imaging, and Omics determinants of COPD and other disease progression in elderly subjects, to assess the impact of COVID-19 on COPD and other disease progression, and to discover determinants of severe COPD development in subjects with preserved ratio, impaired spirometry (PRISm). The acquisition will also support the maintenance of previously collected data and biospecimens, regulatory oversight of the study, and analysis of study data and study biospecimens. The goal of COPDGene is to use extensive longitudinal imaging, physiology, and Omics molecular data in combination with genetics in the COPDGene cohort to identify high-risk subgroups with distinct diagnostic, prognostic, and therapeutic implications. COPDGene has been funded for 15 years through grants and cooperative agreements awarded by NHLBI to National Jewish Health and Brigham and Women’s Hospital. Grant applications for the three Phases of COPDGene [Phase 1: baseline visit (“Visit 1”); Phase 2: five year follow-up (“Visit 2”); Phase 3: ten year follow-up (“Visit 3”)] were all submitted to the parent NIH R01 Funding Opportunity Announcement. Study investigators originally recruited 10,198 current or former smokers in Phase 1. Including nonsmoking controls from both Phase 1 and Phase 2, COPDGene has recruited a total 10,718 subjects all of whom have been extensively phenotyped clinically and radiologically. Additional data collected on these participants include whole genome sequencing as well as RNA sequencing, proteomics, metabolomics, and DNA methylation data from collected blood samples. Investigators have published more than 450 publications, the vast majority of which were peer-reviewed, using COPDGene data. COPDGene also serves as a parent study for many ancillary studies, using public or private funding, a subset of which have collected additional data on all or a subset of participants. COPDGene is overseen by an NHLBI-convened Observational Study Monitoring Board (OSMB). The Visit 4 (15-year follow-up) evaluations will include, where possible, lung function tests (spirometry), questionnaires (including COVID-19 assessment), chest computerized tomography (CT), other functional assessments (e.g., six minute walk distance), and collection and storage of biospecimens from 3,500 of the original 10,718 COPDGene subjects. In addition, this acquisition will support continuation of semi-annual long-term follow-up of the COPDGene cohort and other contact with the cohort as needed, oversight of clinical sites and human subjects protection, maintenance of the database and biobank, continued coordination with NIH and NHLBI data resources, activities relevant to the data management and sharing plan, analysis of data, travel to meetings, and publication costs.", "keywords": [ "Address", "Adverse event", "Ancillary Study", "Annual Reports", "Applications Grants", "Archives", "Area", "Award", "Bioinformatics", "Biological Markers", "Biological Specimen Banks", "Blood specimen", "Bronchodilator Agents", "COVID-19", "COVID-19 impact", "Cause of Death", "Certification", "Cessation of life", "Characteristics", "Chest", "Chronic Obstructive Pulmonary Disease", "Clinical", "Clinical Data", "Clinical Research", "Clinical/Radiologic", "Collaborations", "Collection", "Communication", "Communities", "Compensation", "Computer Security", "Contractor", "Contracts", "DNA Methylation", "Data", "Data Analyses", "Data Coordinating Center", "Data Science", "Data Security", "Data Set", "Databases", "Development", "Diagnostic", "Diffusion", "Disease Progression", "Documentation", "Educational workshop", "Elderly", "Electronics", "Enrollment", "Ensure", "Epidemiology", "Evaluation", "Event", "Funding", "Funding Opportunities", "Future", "Genes", "Genetic", "Genomics", "Goals", "Grant", "Health", "Hospitals", "Image", "Impairment", "Information Systems", "Institutional Review Boards", "International", "Internet", "Jews", "Journals", "Laboratories", "Link", "Long-term Follow-up", "Longitudinal cohort study", "Maintenance", "Manuscripts", "Measures", "Medical History", "Metadata", "Methods", "Molecular", "Monitor", "Names", "National Heart Lung and Blood Institute", "Natural History", "Observational Study", "Outcome", "Oxygen", "Parents", "Participant", "Peer Review", "Persons", "Phase", "Physical Performance", "Physiological", "Physiology", "Policies", "Privatization", "Procedures", "Proteomics", "Protocols documentation", "PubMed", "Publications", "Publishing", "Pulmonary Emphysema", "Pulmonary function tests", "Quality Control", "Quality of life", "Questionnaires", "Recommendation", "Reporting", "Research", "Research Personnel", "Resolution", "Resources", "Risk Factors", "SARS-CoV-2 infection", "Scanning", "Schedule", "Scientist", "Site", "Specific qualifier value", "Spirometry", "Standardization", "Subgroup", "Support Contracts", "System", "Teleconferences", "Telephone", "Testing", "Therapeutic", "Time", "Tobacco use", "Training", "Trans-Omics for Precision Medicine", "Travel", "U-Series Cooperative Agreements", "United States National Institutes of Health", "Update", "Vaccination", "Visit", "Walking", "Woman", "Work", "X-Ray Computed Tomography", "adjudication", "biobank", "catalyst", "clinical ce" ], "approved": true } }, { "type": "Grant", "id": "15767", "attributes": { "award_id": "1R35GM160163-01", "title": "Scalable and Epidemiologically Interpretable Phylodynamics to Recover Heterogeneous Transmission Dynamics", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of General Medical Sciences (NIGMS)" ], "program_reference_codes": [], "program_officials": [ { "id": 32565, "first_name": "GUOQIN", "last_name": "YU", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-08-01", "end_date": "2030-06-30", "award_amount": 410000, "principal_investigator": { "id": 32838, "first_name": "Nicola Felix", "last_name": "Mueller", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2635, "ror": "", "name": "UNIVERSITY OF CALIFORNIA, SAN FRANCISCO", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "As pathogens are transmitted between individuals, they accumulate mutations, leaving a footprint of the transmission history in the pathogen genomes. Using phylogenetic methods, we can reconstruct the transmission history connecting individual cases from these genomes, by reconstructing the relationships of the pathogens. We can then infer population-level transmission dynamics, from the ancestral relationships of the pathogens, or phylogenies, using phylodynamic methods. Infectious disease transmission and disease burden are highly heterogeneous, differing between neighborhoods, across age, and socioeconomic groups, and racial and ethnic lines. This heterogeneity means that it is crucial to a) be able to illuminate differential disease burdens and b) account for these heterogeneities when modeling or forecasting infectious disease outbreaks. Traditional approaches based on reported caseloads are often insufficient for capturing the full scope of highly heterogeneous transmission dynamics. Phylodynamics offers a potential solution, as it infers transmission dynamics from the connectivity of cases, providing an opportunity to disentangle these complex patterns. However, limitations in our available toolbox prevent us from fully utilizing the vast availability of pathogen genomes to study these complex transmission dynamics, as current phylodynamic approaches suffer from multiple challenges. With the advent of widely available sequencing, phylodynamic tools are not computationally efficient enough to analyze the amounts of data generated at the granular scales crucial to understanding transmission dynamics. Additionally, the model parameters need to be epidemiologically interpretable to be actionable. In this project, we seek to address these two points by developing novel approaches to reconstruct transmission dynamics from pathogen sequence data. We will develop novel phylodynamic tools to reconstruct transmission dynamics at a granular scale by integrating neural networks into phylodynamic likelihood calculations that we show in preliminary results to dramatically improve computational efficiency and scalability. Phylodynamic methods are parameterized by more or less abstract parameters that either have no direct epidemiological meaning or are contingent on idealized assumptions about disease spread. We will establish how and when current approaches return biased results when reconstructing city-scale transmission dynamics, describe how they can be used to estimate actual disease burden, and test them using SARS-CoV-2 sequence data collected by Kaiser Permanente Southern California (KPSC) and in the UK over the pandemic. Finally, we will develop ways to quantify the factors influencing disease burden, such as geography, age, and socioeconomics. We will apply these tools to KPSC SARS-CoV-2 data, where we can access rich patient metadata to study these patterns. Our overarching goal is to utilize phylodynamic inference of heterogeneous transmission dynamics to parameterize complex infectious disease dynamic models and improve prediction accuracy.", "keywords": [ "2019-nCoV", "Address", "Age", "California", "Cities", "Communicable Diseases", "Complex", "Data", "Disease", "Disease Outbreaks", "Epidemiology", "Ethnic Origin", "Genome", "Geography", "Goals", "Guidelines", "Heterogeneity", "Individual", "Metadata", "Methods", "Modeling", "Mutation", "Neighborhoods", "Patients", "Pattern", "Phylogenetic Analysis", "Phylogeny", "Population", "Race", "Recording of previous events", "Reporting", "Testing", "Viral", "burden of illness", "disease transmission", "genome sequencing", "improved", "neural network", "novel", "novel strategies", "pandemic disease", "pathogen", "pathogen genome", "prevent", "socioeconomics", "tool", "transmission process" ], "approved": true } } ], "meta": { "pagination": { "page": 3, "pages": 1405, "count": 14046 } } }