Research Projects

Treatment Effectiveness using Observational Data

We develop methods to overcome time-dependent confounding affected by previous treatments to conduct treatment comparative effectiveness studies using observational data. This includes novel marginal structural models, their associated theoretical properties, and tests of their performance using Monte Carlo simulation studies. We also research methods for combining longitudinal matching with missing data methods and optimal treatment regimes for rare disease studies with limited sample size. New models are applied to real data from observational cohort studies and electronic health record databases to answer important clinical questions for children and adults with kidney diseases. These projects are supported by an NIH/NIDDK-funded P50 grant and NIH/NIDDK-funded R01 grant and were previously supported by a NephCure pilot grant.

Biomarkers and Surrogate Endpoints

We research methods for biomarker and surrogate endpoint evaluation using observational data, including landmark analyses and causal mediation analyses. We lead statistical analyses for the Proteinuria and Other Biomarkers as Endpoints for Clinical Trials in Kidney Disease - Membranous Nephropathy (PARASOL-MN) project, in which we collaborate with data registries across the globe and stakeholders from academia, industry, and regulatory agencies to validate proteinuria and anti-phospholipase A2 receptor antibodies (PLA2R-Ab) as endpoints for use in clinical trials. These projects are supported by a NIH/NIDDK-funded R01 grant and the International Society of Glomerular Diseases.

Glomerular Disease

We collaborate with investigators in the Nephrotic Syndrome Study Network (NEPTUNE) and Cure Glomerulonephropathy Network (CureGN) to conduct clinical research in glomerular disease, including projects related to biomarker discovery, nocturnal blood pressure dysregulation, vaccine effectiveness, pregnancy, and skeletal outcomes. Our research team leads studies and develops new methods for analyses of time-varying biomarkers and kidney function outcomes. These projects are supported by multiple NIH/NIDDK-funded R01 grants, an NIH/NHLBI-funded R01 grant, and previously by the NIH/NIDDK-funded NEPTUNE U54 grant.

Pediatric Kidney Disease

We collaborate with pediatric nephrologists at the Children's Hospital of Philadelphia to conduct clinical research in pediatric kidney diseases, including acute kidney injury, chronic kidney disease, kidney transplant, and thrombotic microangiopathy. We lead research on kidney disease progression as part of the Preserving Kidney Function in Children with Chronic Kidney Disease (PRESERVE) study that leverages the PCORnet electronic health records database. These projects are supported by an NIH/NHLBI-funded R01 grant and the Penn-CHOP Kidney Innovation Center.

Computational Pathology in Kidney Diseases

We collaborate with nephropathologists, nephrologists, engineers, and molecular biologists to extract information from digital kidney biopsy images and identify important diagnostic, mechanistic, and prognostic imaging features. We develop novel high-dimensional statistical methods to analyze these data and use machine learning, computational image analysis, and bioinformatics tools to extract and integrate (bulk, single-cell, and spatial) transcriptomic, proteomic, imaging, and clinical data. These projects are supported by multiple NIH/NIDDK-funded R01 grants.