Translational Data Science Integrated Research Center
Leadership & Faculty
The Translational Data Science Integrated Research Center connects computational and quantitative scientists to biologists, clinicians and experimentalists.
Dr. Raphael Gottardo
Scientific Director, TDS IRC
Dr. Raphael Gottardo oversees the TDS IRC's vision and direction. Dr. Gottardo’s leadership helps position Fred Hutch as an incubator for new computational tools and methodologies and as a translator of data-driven discoveries into improved patient care.
Retrovirus-based gene transfer into hematopoietic stem cells has emerged as a viable treatment for genetic, malignant and infectious diseases with the potential to significantly decrease global disease burden.
The goal of the Berger laboratory is to enable precision medicine by systematically uncovering the molecular alterations in cancer, determining the function of these variant alleles, and understanding how these alleles modulate response to targeted or immune-based therapies.
The Clurman Lab studies how cell division is regulated in normal cells, and how abnormal control of cell division leads to cancer. They hope to use these mechanistic insights into tumor formation to develop new cancer treatment strategies.
Research focuses on statistical and computer modeling for policy development. A critical component of this work is the estimation of disease natural history and progression which then forms a substrate for modeling comparative effectiveness of alternative interventions.
Determining how changes in microbial communities impact human health; identifying, characterizing, and culturing microbes found in the human genital tract; and associating the reproductive tract microbiome with human disease.
Developing molecular diagnostic tests to detect and identify pathogens in immunocompromised hosts such as cancer patients.
The Galloway Lab studies the mechanisms by which human papillomaviruses contribute to cancer, with an emphasis on types most likely to progress to cervical cancer. They work to understand the natural history of genital HPV infections and why only a small subset of women infected with high-risk HPVs develop cancer.
Dr. Ghajar directs the Laboratory for the Study of Metastatic Microenvironments (LSM2). The goal of his research program is to understand how microenvironments within distant tissues regulate dormancy and growth of disseminated tumor cells (DTCs), and whether these niches convey chemoresistance to dormant DTCs. His belief is that solving these puzzles will allow the development of therapeutic regimens that eradicate dormant DTCs before they can develop into full-blown metastases.
Research focus includes vaccine clinical trials, the design and analysis of Phase I/II trials, for evaluating vaccine effects on immune responses; the design and analysis of Phase 2b/III trials, for evaluating vaccine efficacy, immune correlates, sieve analysis, and post-infection vaccine effects; general biostatistical methods research, such as survival analysis, causal inference, and evaluation of surrogate endpoints
Developing methods and tools for high-throughput, high-dimensional experiments with applications in vaccine research, immunology and immunotherapy; flow cytometry, peptide microarrays, next generation sequencing; Bayesian inference and computation and statistical computing
Research is focused on understanding the factors that control the formation of the hematopoietic stem cells, harnessing technologies to analyze gene activities across the many different cell types within the special hematopoietic stem cell niche and identifying specific biological signals that trigger the formation of blood stem cells to develop a system for generating and cultivating blood stem cells in the lab.
Research focus included the design and evaluation of vaccine field trials; modeling infectious disease dynamics and strategies for mitigation and control; causal inference in infectious diseases; and evaluating surrogates of protection.
Uses population genetic theory and high-throughput biological sequence analysis to study recent evolutionary history in humans and other species. A primary research interest is the evolution of mutagenesis, understanding the forces that control DNA replication fidelity, the mutational breakdown of established traits, and the ultimate origin of new traits.
Clinical and translational investigations relating to infections in immunocompromised hosts, with a focus on disease associations, risk stratification, and diagnostic strategies for viral infections in transplant recipients
Research focus includes statistical methods for bioassays (e.g., flow cytometry, sequencing); dynamic modeling of biological systems (e.g., multi-type cell populations, B-cell repertoire); nonparametric methods for supervised and unsupervised learning; stochastic processes (e.g., branching processes); algorithms for scalable data analysis.
The Kemp Lab seeks to identify the next generation of targeted anticancer agents. We use a combination of high throughput functional genomic and small molecule screens, and genomic analysis applied to a range of isogenic and patient derived tumor models. We are discovering and validating novel drug targets and therapeutic options for multiple solid tumor types including pancreatic, ovarian, head and neck and breast cancer.
The Kiem Lab is focused on research and clinical trials using stem cell biology and stem cell gene transfer with the goal of developing stem cell-based treatment strategies for patients with genetic or infectious stem cells. We are conducting studies using embryonic stem cells and induced pluripotent stem cells.
Research expertise is adaptive function estimation for genomic data and nonparametric function estimation and the analysis of high dimensional data, in particular as applied to genomic and proteomics data.
The MacPherson Lab is focused on understanding the mechanisms through which cancer-mutated genes drive tumorigenesis. The lab studies small cell lung cancer and other solid tumors. We generate novel genetically engineered mouse models that we use to interrogate the biology underlying major cancer driver genes. We are particularly interested in understanding epigenetic regulators that are genetically mutated in human tumors.
Research focuses on development and application of novel methods for identifying and characterizing antigen specific T cells in the context of cancer and chronic infection with the goal of identifying specific and accurate biomarkers of human health and disease based on antigen-specific T cells.
Genetic and molecular epidemiology, common complex diseases, including cancer, obesity, type 2 diabetes and cardiovascular diseases, as well as intermediate traits, including inflammation and metabolic measurements.
Studies focus on 1) understanding the roles of distinct T cell subsets in protective immunity to pathogens and tumors and on 2) the development and clinical application of adoptive T cell therapies for viral diseases and cancers, using unmodified and genetically modified antigen-specific T cells.
Interest in describing the quantitative and dynamical features of human pathogens and immune responses. Most of work to-date is on the pathogenesis of HSV-2 infection but also interested in applying models to optimize viral eradication strategies, and to use models to capture kinetic features of the human microbiome.
Develops statistical/computational methods and software packages for different types of omic data, including array or sequencing data for germline/somatic point mutations, copy number alterations, DNA methylation, and gene expression.
The Tapscott Lab studies gene transcription and expression in normal development and disease, with an additional emphasis on rhabdomysarcomas (cancers with characteristics of skeletal muscle) and human muscular dystrophies. Other research areas include gene and cell therapies for muscular dystrophy, and the biology of triplet repeats and their associated diseases.
Cancer care delivery research including, including comparative effectiveness, health care delivery, health disparities, and health outcomes, and in particular the utilization of large registry and administrative claims databases in conjunction with clinical trial data for secondary data analysis.
Clinical focus is treating patients with blood cancers such as leukemia, lymphoma, and multiple myeloma. Research is focused on cancer immunology, specifically the mechanisms and molecules that mediate graft-versus-host disease and graft-versus tumor.
Research focus: Estimating equation techniques, developing statistical methods for assessing genetic associations, gene-environment interactions including methods for haplotype-based methods, genome-wide association studies, time-varying phenotypes and sequence analysis
Research focus: Statistical methods for evaluating the ability of biomarkers or algorithms to identify cancer early, or signal disease prognosis; Statistical methods for family-based association studies
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