Investigators across UCSF are engaged in a wide range of precision medicine research. The compilation captured here can be searched by keywords or topics, to be included, a project must fulfill these criteria.
If you have a precision medicine project you think should be listed or have a question about a specific project please send us an email.
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Global Preterm Birth Initiative
The Global Preterm Birth Initiative at UCSF Benioff Children’s Hospitals focuses on biological, behavioral, and social factors that drive premature birth, the initiative seeks to define cultural and social barriers to the adoption of healthy practices, and to contribute to the development of new treatments and diagnostic tools.
Topics: children's precision medicine, population health sciences, women's precision medicine
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The Health eHeart study uses mobile and other technologies to collect real-time data on heart patients, transforming the knowledge gained through the famed Framingham Study to provide a daily portrait of heart health. The data are used to help patients and their providers better understand each individual’s progression, and will create a pool of data that helps researchers get a better picture of heart disease overall.
Topics: digital health
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Improving precision medicine for breast cancer in Latinas: A multi-tiered approach
The objective of this TRANSPERS project is to examine payer coverage and clinical decision-making/access to the use of cancer risk multigene tests (panels and sequencing tests) in the Latina population within the state of California.
Topics: cancer precision medicine, health economics and policy, omics, population health sciences, TRANSPERS
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Developed and led by a comprehensive group of researchers, faculty and staff, The Information Commons is a fast, shared repository of UCSF clinical data, clinical notes, related basic science and population data, and supporting tools on Spark, a next generation Apache-based open-source platform developed at UC Berkeley.
Topics: computational health sciences, knowledge network
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Integrating Genomics and Imaging to Predict Pain Progression
An inter-disciplinary team is developing a multi-modal framework integrating genomics, imaging, and clinical data to develop novel graph-based deep learning predictive models enabling the extraction of latent multi-domain signatures of unique clinical progression trajectories and prognose subject’s future incidence of joint pain. While integrating genomics with imaging and clinical information will shed light on the contribution of heritability in joint pain and contribute to the discovery of novel structural and functional joint imaging pain biomarkers, inconsistencies between joint abnormalities and patient experience may still be observed.
Topics: artificial intelligence, imaging
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Machine and Deep Learning Applied to MR Images to Characterize Degenerative Joint Disease
Development of algorithms for advanced computer vision and deep learning for improving the usage of non-invasive imaging as diagnostic and prognostic tools of degenerative joint disease. Their lab has developed deep learning convolutional neural networks for musculoskeletal tissue segmentation, abnormality detection, and severity staging covering a diverse range of imaging modalities and diseases – including bone fractures, soft tissue degeneration, and sports injuries.
Topics: artificial intelligence, imaging
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Machine Learning for Interpreting Rare Variation in Comprehensive Newborn Screening and Pharmacogenetics
In California 500,000 babies are born each year, some of whom have genetic mutations that cause disease or altered responses to medications. Recognizing which genetic variants cause problems is surprisingly difficult–harder than finding a needle in a haystack, where once you find the needle, you know it’s different from the hay. The team will search for the mechanisms by which variants impact the function of genes. With experts in biology, computer science, medicine, and ethics from Stanford, UCSF, and Berkeley this project, funded by the Chan Zuckerberg Biohub, will focus on serious newborn diseases and on gene variants that require customized drug choice and dosage.
Topics: artificial intelligence, children's precision medicine, ethics and engagement, omics
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Mapping Glioblastoma Evolution Under Therapy
The goal of this project is to investigate evolutionary dynamics between primary and recurrent GBM and concomitant changes in infiltrating immune cells, using RNA sequencing and UCSF500 Gene Panel results. This will be the first study to compare GBM biospecimens at both diagnosis and recurrence with a significant sample size.
Topics: cancer precision medicine
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Marcus Program in Precision Medicine Innovation
The Marcus Program in Precision Medicine Innovation (MPPMI) seeks to fuel innovation in precision medicine by fostering creative, high risk, high impact team science projects anchored in basic science and extending into the precision medicine continuum toward improved patient outcomes. Funding has been generously provided by George and Judy Marcus to drive innovative and collaborative efforts between basic researchers and clinical or social/behavioral/population scientists, which are essential to making precision medicine a reality.
Topics: basic discovery
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The MS Bioscreen is a data infrastructure platform that gathers all relevant MS data from different sources, including clinical, imaging, and biomarker information, visually represents the disease course of an individual with MS from a front-end interface, and frames this course within the context of a large cohort of patients treated according to contemporary standards.
Topics: clinical discovery, precision neuroscience
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Neighborhood Explorer allows searching SPOKE for a node of interest, such as a specific drug compound, gene, or protein, and seeing what other nodes are in its immediate connectivity neighborhood, such as related diseases, side effects, pathways, and other compounds, genes, or proteins. The search can be limited by filtering to specific node and edge types, and by edge value (for example, compound-treats-disease edges at least clinical trial phase 3 or FDA-approved).
Topics: knowledge network
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Next Generation CAR T Cells for Glioblastoma
The goal of this project is to develop next-generation CAR T cell therapies for treatment of GBM, using combinatorial antigen recognition to achieve precision tumor targeting. Upon completion of current preclinical studies, the project will prepare for the first-in-human clinical trial.
Topics: cancer precision medicine
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Pilot Study Testing Feasibility of Individualized Therapy for Recurrent Glioblastoma
The goal of this project is to assess the feasibility, safety, and efficacy of individualized, patient-specific treatment regimens for recurrent GBM. Individualized treatment regimens are formulated on the basis of gene expression data from the UCSF500 Gene Panel, whole genome, and RNA sequencing. Additional aims of this project include the generation of preclinical models to test selected agents to predict patient response, as well as evaluation of hyperpolarized 13C imaging to assess early response to treatment.
Topics: cancer precision medicine
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Precision Genomics in the WISDOM Pragmatic Clinical Trial: An ‘Embedded’ ELSI Study of Risk-based Breast Cancer Screening
Precision genomic screening raises multiple ELSI (ethical, legal, social, and policy) concerns. The purpose of the project is to follow and assess the ELSI issues that accompany a pioneering randomized pragmatic clinical trial of a risk-based approach to breast cancer screening. The WISDOM (Women Informed to Screen Depending on Measures of Risk) study is a clinical trial that uses genomics to determine the appropriate use of mammography, and other forms of breast cancer screening, across the population. The trial compares annual mammography to a “personalized” approach to screening, using factors like age, race, family history and health history combined with genetic testing to offer a recommendation for the frequency and type of breast cancer screening a woman should have.
Topics: ethics and engagement, omics, precision cancer medicine
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Precision Imaging of Cancer and Therapy Program
The PICT Program brings together basic, translational and clinical scientists in order to integrate cutting edge, multi-modality imaging into all aspects of patient care and cancer research. By using novel imaging technologies and sophisticated data analysis tools to elucidate the underlying mechanisms of malignant transformation and drug resistance.
Topics: artificial intelligence, imaging, precision cancer medicine