The goal of this project is to develop and populate a searchable database to collect clinical, pathologic, and genomic data from all patients with WHO grade IV glioblastoma (GBM). We seek to establish an actionable database of mutations (identified with the UCSF500 Cancer Panel) and drugs that may counteract the effects of those mutations to improve treatment of GBM.

Led by the National Institutes of Health (NIH), All of Us is an unprecedented effort to gather genetic, biological, environmental, health and lifestyle data from 1 million or more volunteer participants living in the United States. A major component of the federal Precision Medicine Initiative, the program’s ultimate goal is to accelerate research and improve health.  In California, the program has been implemented by the California Precision Medicine Consortium, which includes UCSF, UCSD, UCI, UCD, USC, and Cedars-Sinai Medical Center.

A new technology development grant from the NIH, as part of the HEAL Initiative and BACPAC consortium, aimed at improving treatments for chronic pain and curbing the rates of opioid use. The team bring together extensive expertise in MR bioengineering, advanced MRI data analysis, radiology, neuroscience, neurosurgery, orthopedic surgery, and multi-dimensional analytics to respond to the critical need for clarity in the etiologies of chronic back pain and other disorders of the spine.

BRIDGE is a SMART on FHIR application that launches from APeX and is already available in four pilot clinics: Autism, Geriatrics, Memory and Aging Center, and Multiple Sclerosis. Clinicians can click on a link from the patient encounter screen in APeX to launch the BRIDGE dashboard. A platform that allows for configuration of new clinic specific dashboards making use of our existing data integrations and widgets. The BRIDGE platform can also be extended to add additional data source integrations, algorithms and visualizations.

The objective of this TRANSPERS project is to assess payer coverage decisions and the economic value of two types of emerging genomic tests for disease management and screening: cfDNA and PRS tests. We will examine which cfDNA and PRS tests are covered and why, address the economic value of cfDNA and PRS tests, and compare evidence needs for payer coverage and economic value assessment across clinical scenarios and generalize our findings on evidence needs to other emerging clinical scenarios.

Cancer Cell Map Initiative (CCMI) is a collaboration between UCSF and UCSD that is studying complexes of biological molecules that include particular proteins mutated in cancer. Defining these complexes can reveal the biological processes and pathways affected by the mutation, and suggest targets for therapeutic intervention. The CCMI leverages advanced interaction mapping and computational facilities to generate, assemble and analyze cancer networks, focusing initially on had and neck squamous cell carcinoma and breast cancer. 

The UCSF Clinical Cancer Genomics Laboratory (CCGL) performs standard-of-care and advanced molecular testing for patients with cancer, and to provide special expertise in solid tumors.  The laboratory's diverse capabilities include targeted gene sequencing, microsatellite instability testing, fluorescence in situ hybridization (FISH), and next-generation sequencing (NGS).

The objective of this TRANSPERS project is to examine “coverage, price, and reimbursement” (“CPR”) for cancer risk multigene tests (panels and sequencing tests): what tests are covered by payers, why are tests covered or not covered, and how CPR influences testing decisions and practices in clinic settings.

Combining Deep Learning techniques with brain imaging to discover changes in brain metabolism predictive of Alzheimer’s disease (AD). The team trained a DL algorithm using more than 2,100 18-F-fluorodeoxyglucose PET scans from 1,002 patients – a dataset originating from the Alzheimer’s Disease Neuroimaging Initiative. After testing on an independent set of 40 scans from 40 patients never studied, the algorithm was able to predict every case that advanced to AD.

Developing an AI system for probabilistic brain MRI diagnoses, this system computationally models a neuroradiologist’s process of image interpretation by using a convolutional neural network for detection of imaging abnormalities, image processing for quantitative descriptions of these abnormalities in terms of signal, location, and volumetric features ,and a probabilistic integration of these derived features with clinical features in the form of Bayesian inference, ultimately arriving at a probability-ranked differential diagnosis.

The objective of this TRANSPERS project is to develop conceptual frameworks and methodological approaches to examine the economic, financial/coverage, and policy implications of genetic testing for ADRD risk and conduct initial analyses in the following areas: coverage policies for ADRD genetic testing, role of physicians in managing patients who present their APOE DTC testing results, and economic value of ADRD genetic testing.

The goal of this project is to assess the safety and efficacy of a novel adeno-associated virus (AAV) gene therapy that stimulates the host immune system to target glioblastoma cells in preclinical animal models. 

The Genomic Medicine Initiative serves as a preeminent hub for innovative genetic diagnosis, counseling and testing, and spans pre-conception, pre-implantation, prenatal, neonatal, cancer, pediatric and adult conditions. The UCSF Genomic Medicine Initiative (GMI) has developed a CLIA-certified Whole Exome Sequencing (WES) protocol, applying cutting-edge sequencing and bioinformatics pipelines to diagnose complex clinical cases.

The objective of this TRANSPERS project is on analyzing evidence regarding exome sequencing from the perinatal period into early childhood through examining payer coverage, and payer decision-making and data integration across multi-CSER sites in a diverse population.

The goal of this project is to develop and populate a searchable database to collect clinical, pathologic, and genomic data from all patients with WHO grade IV glioblastoma (GBM). We seek to establish an actionable database of mutations (identified with the UCSF500 Cancer Panel) and drugs that may counteract the effects of those mutations to improve treatment of GBM.