Improving Quality of Life Cluster

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Precision Health Imaging and Genetics (PHIG)

One of the promises of precision medicine is that genomic data may better inform diagnosis and individualized treatment of patients with potential to develop specific disease states. Advances in multimodal medical imaging (computed tomography, magnetic resonance imaging) have become central to modern medicine and individualized therapy. While the genomics provide information about long-term traits of an individual, the medical imaging profiles the individual’s current state. The confluence of genomics and medical imaging hence will provide the necessary substrate to make precision health a reality. Researchers in this focus group work on multimodal imaging and genetics to drive clinical application of knowledge extracted from this aggregate data. Central to this proposal is the prediction of individuals’ health outcome based on quantitative characterization of imaging phenotypes using advanced imaging and large-scale genomic data.

Pharmaceutical Data Sciences

Despite innovative drug discovery and implementation of evidence-based treatment guidelines, sub-optimal medication response rates, in the range of 30% to 60%, are still observed in clinical practice for many conditions (e.g., depression, schizophrenia, rheumatoid arthritis, cardiovascular diseases, cystic fibrosis, and pain management, to name a few). Unfortunately, clinicians lack effective tools to predict drug responses and adverse drug reactions. Pharmacogenomics, including the millions of genes located within our microbiomes, has tremendous potential to improve treatment success and prevent unnecessary drug toxicity. A wealth of pharmacogenomics data is emerging; however, the best evidence is not effectively implemented in the clinical setting. To bridge this gap between the advances of pharmacogenomics discovery and clinical practice, and yield optimal outcomes for patients, the Skaggs School of Pharmacy and Pharmaceutical Sciences is creating a program at UCSD with informatics and computational innovations to collect, link, store, and analyze pharmacogenomics with related data (e.g., multi-omic, pharmacokinetic/dynamic, metabolomic, and other phenotypic information), and serve as a global resource center to integrate pharmacogenomics information into clinical decision-making tools. Pharmacogenomics information is inherently “big data”, sourced from whole genome sequencing or single gene analysis linking to related data sources. Informatics platforms to link these data with phenotypes for effective clinical translations do not exist. Collaborating with HDSI, we plan to design informatics tools, equipment, and projects to collect, link, store, and analyze pharmacogenomics and related data, facilitating and stimulating research that results in new clinical decision-making tools.