School of Medicine


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  • Gentaro Ikeda

    Gentaro Ikeda

    Instructor, Medicine - Cardiovascular Medicine

    BioDr. Ikeda is a physician-scientist who develops innovative diagnostic and therapeutic modalities for patients with cardiovascular disease. Based on his clinical experience as a cardiologist, he has become aware of major clinical shortcomings, specifically in the current pharmaceutical therapies for myocardial infarction (MI) and chronic heart failure (HF). Some evidence-based drug therapies, including β-blockers, ivabradine, and renin-angiotensin-aldosterone antagonists are difficult to apply to critical patients due to adverse side effects. Drugs that have shown efficacy in basic animal experiments have failed to show significant benefits in clinical trials. To address these problems, he moved to academia to conduct translational research. During his graduate training in the Egashira Lab, he focused on drug delivery systems (DDS) that target mitochondria in animal models of MI. He obtained advanced skills in molecular biology, mitochondrial bioenergetics, and animal surgery. He realized the importance of translational research and the great potential of DDS to overcome many clinical problems. He developed nanoparticle-mediated DDS containing cyclosporine for the treatment of patients with MI. He published a first-author paper and received academic awards for his novel science. Since becoming a postdoctoral fellow in the Yang Lab, he has continued to build upon his previous training in translational research. He is currently developing an innovative therapy, namely, extracellular vesicles-mediated mitochondrial transfer for mitochondria-related diseases such as heart failure and mitochondrial disease.

  • John P.A. Ioannidis

    John P.A. Ioannidis

    Professor of Medicine (Stanford Prevention Research), of Epidemiology and Population Health and by courtesy, of Statistics and of Biomedical Data Science

    Current Research and Scholarly InterestsMeta-research
    Evidence-based medicine
    Clinical and molecular epidemiology
    Human genome epidemiology
    Research design
    Reporting of research
    Empirical evaluation of bias in research
    Randomized trials
    Statistical methods and modeling
    Meta-analysis and large-scale evidence
    Prognosis, predictive, personalized, precision medicine and health
    Sociology of science

  • Haruka Itakura, MD, PhD

    Haruka Itakura, MD, PhD

    Assistant Professor of Medicine (Oncology)

    BioDr. Itakura is an Assistant Professor of Medicine (Oncology) in the Stanford University School of Medicine and practicing oncologist at the Stanford Cancer Center with background in biomedical informatics. She is a physician-scientist whose research mission is to drive medical advances at the intersection of cancer and data science research. Specifically, she aims to innovate state-of-the-art technologies to extract clinically useful knowledge from heterogeneous multi-scale biomedical data to improve diagnostics and therapeutics in cancer. She is a board-certified hematologist-oncologist and informaticist with specialized training in basic science, health services, and translational research. Her clinical background in oncology and PhD training in Biomedical Informatics position her to develop and apply data science methodologies on heterogeneous, multi-scale cancer data to extract actionable knowledge that can improve patient outcomes. Her ongoing research to develop and apply cutting-edge knowledge and skills to pioneer new robust methodologies for analyzing cancer big data is being supported by an NIH K01 Career Development Award in Biomedical Big Data Science. Her research focuses on developing and applying machine learning frameworks and radiogenomic approaches for the integrative analysis of heterogeneous, multi-scale data to accelerate discoveries in cancer diagnostics and therapeutics. Projects include prediction modeling of survival and treatment response, biomarker discovery, cancer subtype discovery, and identification of new therapeutic targets.