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Introduction

Informatics tools are essential to biomedical and health research and development. The field of cancer research, like most scientific disciplines, is facing an overwhelming deluge of data that are increasingly challenging to collate, store, access, analyze, and exchange. There is a particular need to integrate research and clinical data to facilitate personalized medicine approaches to cancer prevention and treatment (e.g., tailoring treatment based on an individual patient’s genetic makeup as well as that of the tumor) and to allow for more rapid learning from patient experiences (IOM, 2010, 2011). There is an increased national urgency to find solutions to support and sustain the cancer informatics ecosystem, especially in light of the recent devolution of the National Cancer Institute’s (NCI’s) Cancer Biomedical Informatics Grid® (caBIG) program.1

To further examine informatics2 needs and challenges for 21st century biomedical research, the National Cancer Policy Forum of the Institute of

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1 caBIG is discussed further in Chapter 2. Note that caBIG and Cancer Biomedical Informatics Grid are registered trademarks.

2 Biomedical informatics has been defined as the science that develops methods, techniques, and theories regarding how to use data, information, and knowledge to support and improve biomedical research, human health, and the delivery of health care services (http://www.amia.org/glossary). In the clinical arena, informatics is an applied and interdisciplinary field, at the intersection of information science, computer science, and clinical medicine, to provide improved patient care by harnessing and optimizing health information technology (Miriovsky et al., in press).



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1 Introduction Informatics tools are essential to biomedical and health research and development. The field of cancer research, like most scientific disciplines, is facing an overwhelming deluge of data that are increasingly challenging to collate, store, access, analyze, and exchange. There is a particular need to integrate research and clinical data to facilitate personalized medicine approaches to cancer prevention and treatment (e.g., tailoring treatment based on an individual patient's genetic makeup as well as that of the tumor) and to allow for more rapid learning from patient experiences (IOM, 2010, 2011). There is an increased national urgency to find solutions to support and sustain the cancer informatics ecosystem, especially in light of the recent devolution of the National Cancer Institute's (NCI's) Cancer Biomedical Informatics Grid (caBIG) program.1 To further examine informatics2 needs and challenges for 21st century biomedical research, the National Cancer Policy Forum of the Institute of 1caBIG is discussed further in Chapter 2. Note that caBIG and Cancer Biomedical Informatics Grid are registered trademarks. 2Biomedical informatics has been defined as the science that develops methods, tech- niques, and theories regarding how to use data, information, and knowledge to support and improve biomedical research, human health, and the delivery of health care services (http:// www.amia.org/glossary). In the clinical arena, informatics is an applied and interdisciplinary field, at the intersection of information science, computer science, and clinical medicine, to provide improved patient care by harnessing and optimizing health information technology (Miriovsky et al., in press). 1

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2 INFORMATICS NEEDS AND CHALLENGES IN CANCER RESEARCH Medicine (IOM) held a public workshop3 in Washington, DC, on Febru- ary 27 and 28, 2012, using cancer research as a model research enterprise to consider the role of informatics from basic discovery science through translational research, product development, clinical trials, comparative effectiveness research, and health services research. The workshop was designed to raise awareness of the critical and urgent importance of the challenges, gaps, and opportunities in informatics; to frame the issues surrounding the development of an integrated system of cancer informatics tools for acceleration of research; and to discuss solutions for transformation of the cancer informatics enterprise. Specifically, invited speakers and participants considered the following: the design, development, and integration of informatics tools in cancer research; standards for cancer informatics tools; interoperability and harmonization; infrastructure needs for research; data annotation and curation of multiple complex datasets; methods for data use and representation; the implications of implementing effective informatics tools for research; and sustainability, governance, policy, and trust. John Mendelsohn, co-director of the Khalifa Institute for Personal- ized Cancer Therapy at the University of Texas M.D. Anderson Cancer Center and chair of the IOM's National Cancer Policy Forum, stressed that informatics is much more than electronic health care records. He called upon participants to offer practical action items that could help to advance knowledge and improve informatics as applied to cancer research. An overview of key discussion points raised by individual presenters is provided here. 3This workshop was organized by an independent planning committee whose role was limited to the identification of topics and speakers. This workshop summary was prepared by the rapporteurs as a factual summary of the presentations and discussions that took place at the workshop. Statements, recommendations, and opinions expressed are those of the individual presenters and participants, are not necessarily endorsed or verified by the IOM or the National Cancer Policy Forum, and should not be construed as reflecting any group consensus.

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INTRODUCTION 3 OVERVIEW OF KEY POINTS HIGHLIGHTED BY INDIVIDUAL PRESENTERS Cancer researchers and care providers are facing an over- whelming volume of data from a multitude of sources and are hampered by the inability to merge those data or to communicate effectively across disciplines and stakeholders because of divergent standards, lack of interoperability, and other barriers. Biomedical informatics could be advanced by bandoning siloed datasets for large-scale, standardized, a interoperable open source databases with professional annota- tion, analytics, and curation; integrating research and clinical data in an organized and effi- cient manner; supporting an open source platform for the development of software; and considering secondary uses of IT infrastructure as a way to reduce overall costs. The clinical translational research process could be advanced by bringing routinely gathered clinical data up to the same stan- dards as high-quality research data; developing new statistical methods and study designs for use with clinical data; developing better data mining and filtering approaches to sort through massive datasets; connecting genomic and molecular data with clinical data; structuring clinical data appropriately to support research; integrating data that are already in the public domain to gener- ate new hypotheses for testing; ensuring that these processes are guided in a way that is com- patible with a research framework; and using a systems view of disease, which postulates that disease is the result of perturbation of one or more biological networks that leads to altered expression of information, to address the complexity of biology. continued

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4 INFORMATICS NEEDS AND CHALLENGES IN CANCER RESEARCH Clinical cancer care could be improved by developing frameworks that can help clinicians make progres- sively better care decisions with each individual patient, even in the absence of gold standard data; making it easier for every oncology practice to care for a patient on a clinical trial protocol; and developing a coalition as a nonprofit membership organization comprised of all stakeholders, who are deeply committed to actualizing a common vision of data liquidity to achieve person- alized cancer care and a rapid-learning health care system. Patient engagement could be enhanced by building trust through improved transparency, both to the public at large and to patients, about how patient data are used, the typical tools that institutions use to protect data, and oversight and accountability for those protections; empowering patients to drive disruptive innovation in health care; and providing more guidance about how to comply with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. ORGANIZATION OF THE WORKSHOP AND SUMMARY The report that follows summarizes the presentations and discussions by the expert panelists and participants. As introduced by Sharon Murphy, scholar-in-residence at the IOM, the workshop was organized into three main panel sessions. The first panel session provided an overview of the informatics landscape and framed the issues from a variety of stakeholder perspectives, including clinical and translational research, epidemiology and biostatistics, major cancer centers, and cancer cooperative groups (Chapter 2). Following the overview, the keynote address was delivered by Leroy Hood of the Institute for Systems Biology, focusing on the role of informatics in personalized medicine (Chapter 3). The second panel session incorporated several illustrative "use cases" reflecting successful informatics- supported approaches to managing large, complex datasets, including data

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INTRODUCTION 5 collection, storage, and retrieval; data analysis and reporting; and data sharing (Chapter 4). The third panel session challenged participants to look forward and consider new models and potential strategies to advance infor- matics as a community and reap the most value from the huge investment in cancer research (Chapter 5). A proposal for a broad stakeholder coalition as one pathway for addressing the informatics needs of the cancer research community was also described (Chapter 6). In closing the workshop, Amy Abernethy, associate professor of medicine in the Division of Medical Oncology at the Duke University School of Medicine, offered reflections on the themes discussed and summarized the suggestions made for moving forward (Chapter 7). REFERENCES IOM (Institute of Medicine). 2010. A foundation for evidence-driven practice: A rapid learning system for cancer care: Workshop summary. Washington, DC: The National Academies Press. IOM. 2011. Digital infrastructure for the learning health system: The foundation for continuous improvement in health and health care: Workshop series summary. Washington, DC: The National Academies Press. Miriovsky, B. J., L. N. Shulman, and A. P. Abernethy. 2012. In press. Importance of health information technology, electronic health records and continuously aggregating data to comparative effectiveness research and learning health care. Journal of Clinical Oncology.

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